Skip to main content
. 2021 Jul 24;17(3):e1188. doi: 10.1002/cl2.1188

Table B2.

Provisional Tool For Effect Size Data Coding

Description Question Coding
ID Unique study identification # For example, AQC001
Unique effect size identification # For example, AQC001_01, AQC001_02, AQC001_03, and so forth
First author—impact evaluation Surname Open answer
Outcome for effect size (answer for all studies) Outcome Which outcome is being coded?

1 = Productivity

2 = Income

3 = Nutrition or health

4 = Empowerment

5 = Other (specify)

Definition of outcome Please provide the authors definition of the outcome (including description of the subgroup if relevant) Open answer
Exposure to intervention (in months) How long is the intervention exposure itself? #
Evaluation period (in months) The total number of months elapsed between offering an intervention and the point at which an outcome measure is taken post intervention, or as a follow‐up measurement. If <1 month, use decimals (e.g., 1 week would be 0.25) #
Comparison What type of comparison group is used?

1 = No intervention (service delivery as usual)

2 = Other intervention

3 = Pipeline (wait‐list) control (still service intervention the delivery as usual)

Describe Comparison Group If answer above is (1) no intervention, type N/A, if (2) Other Intervention, list what control group is receiving, if (3) Pipeline control, report when the control group will receive the intervention in relation to the treatment group (e.g., 1 year later) Free Text
Counterfactual How is the counterfactual chosen? Free text (e.g., random control trial, propensity score matching, etc.)—Multiple codes are ok
Subgroup analysis Is this effect size data for a subgroup?

0 = No

1 = Yes

Subgroup analysis description If yes to question 2, which type of subgroup? Open answer—this can include separate samples for gender, income, place of residence
Source Which page(s) contain the effect size data? Open answer
Data to be extracted Which type of data to be extracted?

1 = Continuous—means and SDs

2 = Continuous—mean difference and SD

3 = Dichotomous outcome—proportions

4 = Regression data—dichotomous outcome (e.g., logistic regression)

5 = Regression data—continuous outcome (e.g., linear regression)

Analysis type for this effect size What type of analysis was used (Regression, 2SLS, ANCOVA, etc.)? Multiple codes are ok Free text
Effect size data (answer for all studies) Sample size metric Sample size unit of analysis

1 = Individual

2 = Household

3 = Group (e.g., community org)

4 = Village

5 = Other

6 = Not clear

Treatment effect estimated What treatment effect is estimated?

1 = ITT

2 = ATET

3 = ATE

4 = LATE

Sample size (treatment) Initial sample size treatment group #
Sample size (control) Initial sample size control group #
Sample size (total) Initial sample size total #
Observations (treatment) Number of treatment observations after attrition/follow up #
Observations (control) Number of control observations after attrition/follow up #
Observations (total) Total number of control observations after attrition/follow up #
Outcome data—if continuous (Means and SDs) Baseline outcome treatment State result of baseline outcome for treatment group #
SD Baseline outcome treatment State SD of baseline outcome measure for treatment group #
Baseline outcome control State result of baseline outcome for control group #
SD Baseline outcome control State SD of baseline outcome measure for control group #
Outcome in treatment post intervention State result of post intervention outcome for treatment group #
SD Outcome in treatment post intervention State SD of post intervention outcome measure for treatment group #
Outcome in control post intervention State result of post intervention outcome for control group #
SD Outcome in control post intervention State SD of post intervention outcome measure for control group #
Outcome in treatment 1st follow up State result of 1st follow up outcome measure for treatment group #
SD Outcome in treatment 1st follow up State SD 1st follow up outcome measure for treatment group #
Outcome in control 1st follow up State result of 1st follow up outcome measure for treatment group #
SD Outcome in control 1st follow up State SD 1st follow up outcome measure for treatment group #
Outcome data—If continuous (Mean difference and SD/SE at follow up) Mean difference at follow up State mean difference #
SD at follow up State SD at follow up #
SE State SE #
Outcomes data—if dichotomous (Proportions r) Baseline number with outcome in treatment State result of baseline outcome for treatment group #
Proportion with outcome at baseline in treatment State proportion with outcome at baseline in treatment #
Baseline number with outcome in control State result of baseline outcome for treatment group #
Proportion with outcome at baseline in control State proportion with outcome at baseline in control #
Number with outcome in treatment post intervention State number with outcome post intervention for treatment group #
Proportion with outcome in treatment group post intervention State proportion with outcome post intervention in control group #
Number with outcome in control post intervention State number with outcome post intervention for control group #
Proportion with outcome in control group post intervention State proportion with outcome post intervention in control group #
Number with outcome in treatment 1st follow up State number with outcome at 1st follow up for treatment group #
Proportion with outcome in treatment group 1st follow up State proportion with outcome at 1st follow up in treatment group #
Number with outcome in control 1st follow up State number with outcome at 1st follow up for control group #
Proportion with outcome in control group 1st follow up State proportion with outcome at 1st follow up in control group #
Regression data Type of coefficient What is the coefficient type? 1 = raw 2 = standardised 3 = other
Coefficient What is the coefficient estimate? #
Pooled SD of outcome What is the pooled SD of the outcome? #
SE What is the SE of the coefficient estimate? #
t test What is the t statistic associated with the focal predictor? #
p value What is the p value associated with the coded effect? #