Survey Fields & Coding Protocol

Barrera-Osorio et al. 2011 report effects from two different experiments in Bogota in different parts of the city (San Cristobal and Suba). We know that there are two different experiments because the paper declares "As required by the SED, the assessment of the treatments was divided into two separate experiments located in two very similar localities in Bogota, San Cristobal, and Suba." The paper also reports that eligible populations for the tested interventions are different across the two sites: "Eligible registrants in San Cristobal, ranging from grade 6–11..."; and "The tertiary treatment was evaluated separately in an experiment in Suba, where students ranging from grade nine through eleven..." The response to this field would be 2. Jeong et al. 2023 evaluate the differences in how question modules in a survey are ordered in order to examine the effects of survey fatigue. In this case, the coder should enter 0. De Martino et al. 2015 conduct a lab-in-the-field experiment on landholders and annual payment offers for environmental services. As the experiment conducted was hypothetical, the coder should enter 0.

Barrera-Osorio et al. 2011 report effects from two different experiments in Bogota in different parts of the city (San Cristobal and Suba). When coding the experiment in San Cristobal, enter “1” for this field, and then enter “2” when providing information for the experiment in Suba in a new survey.

Parallel: In Barrera-Osorio et al, 2022 , authors evaluate the performance-based reward program by randomizing primary schools into three distinct groups -- recognition, in-kind performance reward, and control [see: Sample and experimental design]. The response to this field is parallel Factorial: In Andrew et al, 2018 researchers randomized towns into four groups. The first received the psychosocial stimulation only (PS), the second received multiple micronutrient supplementation only (MN), the third received both interventions (PS and MN), and the fourth received neither (Control). The response to this field is factorial design because one arm receives the combination intervention PS + MN. Crossover: In Lopez et al, 2022 authors vary in which days doctors received a doctor-specific intervention, and in which days patients received a patient-specific intervention. As doctors (and patients) can cross between the control and treatment groups, the response to this field is crossover design [see: Data collection, figure 2]. In Miguel and Kremer, 2004 authors vary the timing in which three groups of randomly selected schools receive school-based deworming. As the control group crosses over into the treatment group by the end of the study, the response to this field is crossover.

Ichino and Schündeln (2012) used “a two-stage randomized design with blocking”. In the first stage, constituencies were randomly assigned into treatment and control. In the second stage, approximately 25% of the electoral areas in each constituency were randomly selected to receive the intervention. There were two units of randomization: (1) constituency and (2) electoral area. The answer to this field would be “Yes”. In Dolan et al., 2022, the randomization was conducted at site level. 87 sites were randomly assigned into three arms. Although some outcomes were measured and analyzed at the student level, there was only one unit of randomization. So, it is a clustered RCT but did not use a 2-stage randomization of interventions. The answer to this field would be “No”. In Gupta et al., 2024, the unit of randomization was household. Households were randomly assigned to receive the cash transfer intervention at different times, in a cross-over design. The randomization of the timing was conducted at one time and at the household level, so it is a single stage randomization. The answer to this field would be “No”.

Barrera-Osorio et al., 2022 have two distinct interventions. "Out of this sample, 140 schools were randomly assigned to each of the two treatment arms – recognition or in-kind performance rewards – and 140 schools were randomly assigned to the control." For this field, the response would be 2 interventions. [see: Intervention, sample and experimental design] Ozler et al, 2018 have four separate arms and four unique intervention components. Out of the four interventions, one was common to all arms though not part of the status quo in child care centers outside the study sample. The response for this field would be 4 interventions: 1. Learning materials and supplies, 2. teacher training and mentoring, 3. teacher incentives, and 4. parenting training. [see: Interventions] Egger et al., 2022 The two interventions are "cash transfer, high saturation" and "cash transfer, low saturation". The cash transfer provided to the household is the same in both interventions, but in one arm a larger share of households receive the transfer, so the intensity of treatment at the village level is different. This means there are two different (village level) interventions.". [see: Figure A1] Ichino and Schündeln (2012) used “a two-stage randomized design with blocking”. In the first stage, constituencies were randomly assigned into treatment and control. In the second stage, approximately 25% of the electoral areas in each treatment constituency were randomly selected to be visited by registration observers. Because the study presents treatment effects comparisons at the constituency level as well as the electoral area level. There are two interventions in this experiment: (1) treatment at the constituency level and (2) visit by registration observers. In de Andrade et. Al. (2014) geographic blocks are first randomized to communication, control, or inspector categories, and then firms within communication blocks are randomized to a communication treatment or a free-cost treatment, and firms within inspector blocks are randomized to a direct inspector visit or indirect inspector exposure. Because the paper reports all treatment effects at the firm level (e.g., communication vs. control, free-cost vs. control, inspector vs. control, indirect inspector vs. control) and no contrasts are estimated at the block level, only the four firm-level interventions are counted Miguel and Kremer (2004) have a crossover design, in which the deworming treatment is phased in to different schools in different years: “Group 1 schools received free deworming treatment in both 1998 and 1999, Group 2 schools in 1999, while Group 3 schools began receiving treatment in 2001” (page 165). There are three “interventions” in this study, one is the program intervention: “free deworming treatment”. The other two are “timing interventions” specific to the crossover design: treatment in 1998 and treatment in 1999. Note that “treatment in 2001” happened after the study period, so should not be included in the interventions.

Barrera-Osorio et al., 2022 have two interventions. Section 2.1 (Performance-based reward program, p2) states “Rewards took the form of either goods (in-kind) or recognition, depending on the treatment arm to which the teacher’s school was assigned. The value of the reward was determined on an absolute scale, without relative performance comparisons to other teachers.” One intervention is “Public recognition of high-performing teachers”, and the other one is “In-kind reward for high-performing teachers”. Ozler et al, 2018 In this study, section 2.3 (Interventions, p451) describes the interventions. The 4 distinct interventions are – (1) “Provision of play and learning materials (intervention common to all arms)”, (2) “Training and mentoring of teachers”, (3) “Teacher incentives”, and (4) “Parenting training”. Ichino and Schündeln (2012) used “a two-stage randomized design with blocking”. In the first stage, constituencies were randomly assigned into treatment and control. In the second stage, approximately 25% of the electoral areas in each constituency were randomly selected to be visited by registration observers. There are two interventions in this experiment and the labels are: (1) treatment at the constituency level; visit by registration observers.

Ozler et al, 2018 is a cluster randomized trial, in which Community-Based Childcare Centers (CBCCs) were randomized into control, where the children received a learning kit, or the three treatment arms in which children also received learning kits and a combination of different interventions. The number of unit of randomization is 1. The unit is the CBCC because that is the level at which any of the treatments were allocated [see: Study design and sample selection]. Guiteras et al, 2014 is a cluster randomized trial, in which communities were first randomly assigned to receive a community motivation and health information campaign, or an information campaign combined with subsidies for the purchase of hygienic latrines, or a supply-side market access intervention linking villagers with suppliers and providing information on latrine quality and availability, or no interventions. Second, within the subsidy communities, eligible households were randomly assigned to receive subsidy vouchers through household-level lotteries. There are 2 units of random assignment in this experiment: community and household.

Ozler et al, 2018 is a cluster randomized trial, in which Community-Based Childcare Centers (CBCCs) were randomized into control, where the children received a learning kit, or the three treatment arms in which children also received learning kits and a combination of different interventions. The unit of randomization is “Community-Based Childcare Centers (CBCCs)” [see: Study design and sample selection]. Guiteras et al, 2014 is a cluster randomized trial, in which communities were first randomly assigned to receive a community motivation and health information campaign, or an information campaign combined with subsidies for the purchase of hygienic latrines, or a supply-side market access intervention linking villagers with suppliers and providing information on latrine quality and availability, or no interventions. Second, within the subsidy communities, eligible households were randomly assigned to receive subsidy vouchers through household-level lotteries. The two units of random assignment in this experiment are community and household.

Barrera-Osorio et al., 2022 . "Out of this sample, 140 schools were randomly assigned to each of the two treatment arms – recognition or in-kind performance rewards – and 140 schools were randomly assigned to the control." There are 3 treatment arms in this study: 2 treatment arms and 1 control arm. Ozler et al, 2018 has four separate arms and different subsets of 3 interventions are assigned to treatment arms. In this study, there are four arms -T1. Comparison Group: Provision of play and learning materials, T2. T1 + Training and mentoring of teacher, T3. T2 + Teacher incentives, T4. T2 + Parenting training [see: Interventions]. The response for this field is 4. Miguel and Kremer (2004) has three different arms: one arm that receives the deworming treatment in 1998 and 1999, one arm that receives the deworming treatment in 1999, and one comparison arm that receives the treatment after the data is collected. The response for this field is 3.

Barrera-Osorio et al., 2022. "Out of this sample, 140 schools were randomly assigned to each of the two treatment arms – recognition or in-kind performance rewards – and 140 schools were randomly assigned to the control. " So for this field: First, select "None" Next, select "Public recognition of teacher high performance" Finally, select "In-kind rewards for teacher high performance" Knauer et al. (2020) feature a factorial design in which each successive arm receives an additional intervention or two than the other arms. So, for this field: First, for arm 1, the coder would select “None.” For arm 2, the coder would select “Storybooks.” For arm 3, the coder would select “Storybooks + DRT + SMS” For arm 4, the coder would select “Storybooks + DRT + SMS + Booster Training” And finally for arm 5 the coder would select “Storybooks + DRT + SMS + Booster Training + Home Visits.” Miguel and Kremer (2004) have a crossover design, in which the deworming treatment is phased in to different schools in different years. For this field: For arm 1, the coder would select “Free deworming treatment” + “treatment in 1998” + “treatment in 1999” For arm 2, the coder would select “Free deworming treatment” + “treatment in 1999” For arm 3, the coder would select “None”

reatment arm is available in the paper. See Figure 2 in Randomization Section. The coder would input the following for each treatment arm, which was identified in Stage 1: TVET treatment and UCT treatment: 313 TVET treatment and UCT control: 312 TVET treatment and Non-UCT Group: 673 TVET control and UCT treatment:273 TVET control and UCT control: 270 TVET control and Non-UCT Group: 756 In Badrinathan 2021, the number of units assigned to each study arm is only available for the control arms (n = 406). The author does note that an equal proportion was assigned to each of the three treatment arms but does not provide an exact number for the two treatment arms. Thus, a coder would put “406” to indicate the number of units for treatment arm 1 and treatment arm 2, and check the “Number is estimated” column. Then provide “406” for the control arm. For the "call to action" intervention in Garbiras-Diaz and Montenegro 2022, the number of units assigned to each arm is presented in Figure 1 (Randomization Design) as follows: Placebo Control Group: 225 Information Message: 158 Call-to-action Message: 156 Call-to-action Information + Message: 159

In Badrinathan 2021, the number of units assigned to each study arm is only available for the control arms (n = 406). The author does note that an equal proportion was assigned to each of the three treatment arms but does not provide an exact number for the two treatment arms. Thus, a coder would put “406” to indicate the number of units for treatment arm 1 and treatment arm 2, and check the “Number is estimated” column. Then provide “406” for the control arm.

arm is only available for the control arms (n = 406). The author suggests that “Overall, the sample was equally divided between the two treatment and placebo control groups (i.e., one third of the sample in each of the three groups.” (page 1330). Thus, a coder would put “406” to indicate the number of units for treatment arm 1 and treatment arm 2, and check the “Number is estimated” column. Then provide the information “Overall, the sample was equally divided between the two treatment and placebo control groups (i.e., one third of the sample in each of the three groups (page 1330).” in this field.

In Berman et al. (2019), the authors note that they stratify by province, share of respondents in the baseline survey that report at least occasional access to electricity, and the share of respondents reporting that the district governor carries the most responsibility for keeping elections fair. The correct answer here would be 3. In Dupas (2011), the author notes that the randomization procedure is stratified by teacher training status. The correct answer here would be 1. In Ozler et al, 2018, a "block randomization" was used to assign childcare centers in each district to the four study arms. "Centers were grouped based on mean height-for-age (HAZ) and Peabody Picture Vocabulary Test (PPVT - a measure of receptive vocabulary) z-scores, both of which were collected at baseline. The Ministry held a public lottery at each district capital where a representative from each center was asked to draw a colored dot from an envelope to determine that center's treatment status." In this example, the authors created groups (also referred to as bins or blocks) of 4 centers in the same district using PPVT and HAZ. Hence, there is one stratification variable group/bin/block.

Andrew et al, 2018 reports that "Randomization was done at the level of the cluster (town), after stratification by region. Within each of the 3 regions, 8 towns were randomly allocated to each of the 3 treatment groups and the control group using computer-generated random numbers" [Randomization and masking]. The response to this field would be "region" since that is the variable that makes up the strata as indicated in the paper. In Freeman et al. (2022), authors use a stratified randomization design so the response to the previous question asking if the intervention was stratified is "Strata". The authors note "a stratified random design at the woreda-level was used to assign an equal number of study kebeles to either the Andilaye intervention or the control group receiving no intervention". The response to this question is "Woreda", as it is the local term used consistently throughout the paper. In Ozler et al, 2018, a "block randomization" was used to assign childcare centers in each district to the four study arms. "Centers were grouped based on mean height-for-age (HAZ) and Peabody Picture Vocabulary Test (PPVT - a measure of receptive vocabulary) z-scores, both of which were collected at baseline. The Ministry held a public lottery at each district capital where a representative from each center was asked to draw a colored dot from an envelope to determine that center's treatment status." In this example, the authors created groups (also referred to as bins or blocks) of 4 centers in the same district using PPVT and HAZ. The response to this question is “Block (mean height-for-age and Peabody Picture Vocabulary Test z-scores)”.

In Ozler et al, 2018, a "block randomization" was used to assign childcare centers in each district to the four study arms. "Centers were grouped based on mean height-for-age (HAZ) and Peabody Picture Vocabulary Test (PPVT - a measure of receptive vocabulary) z-scores, both of which were collected at baseline. The Ministry held a public lottery at each district capital where a representative from each center was asked to draw a colored dot from an envelope to determine that center's treatment status." The response to this question would be "Yes", as the same set of variables were used for stratification. In Wolf et al. 2019, there are two stages of randomization. In the first stage, the intervention assignment was stratified by district and public/private status of the school. In the second stage, the interventions were assigned within groups created by treatment assignment in the first stage. The stratification variable is “results of the first random assignment”. The response to this question would be "No", since the stratification variables are different across interventions.

Wolf et al, 2018 has 4 interventions: Teacher training and coaching program Parental awareness meetings Text messages for teachers Picture-based paper flyers or texts for parents Based on the information in the section "Randomization", in a first stage of randomization, three of the interventions (teacher training and coaching program; and parental awareness meetings) were stratified by district and public/private status of the school. The text messages for teachers and the texts/flyers for parents were assigned in a second stage of randomization. These interventions were stratified by treatment assignment in the previous stage so that stratification variables for this assignment of interventions to arms would be indicators for being assigned to the two of the arms. So, for this field, the stratification mapping for 4 interventions: Teacher training and coaching program - district and public/private status of the school Parental awareness meetings - district and public/private status of the school Text messages for teachers - indicator for school being part of teacher training and coaching program Picture-based paper flyers for parents - indicator for school being part of program with teacher training & coaching and parental awareness meetings

Ashraf et al., 2010 include treatment effects for the full sample in Tables 2, 3, 4 and 5. The unit of analysis in Table 2 is “Household” for the outcome “Household purchased Clorin (dummy)”. The unit of analysis in Table 3 is also “Household” for the two outcomes: “Water currently treated with Clorin” and “Drinking water contains free Clorin”. The two outcomes from Table 3 are also in Table 4. The unit of analysis in Table 5 is “Household” for two outcomes: “Bottle exhausted?” and “Use Clorin for non-drinking water purposes”. Therefore, there is only ONE (1) unit of analysis in this experiment.

For example, Ozler et al. 2018 include treatment effects estimated using various units of analysis. The treatment effects on child assessments and behavioral problems (Tables 3&4) were estimated at the child level, so the unit of analysis of those outcomes is child. Table 5 includes impacts on parenting quality, for which the unit of analysis is “primary caregiver” (see section 2.4.2, page 453). For impacts on CBCC outcomes in Table 6, the unit of analysis is Community-Based Childcare Center (CBCC).

In Ozler et al, 2018, the paper has a total of 13 tables and 2 figures. Of all the exhibits, 11 tables report treatment effects (i.e. Tables 3 though 13). However, Table 7 reports a robustness check and Table 8 reports quasi-experimental results using treatment assignment as an instrumental variable. These two tables should not be included. Thus, this paper has 9 tables with treatment effects for the full sample. The response for this field is 9. Leaver et al. 2011 include 4 figures and 6 tables. Figure 1 and Tables 1 and 2 report experimental design and baseline characteristics. Figures 2, 3 and 4, and Tables 3, 4 and 5 include treatment effects for the full evaluation sample. Table 6 reports quasi-experimental results. Therefore, there are 6 tables or figures with full sample treatment effects in the paper. The response for this field is 6. Riley 2024 has 6 tables and 2 figures. Figures 1 and 2 present take-up and balance. Table 2 only reports heterogeneous effects, and the rest 5 tables include at least one set of treatment effects for the full sample. The response for this field is 5. In Ara et al. 2019, the outcome variables, Median duration of EBF and Median duration of any breastfeeding should be included in Table 2 because formal p-values are reported in the text. In Kondylis et al. 2016, the authors report treatment effects in Tables 6-10. However, they only report heterogeneous treatment effects by the gender of the farmer. In this case, we would include tables 6-10 for this paper.

For Ozler et al, 2018, the labels are: Table 3, Table 4, Table 5, Table 6, table 7, Table 9, Table 10, Table 11, Table 12, and Table 13. First only enter "Table 3" in this field and answer the questions about Table 3, and repeat the process for each of the rest tables. For Leaver et al. 2021, using the order of appearance in the paper, the labels are: Figure 2, Figure 3, Table 3, Figure 4, Table 4, and Table 5.

In Guiteras et al, 2015, the published manuscript does not show any table in the main paper. Figures 1 & 2 report the treatment effects, however, we can not obtain the precise statistics such as point estimates and standard errors directly from the figures. From the notes of Figure 1, "Figure displays the sum of the estimated coefficients and the control group means found in columns (2) and (6) of table S2 and column (2) of table S3. (A) Any latrine access; (B) hygienic latrine access; (C) open defecation among adults", we learn that the estimated coefficients can be found in tables S2 and S3 in the supplementary materials. Figure 1 includes three outcomes: "(A) Any latrine access; (B) hygienic latrine access; (C) open defecation among adults". Figure 2 includes three outcomes: "(A) Any latrine ownership; (B) hygienic latrine ownership; (C) open defecation among adults." Ashraf et al., 2010 include treatment effects for the full sample in Tables 2, 3, 4 and 5. The outcome in Table 2 is “Household purchased Clorin (dummy)”. There is only one outcome. There are two outcomes in Table 3. They are “Water currently treated with Clorin” and “Drinking water contains free Clorin”. The two outcomes from Table 3 are also in Table 4. The title of Table 5 includes Heterogeneity, however, the table reports the full sample estimates for two outcomes: “Bottle exhausted?” and “Use Clorin for non-drinking water purposes”. Note that only full-sample treatment effects and their outcomes should be included.

• In Guiteras et al, 2015, figures 1 & 2 report the treatment effects of five unique outcomes. The outcome names can be found in the notes below Figure 1 and Figure 2:
• Any latrine access,
• hygienic latrine access,
• open defecation among adults,
• any latrine ownership, and
• hygienic latrine ownership. In the Ashraf et al. (2010) example, the outcome names can be found in Tables 2, 3, 4 and 5, which are:
• Household purchased Clorin (dummy)
• Water currently treated with Clorin
• Drinking water contains free Clorin
• Bottle exhausted?
• Use Clorin for non-drinking water purposes.

For example, Ozler et al. 2018 include treatment effects estimated using various units of analysis. The treatment effects on child assessments and behavioral problems (Tables 3&4) were estimated at the individual child level, so the unit of analysis of those outcomes is child. A coder would choose “Child” for outcomes in Tables (3&4) as their unit of analysis. Table 5 includes impacts on parenting quality, for which the unit of analysis is primary caregiver. For each outcome in Table 5, select “Primary caregiver” as the unit of analysis.

The treatment effects on outcome of “Perceived earnings - Less than 4000” in Table 5 of Avitable and de Hoyos (2018) are reported for the full sample, male sample and female sample. The male and female sample estimates are cited in the abstract and have sufficient information to calculate the effect sizes (i.e with point estimates, SDs, and sample sizes), so they are eligible for extraction. Therefore, for this outcome, the answers should be “full sample results” and “sub-sample results”, both boxes should be checked.

The treatment effects on outcome of “Perceived earnings - Less than 4000” in Table 5 of Avitable and de Hoyos (2018) are reported for the full sample, male sample and female sample. The number of subgroups is “2”.

The treatment effects on outcome of “Perceived earnings - Less than 4000” in Table 5 of Avitable and de Hoyos (2018) are reported for the full sample, male sample and female sample. Enter “Male” and “Female” in each of the subgroup label columns.

The Freeman et al, 2022 study collects household surveys and observation-based data at baseline, midline, and endline. In each round, both survey and observation data were collected at the same time [see: Data collection]. Additionally, Figure 2 illuminates the points in time when each of the data collection rounds was conducted. The response for this field would be 3. Pande & Field, 2008 only use online endline data on loans and repayment in the current paper. The response for this field would be 1. Muralidharan et al. 2021 use administrative data from three sources: 1. Register of landlords, 2. a record of check distribution maintained by the MAOs, and 3. bank records of check encashment [see B. data]. Table 1 suggests that the register data was collected between September and December 2017. Appendix C indicates that the authors received "the up-to-date MAO and bank-based datasets at three points in time: once in July, once in August and once in September 2018. Therefore, there are seven rounds of data collection in the study. The response for this field is 7. De Hoyos et al. 2021 include the following data: i. Student assessments: 2013, 2014, 2015 ii. Student survey: 2013, 2015 iii. Teacher survey: 2013, 2014, 2015 iv. Principal survey: 2014, 2015 v. National assessments: 2016 vi. Internal efficiency: 2013, 2014, 2015, 2016, 2017 Based on data source and time, there are 3 rounds of survey data, as they are conducted at the same time of year, 4 rounds of assessment data (school and national), and 5 rounds of administrative data on internal efficiency. The total would be 12 rounds of data Round 1: Student and teacher surveys in 2013 Round 2: Teacher and principal surveys in 2014 Round 3: Student, teacher, and principal surveys in 2015 Round 4: Student assessment 2013 Round 5: Student assessment 2014 Round 6: Student assessment 2015 Round 7: National assessment 2016 Round 8: Internal efficiency 2013 Round 9: Internal efficiency 2014 Round 10: Internal efficiency 2015 Round 11: Internal efficiency 2016 Round 12: Internal efficiency 2017

Freeman et al, 2022 study collect household surveys and observations-based data at baseline, midline, and end line. [see: Data collection] Additionally, Figure 2 illuminates the points in time when each of the data collection rounds was conducted. The response for this field would be: Baseline Midline Endline Ozler et al, 2018 use three rounds of data collection [see: Data sources] The response for this field would be: Baseline 18-month follow-up 36-month follow-up For Muralidharan et al. 2021, which draw on three administrative data sources and have seven total rounds, the round names would be: Register of landlords September – December 2017 Bank-based dataset July 2018 MAO record dataset July 2018 Bank-based dataset August 2018 MAO record dataset August 2018 Bank-based dataset September 2018 Mao record dataset September 2018 The Freeman et al, 2022 study collects household surveys and observation-based data at baseline, midline, and endline. In each round, both survey and observation data were collected at the same time [see: Data collection]. Additionally, Figure 2 illuminates the points in time when each of the data collection rounds was conducted. The response for this field would be 3. Pande & Field, 2008 only use online endline data on loans and repayment in the current paper. De Hoyos et al. 2021 include the following data: vii. Student assessments: 2013, 2014, 2015 viii. Student survey: 2013, 2015 ix. Teacher survey: 2013, 2014, 2015 x. Principal survey: 2014, 2015 xi. National assessments: 2016 xii. Internal efficiency: 2013, 2014, 2015, 2016, 2017 Based on data source and time, there are 3 rounds of survey data, as they are conducted at the same time of year, 4 rounds of assessment data (school and national), and 5 rounds of administrative data on internal efficiency. The total would be 12 rounds of data Round 1: Student and teacher surveys in 2013 Round 2: Teacher and principal surveys in 2014 Round 3: Student, teacher, and principal surveys in 2015 Round 4: Student assessment 2013 Round 5: Student assessment 2014 Round 6: Student assessment 2015 Round 7: National assessment 2016 Round 8: Internal efficiency 2013 Round 9: Internal efficiency 2014 Round 10: Internal efficiency 2015 Round 11: Internal efficiency 2016 Round 12: Internal efficiency 2017

Freeman et al, 2022 has three rounds of data collection: Baseline, Midline and Endline. Figure 2 provides the timeline for data collection. Baseline: March – May, 2017 Midline: March – May, 2018 Endline: March – May, 2019 The answers to this question would be: For Baseline, Year = 2017, Month = March, Day = -99 For Midline, Year = 2018, Month = March, Day = -99 For Endline, Year = 2019, Month = March, Day = -99

Freeman et al, 2022 has three rounds of data collection: Baseline, Midline and Endline. Figure 2 provides the timeline for data collection. Baseline: March – May, 2017 Midline: March – May, 2018 Endline: March – May, 2019 The answers to this question would be: For Baseline, Year = 2017, Month = May, Day = -99 For Midline, Year = 2018, Month = May, Day = -99 For Endline, Year = 2019, Month = May, Day = -99

Freeman et al, 2022 has three rounds of data collection: Baseline, Midline and Endline. Figure 2 provides the timeline for data collection. Baseline: March – May, 2017 Midline: March – May, 2018 Endline: March – May, 2019 The paper reports the start and end time for data collection directly, so the end dates were not calculated based on the duration information. The answers to this question would be: For Baseline, No; For Midline, No; For Endline, No.

In table 3 from Ozler et al, 2018: - We see 3 comparisons in the first panel of rows: 1. T2 (teacher training) vs. Control 2. T3 (T2 + teacher incentives) vs. Control 3. T4 (T2 + parenting training) vs. Control - We see 1 additional comparison in the second panel of rows that pools all treatment groups into 1 group. 4. Any Treatment (T2, T3, or T4) vs. Control - The fourth panel of rows contains the precision but not treatment effects for additional comparisons: (i) T2 vs. T3 (ii) T2 vs. T4 (iii) T2 vs. T3 The response for this field would be 4. In Table III from Mbiti et al. 2019, we see five comparisons in Panels A, B, and C: 1. Grants (α1) vs. None (α2) 2. Incentives vs. None 3. Combination (α3) vs. None (α3) (α2+α1) 4. Combination vs. Grants+Incentives 5. Combination (α3) vs. Grants (α1) The response for this field would be 5.

In table 3 from Ozler et al, 2018: - We see 3 comparisons in the first panel of rows: 1. T2 (teacher training) vs. Control 2. T3 (T2 + teacher incentives) vs. Control 3. T4 (T2 + parenting training) vs. Control - We see 1 additional comparison in the second panel of rows that pools all treatment groups into 1 group. 4. Any Treatment (T2, T3, or T4) vs. Control Thus, there are 4 different Treatment arms here and so the responses would be: For Treatment arm 1: Select Teacher training only For Treatment arm 2: Select Teacher training & teacher incentives only For Treatment arm 3: Select Teacher training & parenting training only For Treatment arm 4. Select teacher training, teacher training & teacher incentives, and teacher training & parenting training In Table III from Mbiti et al. 2019, we see five comparisons in Panels A, B, and C: 1. Grants (α1) vs. None (α2) 2. Incentives vs. None 3. Combination (α3) vs. None 4. Combination (α3) vs. Grants+Incentives (α2+α1) (α3) (α1) 5. Combination vs. Grants There are 5 different Treatment arms here and the responses would be: For Treatment arm 1: Grants For Treatment arm 2: Incentives For Treatment arm 3: Combination For Treatment arm 4: Combination For Treatment arm 5: Combination

The reference arm for Ozler et al, 2018 table 3 is the control group. Here, coders should select the arm "Learning kits" that was created when they mapped intervention to arms. The five reference arms for Table III from Mbiti et al. 2019 are: 1. None 2. None 3. None 4. Grants + Incentives [select two interventions] 5. Grants

• For table 3 presents 5 outcomes. These are present in the top row of table 3 under the title "Dependent variable". Since these outcome names were collected previously in the survey, here coders should select:
• Attending CBCC: 2012-13
• Enrolled in Primary: 2012-13
• Malawi Developmental Assessment Tool: Total Score
• Malawi Developmental Assessment Tool: Language Skills
• Malawi Developmental Assessment Tool: Fine Motor/Perception Skills For Freeman et al. 2022, Table 2 reports treatment effects on 10 outcomes. Each outcome is listed as a row in the indicator column. The full list of outcomes collected for the study would appear as options, and coders should select:
• Anxiety score
• Depression score
• Emotional distress score
• Well-being score
• High Anxiety
• High Depression
• High Emotional distress
• Poor well-being

In Hanna et al., 2016, table 3 presents 5 periods used to calculate treatment effects. The first row reports a period that includes all four rounds of midline and endline surveys in estimating the treatment effects. The following rows report the treatment effects in each individual period of midline and endline surveys (one per year since the treatment was administered). Coders should report "5" for this field, 1 each for the 4 separate yearly mid- and end-line surveys and 1 for the pooled endline. In contrast, in Ozler et al, 2018, table 3,the title of the table specifies the results are for the 18-month follow up. Coders should report "1" for this field, as only one round of data collection was used in this table.

Baysan, 2022. In the section D. Implementation, the author notes "... Therefore, I estimate only the intent-to-treat (ITT) effect". There are four exhibits in the papers. Figure 1 and Table 2 report full-sample treatment effects using ITT. For Figure 1 and Table 2, the number of estimands is 1. In Banerjee et al., 2020, ITT estimates are reported for all outcomes (Tables 1 - 4). In addition, LATE estimates are also presented for learning outcomes (in Table 4). For estimates in Tables 1 -3, the number of estimands is 1. For Table 4, the number of estimands is 2.

Baysan, 2022. In the section D. Implementation, the author notes "... Therefore, I estimate only the intent-to-treat (ITT) effect". There are four exhibits in the papers. Figure 1 and Table 2 report full-sample treatment effects using ITT. For Figure 1 and Table 2, select “ITT”. In Banerjee et al., 2020, ITT estimates are reported for all outcomes (Tables 1 - 4). In addition, LATE estimates are also presented for learning outcomes (in Table 4). For estimates in Tables 1 -3, select “ITT”. For Table 4, select both “ITT” and “LATE/TOT”.

In Ozler et al, 2018, table 3, the title of the table specifies the results are for the 18-month follow up. So for this field, coders should select "18-month follow up" In Hanna et al., 2016, table 3 presents treatment effects for individual rounds of data collection. For the individual rounds, coders should select the corresponding round names (e.g., 0-12 month survey, 13-24 month survey, etc.). For the pooled round, coders should select all four of the individual rounds.

In Riley, 2024, E. The empirical Strategy describes the specifications in equation (1) that strata dummies and the baseline value of the outcome (if measured at baseline, otherwise excluded) are included in the estimation of treatment effects. In Table 1, where full sample results are reported, the notes indicate "All regressions include strata dummies and include the baseline value of the outcomes." The response to this question is: 1 In Ashraf et al., 2010, according to tables notes, in Table 2, two specifications are used for the outcome: with and without baseline controls (including baseline Clorin usage and water cholorination, general health behaviors and attitudes, household demographics, and locality fixed effects). One specification is preferred by IDEAL and the other preferred by the authors, so both of them should be extracted. The response to this question is: 2

Riley, 2024 only estimates ITT effects. E. Empirical Strategy describes the specifications in equation (1) that strata dummies and the baseline value of the outcome (if measured at baseline, otherwise excluded) are included in the estimation of treatment effects. In Table 1, Table 4, and Table 6 where treatment effects for the full sample are present, the notes indicate " All regressions include strata dummies and include the baseline value of the outcomes." In this case, response to this question is: - Strata fixed effects, Baseline outcomes, and No controls. Barrera-Osorio et al., 2011 report ITT effect with three sets of specifications for the outcomes in Tables 3: no controls, with demographic controls, and with both demographic controls (including all variables listed in Table 2, the square of the child's age, the number of years too old a child is for his or her grade, and indicator variables for the child's marital status, the family's marital status, grade and whether or not the child is over the average age for his or her grade) and school fixed effects. The stratification variables for randomization are locality, type of school (public/private), gender and grade level. Since no specification directly controls for the strata fixed effects, the specifications with demographic controls, and with both demographic controls and school fixed effects are categorized into the same IDEAL specification category. The response to this questions is: - Static controls [referring to the specifications with demographic controls, and with both demographic controls and school fixed effects] In Li et al., 2022, only Table 5 reports TOT effects on parental knowledge, attitude and practices. The tables note reads "In all regressions, we controlled for baseline parental knowledge, attitude and practices, child characteristics, and family characteristics." Child characteristics include baseline development scores which are the stratification variables of randomization (see Randomization and masking). The response to this question is: -Adjustment for strata fixed effects, baseline value of outcome, and other controls that are either observed before treatment assignment or considered static over the study period.

In Table 1 of Riley, 2024, there are three outcomes and 2 different comparisons using the same specifications. Therefore, there are 6 eligible treatment effects for this table. In Ashraf et al., 2010, according to table notes, in Table 2, two specifications are used for the outcome: with and without baseline controls. One specification is preferred by IDEAL and the other preferred by the authors, so both of them should be extracted. The third column restricts the sample to the follow-up survey sample and should be included as well as IDEAL collects up to 2 estimation periods. Therefore, there are 3 eligible treatment effects in the table.

In Table 1 of Riley, 2024, there are three outcomes and 2 different comparisons using the same specifications. For each outcome, select the corresponding contrast, for example, Mobile Account - Cash or Mobile Disbursement - Cash.

For all the 6 treatment effects in Table 1 of Riley, 2024, the empirical specifications are: Strata fixed effects + Baseline outcome + No controls. For the 3 treatment effects in Table 2 of Ashraf et al., 2010, the empirical specifications for two of them (column 1 and Column 3) are No controls. For the column 2 treatment effect, the empirical specifications are Static controls.

For all the 6 treatment effects in Table 1 of Riley, 2024, the estimation period is “Endline”. For the 3 treatment effects in Table 2 of Ashraf et al., 2010, the estimation periods for two of them (column 1 and Column 2) are “Door-to-door experiment + Follow-up survey”. For the column 3 treatment effect, the estimation period is “Follow-up survey”.

Baysan, 2022. In the section D. Implementation, the author notes "... Therefore, I estimate only the intent-to-treat (ITT) effect". There are four exhibits in the papers. Figure 1 and Table 2 report full-sample treatment effects using ITT. For all the treatment effects in Figure 1 and Table 2, select “ITT”. In Banerjee et al., 2020, there are 12 treatment effects to report from Table 4 from columns 3, 4, 5, 7. For treatment effects in columns 3, 4, 5, the estimand is ITT, and for column 7, it’s LATE/TOT.

In Banerjee et al., 2020, there are 12 treatment effects to report from Table 4 from columns 3, 4, 5, 7. For treatment effects in columns 3, 4, 5, they are preferred by IDEAL, so the box should be left blank. For treatment effects from column 7, they are preferred by the authors and different from IDEAL, so this box should be checked.

-In Alatas et al., 2012, the unit of randomization is subvillage. Subvillages were drawn from villages. [See section B: Sample], so the “Sampling unit 1” should be “Villages”. Villages were drawn from another larger unit – province, so “Sampling unit 2” should be province. Since the province is a geographic unit, the names should also be included in the label, so the answer would be “Provinces (North Sumatra, South Sulawesi, and Central Java)”. The label for the next sampling unit – “Sampling unit 3” - would be the unit where provinces were drawn. The provinces were from the country, so the answer would be “Country”. Till the country, the sampling unit has reached the largest possible unit and there should be no more sampling unit entered for this unit of randomization. In total, there are three sampling units for “Subvillages”. -In the same paper, there are two units of analysis different from the unit of randomization: household and subvillage head (or using answer from stage 1: individual-political/social leader). Both units were drawn from the subvillages, which were the unit of randomization. So, for both household and subvillage head, the “Sampling unit 1” would be “Villages (unit of randomization)”. There are no more sampling units to be entered as it reaches a unit of randomization - Leaver et al, 2021, has two units of randomization: labor market (i.e. district-by-subject-family teaching job market) and school. For this paper, you will see the questions for each of the units of randomization separately. First, “Schools” were drawn from schools with “at least one new post that was filled and assigned to an upper-primary grade” (see Second-Tier Randomization: Experienced Contracts, page 2220) , so “Sampling unit 1” would be “Schools with one new post filled in an upper primary grade”. Sampling unit 1 was drawn from “Schools to which REB had allocated the new posts to contracts”, which should be “Sampling unit 2”. “Schools to which REB had allocated the new posts to contracts” were sampled from “labor markets”, which is another unit of randomization. So, “Sampling unit 3” should be “Labor markets (unit of randomization)”. The sampling units are complete for “Schools” as it reaches another unit of randomization. The next group of sampling units are for “Labor markets”. Labor markets were drawn from districts. The paper did not specify the names of the districts. “Sampling unit 1” would be “Six districts”. The districts were directly sampled from the country, so “Sampling unit 2” would be “Country”. Since the country is the largest possible sampling unit, there will be no more sampling unit for this unit of randomization.

-In Alatas et al., 2012, the unit of randomization is subvillage. Subvillages were drawn from villages. No inclusion or exclusion criteria were mentioned in the sampling process. Therefore, the answer to this field would be “No”. Villages were drawn from another larger unit – provinces. In Footnote 8, an exclusion criterion was stated: “An additional constraint was applied to the district of Serdang Bedagai because it had particularly large sized subvillages. All villages in this district with average populations above 100 households per subvillage were excluded.” The answer to this field would be “Yes”.

-In Alatas et al., 2012, the unit of randomization is subvillage. Subvillages were drawn from villages. No inclusion or exclusion criteria were mentioned in the sampling process. Villages were drawn from another larger unit – provinces. In Footnote 8, an exclusion criterion was stated: “An additional constraint was applied to the district of Serdang Bedagai because it had particularly large sized subvillages. All villages in this district with average populations above 100 households per subvillage were excluded.” The answer to this field would be: “All villages in the district of Serdang Bedagai with average populations above 100 households per subvillage were excluded.”

-In Alatas et al., 2012, the unit of randomization is subvillage. Subvillages were drawn from villages. As the paper notes “For each village, we obtained a list of the smallest administrative unit within it (a dusun in North Sumatra and Rukun Tetangga (RT) in South Sulawesi and Central Java), and randomly selected one of these subvillages for the experiment” [See Section B: Sample, page 1211]. So, the sampling method was “random”. In the same paper, there are two units of analysis that are different from the unit of randomization: household and subvillage head (Answer from Stage 1: individual-political/social leader). The paper stated that “From this census, we randomly sampled 8 households from each subvillage plus the head of the subvillage”. For households, the response would be “random”. For subvillage heads, the answer would be “Total universe”, because all the subvillage heads were included in the sample. -In Briaux et al. 2020 eligible households were selected using a random-route sampling method. It is a non-probability sampling method because the probability of selecting a household is unknown although the “starting points” were selected randomly. The response would be “Non-random”.

In Alatas et al., 2012, the “B. Sample section” describes how the experimental sample was drawn. “The sample for the experiment consists of 640 subvillages spread across three Indonesian provinces: North Sumatra, South Sulawesi, and Central Java. The provinces were chosen to represent a broad spectrum of Indonesia’s diverse geography and ethnic makeup. Within these three provinces, we randomly selected a total of 640 villages, stratifying the sample to consist of approximately 30 percent urban and 70 percent rural locations.8 For each village, we obtained a list of the smallest administrative unit within it (a dusun in North Sumatra and Rukun Tetangga (RT) in South Sulawesi and Central Java), and randomly selected one of these subvillages for the experiment. These subvillage units are best thought of as neighborhoods.Each subvillage contains an average of 54 households and has an elected or appointed administrative head, whom we refer to as the subvillage head.” Footnote 8 added additional details, “An additional constraint was applied to the district of Serdang Bedagai because it had particularly large sized subvillages. All villages in this district with average populations above 100 households per subvillage were excluded. In addition, five of the originally selected villages were replaced prior to the randomization due to an inability to reach households during the baseline survey, the village head’s refusal to participate, or conflict.”

One intervention in Lyall et al. 2020 is a technical and vocational education training program, and a description of the intervention would be: The intervention consisted of three livelihood training components bundled together. “First, participants were enrolled in either three- or six-month TVET [Technical and Vocational Education and Training] courses at one of four VTCs. These courses ranged from motorcycle and mobile phone repair to metal works and computer services to tailoring and English-language tutoring. While content was trade-specific, each course aimed to build practical marketable skills and to improve prospects for full-time employment in the local economy. Second, students were concurrently enrolled in a “soft skills” course designed to bolster business skills and employment opportunities by networking with key local market actors. As part of this course, participants received instruction in time management, decision-making, leadership, and negotiation. Third, participants who successfully completed technical TVET courses were provided with a small start-up kit of trade-specific tools upon graduation.(p130)" A description of the phone-monitoring intervention in Muralidharan et al. 2021 could be: “The call center placed calls to the mobile phone numbers of sampled farmers. If a call did not connect, the call center would attempt to reach that number up to five more times over the following two days before giving up. If connected, the call center operator verified the respondent’s identity and identified themselves as conducting a survey on behalf of the Government of Telangana to understand the respondent’s experience with the Rythu Bandhu Scheme. Calls collected information on whether, where, and when the farmer received their check; whether and when they encashed it; any problems receiving or encashing the check (including time costs and bribes); how they used the funds; suggestions for future rounds of RBS; and overall satisfaction with RBS [Rythu Bandhu Scheme]. (p60)”

There were three sets of eligibility criteria for the two iron interventions in Pasricha et al., 2021. 1. “Children 7.5 to 8.5 months of age” (p983) were eligible. 2. “Children with marked anemia (a hemoglobin level of <8.0 g per deciliter), current febrile illness, severe acute malnutrition, a known inherited red-cell disorder or previous transfusion, or known developmental delay were excluded” (p983). 3. Children in households with iron levels in drinking water exceeding 1 mg per liter were excluded. The eligibility criteria for the conditional cash transfer intervention in Filmer et al. 2023 were described as “Households are eligible if they have a proxy means test score below the provincial poverty line and contain children ages 0 to 14 years or a pregnant woman” (p329). Note that in this paper, the eligibility criteria for the intervention were narrower than the sampling inclusion/exclusion criteria as the sample included ineligible households as well. In Lyall et al. 2020, both interventions in the INVEST programs targeted “at-risk youth” and “internally displaced persons”. The paper noted that the recruitment was done by a consortium of actors but there were no data on “individuals who were deemed ineligible for participation” (p132). So, the eligibility criteria for the two interventions should be “At-risk youth and internally displaced persons”.

-The economic assistance intervention in Lyall et al 2020 was part of a larger program named “INVEST”. The answer would be “component of Introducing New Vocational Education and Skills Training (INVEST) program”. -The private school voucher intervention in Muralidharan and Sundararaman (2015) was called “The AP Private School Choice project”. The answer would be “The AP Private School Choice project”.

Crost, Felter, and Johnston (2016) evaluated part of a conditional cash transfer program (Pantawid Pamilya) in the Philippines. In 2019, the program was scheduled to begin in 19 municipalities of 8 provinces. Among the 19 municipalities, 8 were randomly selected to be part of the evaluated experiment. The remaining received the intervention as scheduled. In this case, the scale of the implemented intervention was larger than the treatment group in the experiment. So, the response to this question would be “No, intervention scale larger than study scale”. In Mbiti et al. (2019), the interventions were implemented at the school level, affecting all students in the focal grades. The study only collected data from a randomly selected group of students and households and included them in the analysis. Specifically, 10 students from each focal grade were sampled and 10 households were selected from each school for data collection. [See III.B.Data] Therefore, the scale of the implemented intervention was larger than the study sample. The response would be “No, intervention scale larger than study scale”.

Crost, Felter, and Johnston (2016) evaluated part of a conditional cash transfer program (Pantawid Pamilya) in the Philippines. In 2019, the program was scheduled to begin in 19 municipalities of 8 provinces. Among the 19 municipalities, 8 were randomly selected to be part of the evaluated experiment. The remaining received the intervention as scheduled. In this case, the scale of the implemented intervention was “19 municipalities of 8 provinces in the Philippines”. In Mbiti et al. (2019), the interventions were implemented at the school level, affecting all students in the focal grades. The study only collected data from a randomly selected group of students and households and included them in the analysis. Specifically, 10 students from each focal grade were sampled and 10 households were selected from each school for data collection. [See III.B.Data] The response to this field could be “All students and households in treatment schools.”

Using the same example from Lyall et al. 2020, the TVET intervention has three components: 1) TVET courses, 2) a “soft skills” course and 3) a start-up kit of trade-specific tools. One answer could be “There are three components in the intervention. The TVET courses were either three months or six months long. The duration of the “soft-skill” course was not stated. The third component was a start-up kit of trade-specific tools.” The “Early Education Program (Programa Educación Inicial or PEI)” in Cardenas, Evans and Holland (2023) was an early childhood education intervention that included 65 group sessions during nine months with each session lasting for about 2 hours. One answer could be “The intervention included 65 group sessions during a nine-month term. ‘These sessions included (1) up to 26 sessions for caregivers and parents (men and women), (2) up to 18 sessions for caregivers and parents (men and women) focused on children, (3) up to 5 sessions for parents who are men, and (4) up to 8 sessions for pregnant women. In addition, promotoras [facilitators who receive two weeks of annual training, educational materials, and a small stipend] could organize up to 8 additional sessions for diagnosis, planning, and evaluation.’ ‘Sessions were generally held for two hours, and the frequency of these sessions is defined through an initial agreement between the promotoras and participants, often one or more times per week between the sessions of type (a) and (b).’” (page 5131)

the program in Part VI: Program Cost-Effectiveness. The cost data for the intervention and details regarding program cost per student are mentioned in the appendix C. The answer to this question would be “Depending on the year type (fiscal, school) and child (enrolled, attending), the annual program cost per student ranges from a low of $77 to a high of $184.” (Appendix C).

For Lyall et al, 2020, the start date is October 2015. which the coder would enter in a month-date format. [See: Study Timeline in Supplementary Material]. The response would be “2015” for “Year”, “October” for “Month” and “-99” for “Day”. For Chong et al, 2015, the authors write "We randomly assigned voting precincts to a campaign spreading information on corruption and public expenditure conducted one week before the 2009 municipal elections in Mexico." The coder would write "2009" and then select “unsure” in the follow-up question. [See: Introduction, Experimental Design and Implementation] The answer would be “2009” for “Year” and “-99” for “Month” and for “Day”.

2016.[See: Study Timeline in Supplementary Material]. The answer would be “2016” for “Year”, “May” for “Month”, and “-99” for “Day”.

For the timeline provided indicates that outcome measures were collected between May 19 and May 23, 2019. The answer to the question would be “No”.

In Bos et al., 2024, the authors discussed the compliance issue of the treatment arms in [4.2. Receipt and use of program materials by households]. “As per the intervention guidelines, households in the treatment group should have received four materials: a child development card, a household picture book, a nature picture book, and a key message booklet. However, Table 6 shows that due to imperfect compliance, the differential likelihood of receipt of the child development card, household picture book, and nature picture book between treatment and control households was approximately 49 percentage points (instead of 100 under perfect compliance). Furthermore, 2%–3% of households in the control group received these materials.” In this example, although “imperfect compliance” is used to describe the fact that only 49% of treatment households received the intervention materials. That was actually a result of low implementation fidelity rather than non-compliance to assigned treatment status. However, the receipt of materials by the control households was a non-compliance issue as they were not assigned to get the intervention (i.e. materials). Therefore, the answers to this field would be “Yes”. for the treatment study arm, “-99”; for the control study arm, “-88” and then enter “2%–3% of households in the control group received these materials” in the open-text field.

In Bos et al., 2024, the authors discussed the compliance issue of the treatment arms in [4.2. Receipt and use of program materials by households]. “As per the intervention guidelines, households in the treatment group should have received four materials: a child development card, a household picture book, a nature picture book, and a key message booklet. However, Table 6 shows that due to imperfect compliance, the differential likelihood of receipt of the child development card, household picture book, and nature picture book between treatment and control households was approximately 49 percentage points (instead of 100 under perfect compliance). Furthermore, 2%–3% of households in the control group received these materials.” In this example, although “imperfect compliance” is used to describe the fact that only 49% of treatment households received the intervention materials. That was actually a result of low implementation fidelity rather than non-compliance to assigned treatment status. However, the receipt of materials by the control households was a non-compliance issue as they were not assigned to get the intervention (i.e. materials). Therefore, the answers to this field would be “2%–3% of households in the control group received these materials” in the open-text field.

assigned to the franchise treatment attended at least one day of business training (which was the first component of the franchise treatment), and 44 percent completed the program and launched a business.' (page 8) In this question, we want the proportion of a treatment that participated in 'some proportion of treatment' (i.e. take-up), so the answer will then be 61%. For the grant arm, in Table A2 [Compliance and Attrition] from appendix [column: Grant], we see that 95% of the grant arm received the grant. Although both the section in the paper and the appendix Table A2 were titled “Compliance and Attrition”. The “compliance” rates for the treatment groups were technically “take-up” rates. Therefore, the response would be: Take-up for franchise arm: 61. Take-up for grant arm: 95.

In Abimpaye et al., 2020, Table 2 is a balance table reporting characteristics by study arm. Coders should answer 'Yes' and then enter “Table 2”. In Carneiro et al., 2024, two balance tables are presented, one for baseline and one for follow-up. These tables are located P1128 Table 1: Baseline Balance, Household and Child Characteristics and P1130: Table 2: Balance of Household and Child Characteristics at Follow-Up. The answer should be ‘Yes’ and then type “Table 1 and Table 2”.

(2018), reports heterogeneous treatment Avitable and de Hoyos effects by gender, household income, math readiness, and Spanish readiness. The four variables should be reported here. Select Gender, Income and Other (specify) for math readiness and Spanish readiness.

implemented the intervention. The answer to this field would be “Innovations for Poverty Action”. For Gaikwad and Nellis 2021, the intervention was implemented by “an NGO” without specifying the name. The answer to this field would be “An anonymous NGO”. In Carneiro et al., 2024, the implementer was not specified in the paper. Thus, the answer to this field would be “Not specified”.

The implementer for the experiment in Chong et al. 2015 was the "Innovations for Poverty Action”. It is an NGO, so the answer to the field would be “NGO”. In Ozler et al. 2018, as noted on page 4, “Under PECD, the Government implemented the following interventions – in partnership with Save the Children and UNICEF”. The implementers are the government, “Save the Children”, and UNICEF. Their types are government, NGO, and multilateral and bilateral international organizations.

In Ozler et al. 2018, there is an “Acknowledgements” section in the paper (page 19). The text in the section should be copied in this field. “We acknowledge funding from three World Bank trust funds - Rapid Social Response Multi-Donor Trust Fund (TF098514), Strategic Impact Evaluation Fund (TF013561), and Impact Evaluation to Development Impact Trust Fund (TF018796).” For Chong et al. 2015, the acknowledgment is stated in footnote 1. Therefore, the text of footnote 1 should be copied here. “This article circulated previously with the title: “Looking Beyond the Incumbent: Exposing Corruption and the Effect on Electoral Outcomes.” We acknowledge partial funding from the Inter-American Development Bank. Supplementary material for this article is available at the “Supplements” link in the online edition. Data and supporting material necessary to reproduce the numerical results for this article are available at http://anadelao.commons.yale.edu.”

In Brudevold-Newman et al., 2023, the name of the organization where the trial is registered is stated in the footnote page 1. 'The study was registered at the AEA RCT registry under ID number AEARCTR-0000459.' The answer should be: AEA RCT registry

In Brudevold-Newman et al., 2023, the ID registration is stated in the footnote page 1. 'The study was registered at the AEA RCT registry under ID number AEARCTR-0000459.' So, the response to this field is “AEARCTR-0000459”.

is stated in the footnote page 5. 'The trial is registered at https://www.socialscienceregistry.org/trials/459.' The answer should be: https://www.socialscienceregistry.org/trials/459

Abimpaye et al., 2020 reports one review with "Rwanda National Ethics Committee" as the ethics review body. So, the response to this field is “1”. Athey et al., 2023 obtained ethical reviews from three committees: “The study protocols were approved by Cameroon’s National Ethics Committee for Human Subjects Research, the National d’Ethiquede la Recherche pour la Humaine (CNERSH; decision no. 2019/08/1183/CE/CNERSH/SP). The study also received administrative authorization from the Ministry of Health’s [Min Division of Health Operations Research (DROS; decision no. D30- 760/L/MIN-SANTE/SG/DROS)]. Last, the protocols were also approved by our own institutional review board (decision no. 780/CIERSH/DM/2018).” The answer to the field would be “3”.

Abimpaye et al., 2020 explicitly states that "This study was reviewed and approved by the Rwanda National Ethics Committee." The answer to this field would be “Rwanda National Ethics Committee”. The study Barrera-Osorio et al., 2022 has an IRB approval number with the organization Columbia University. The response to this field would be “Columbia University”.

Abimpaye et al., 2020 notes that "This study was reviewed and approved by the Rwanda National Ethics Committee”, but no reference or case number was reported. The answer to this field would be “Not stated”. In Barrera-Osorio et al., 2022, the IRB approval number is reported as AAAF4126. The response to this field would be “AAAF4126”.

For example, from Knauer et al, 2019 "we assessed caregiver literacy by asking caregivers to read a simple, five-word (second-grade level) sentence in each language adapted from the Early Grade Reading Assessment (EGRA; Gove & Wetterberg, 2011).", "mental health was measured using an adapted version of the Centers for Epidemiological Studies-Depression scale CES-D; Radloff, 1977; scores range 0–60)." Here the tool used for each outcome is: Literacy: Early Grade Reading Assessment (EGRA) (Gove&Wetterbery, 2011). Mental health: Centers for Epidemiological Studies-Depression scale CES-D (Radloff, 1977). The number of tools is 2.

For example, from Knauer et al, 2019 "we assessed caregiver literacy by asking caregivers to read a simple, five-word (second-grade level) sentence in each language adapted from the Early Grade Reading Assessment (EGRA; Gove & Wetterberg, 2011).", "mental health was measured using an adapted version of the Centers for Epidemiological Studies-Depression scale CES-D; Radloff, 1977; scores range 0–60)." Here the tool used for each outcome is: Literacy: Early Grade Reading Assessment (EGRA) (Gove&Wetterbery, 2011). Mental health: Centers for Epidemiological Studies-Depression scale CES-D (Radloff, 1977). The answers would be: (1) EGRA and (2) CES-D

For example, from Knauer et al, 2019 "we assessed caregiver literacy by asking caregivers to read a simple, five-word (second-grade level) sentence in each language adapted from the Early Grade Reading Assessment (EGRA; Gove & Wetterberg, 2011).", "mental health was measured using an adapted version of the Centers for Epidemiological Studies-Depression scale CES-D; Radloff, 1977; scores range 0–60)." The descriptions are: Literacy: Adapted from Early Grade Reading 1. Assessment (EGRA) (Gove&Wetterbery, 2011). 2. Mental health: An adapted version of the Centers for Epidemiological Studies-Depression scale CES-D (Radloff, 1977).

In Muralidharan et al. 2021, one outcome variable is listed as “Ever encashed” in the tables (from Table 3). The outcome variable measured whether a farmer ever encashed a benefit check during the valid period. Therefore, a response to this field would be “Encashed the program benefit check”. The unit does not need to be specified here because it will be clear from the unit of analysis field. One outcome variable of Table 4 in Barrera-Osorio et al. 2022 is “Total Scores”. The test scores were language and math combined for all children aged 5 to 10 measured at the second follow-up. So, an answer to this field would be “Language and math combined test score for children aged 5 to 10, measured 1.5 years after school in operation”. The target population unit needs to be mentioned in this case as the age restriction may not be obvious from the unit of analysis - child. In Chong et al., 2015, one outcome variable in Table 4 is “Turnout”. The table notes indicate that the outcome variable refers to “total number of votes divided by number of registered voters multiplied by 100”. Therefore, one response to this field would be “Registered voter turnout (percentage)”.

Banerjee et al., 2019, describe the outcome variable “HIV knowledge” explicitly as an index. The indicators that enter the index are also presented. “HIV knowledge measures how aware an individual is of the methods of transmission, the availability of drugs, and the timing of testing for HIV. Higher values of this index correspond to greater awareness.” The response to this question would be “Yes”. In Barrera-Osorio et al, 2011, one outcome is "monitored school attendance rate" (Table 3). According to the authors, "We collected attendance data during the last quarter of 2005 through direct observation. For this purpose, the team assembled a group of assistants who randomly visited schools and classes. The assistants directly called the roll of all students, and students were marked absent if they were not physically present in the classroom." [C. Data]. This variable is constructed from many separate observations, but it does not combine multiple alternative methods of measuring attendance for the same student, so it is not an index. The response to this question would be “No”. In Wolf et al., 2019, “Teacher motivation” is an index outcome although it is not called an index. The “Measures” section mentioned that “Teacher’s motivation was measured using five items adapted from Bennell and Akyeampong (2007) as reported in Wolf, Aber et al. (2015).” There are multiple components in the outcome variable, thus it is an index outcome. The response to this question would be “Yes”. In Barrera-Osorio et al., 2022, “Total score” is an index outcome consisting of language score and math score. The paper does not explicitly state that the variable is an index. However, the Data section stated that children were tested on language and math, so we can infer that “Total score” is an index. The response to this question would be “Yes”.

In Freeman et al. 2022 (Table 3), the outcome variable “Water and sanitation insecurity scores: Water – HWISE Scale” is an index outcome. The “Outcome of Interest” section and table notes describe the details of the variable. One answer to this field would be “Water insecurity was measured through the Household Water Insecurity Experiences (HWISE) scale. HWISE includes 12 items with four response categories (never, rarely, sometimes, often/always). The score is the sum of responses, ranging from 0–36. A higher score indicates greater household water insecurity.” In Barrera-Osorio et al., 2022, “Total score” is an index outcome consisting of language score and math score. Both components were also outcome variables.. The information in the paper on the “Total score” suggests it is simply the sum of the two scores. One response to this field would be “The total score is the sum of the language and math scores.”

For the outcome variable “Weight for age Z-score” in Table 2 of Pickering et al. (2019), the standardization is external because it uses the WHO child growth reference distribution. The response to this field would be “Externally standardized”. In Leaver et al. (2021), “Student learning” in Table 3 was internally standardized. Table 2 notes suggest that “student learning IRT scores are standardized based on the distribution in the experienced FW [Fixed-wage contract] arm”. The response to this field would be “Internally standardized”

For the outcome variable “Weight for age Z-score” in Table 2 of Pickering et al. (2019), the standardization is external because it uses the WHO child growth reference distribution. However, the paper does not specify the standardization details. The response to this field would be “Not stated”. In Leaver et al. (2021), “Student learning” in Table 3 was internally standardized. Table 2 notes suggest that “student learning IRT scores are standardized based on the distribution in the experienced FW [Fixed-wage contract] arm”. The response to this field would be “student learning IRT scores are standardized based on the distribution in the experienced FW [Fixed-wage contract] arm”.

For example, from Knauer et al, 2019 "we assessed caregiver literacy by asking caregivers to read a simple, five-word (second-grade level) sentence in each language adapted from the Early Grade Reading Assessment (EGRA; Gove & Wetterberg, 2011).", "mental health was measured using an adapted version of the Centers for Epidemiological Studies-Depression scale CES-D; Radloff, 1977; scores range 0–60)." Here the tool used for each outcome is: Literacy: Early Grade Reading Assessment (EGRA) (Gove&Wetterbery, 2011). Mental health: Centers for Epidemiological Studies-Depression scale CES-D (Radloff, 1977). These were obtained from the section "Measures: Caregiver survey". Notice for each tool, there is a citation associated with it.

In Sukhtankar et al., 2022, the authors measure DIRs, or Domestic Incident Reports, which represent civil complaints of domestic violence. This is the count of DIRs in a given time period at a given police station. The response to this field would be No. In Cheema et al., 2022, for the measure of women's voter turnout is a variable which is coded as 1 if the respondent voted, and 0 if the respondent did not vote (operationalized by observing the ink from voting day on the respondent's thumb). The response to this field would be Yes. In Freeman et al., 2022, “Poor well-being” is a binary variable. Please note that the variable was dichotomized from a continuous well-being score, “with scores below 13 indicating poor well-being”. Because the variable entering the estimation is a binary variable, the response to this field would be “Yes”.

In Wolf et al., 2019, the “Impact analysis” section (page 23) suggests that “multi-level modeling” was used to estimate the treatment effects on child, teacher and classroom outcomes. So, we can assume “multi-level or hierarchical model/regression” is the estimation model for all treatment effects in the paper, unless it is specified otherwise for a particular case. Table 4 reports treatment effects for teach-level and classroom-level outcomes. Footnote “a” suggests that “teacher turnover” treatment effects were estimated with multinomial logistic regressions. Thus, for those treatment effects, the estimation model should be “Logistic regression”, while for the rest in the same table, the answer should be “multi-level or hierarchical model/regression”. In Ara et al., 2019, Table 3 presents group means by study arm and the p-value associated with the group mean difference without directly reporting the mean difference. In this case, a coder should select “T-test (mean-comparison test)” for treatment effects in the table.