Additional file 1 of Estimating the impact of donor programs on child mortality in low- and middle-income countries: a synthetic control analysis of child health programs funded by the United States Agency for International Development
Creators: name: Weiss, William
name: Piya, Bhumika
name: Andrus, Althea
name: Ahsan, Karar Zunaid
name: Cohen, Robert
Publisher: name: figshare
Year: 2022
Subjects: subject: Medicine
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Developmental Biology
subject: Science Policy
subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Additional file 1: Table S2.1a. Donor countries. Table S2-1b. Quadrant 1 and Quadrant 3 countries. Table S2-1c. Post-treatment results: effects and their p values excluding Chad from donor pool. Figs. S2.1a and S2.1b. Treatment effect and 47 placebos (without Chad in synthetic control). Table S2.2a. Percent composition of Quadrant 3 synthetic control analysis. Table S2.2b. Post-treatment results: Quadrant 3. Table S2.2c. Under-five mortality predictor means in Quadrant 3. Figs. S2.2a and S2.2b. Synthetic control analysis and Placebo Results for Quadrant 3 countries. Table S2.3a. Means in pre-intervention period for predictors between synthetic control and test case. Not nested. Table S2.3b. Country weights in Group 1, non-nested. Table S2.3c. Non-nested: effects and their p values. Figs. S2.3a and S2.3b. SCA analysis for Quadrant 1 countries using non-nested option, and Placebo Results. Fig. S2.4a. Synthetic control analysis for Quadrant 1 country: Ghana. Fig. S2.4b. Synthetic control analysis for Quadrant 1 country: Madagascar. Fig. S2.4c. Synthetic control analysis for Quadrant 1 country: Malawi. Fig. S2.4d. Synthetic control analysis for Quadrant 1 country: Mali. Fig. S2.4e. Synthetic control analysis for Quadrant 1 country: Mozambique. Fig. S2.4f. Synthetic control analysis for Quadrant 1 country: Senegal. Fig. S2.4g. Synthetic control analysis for Quadrant 1 country: Uganda. Fig. S2.4h. Synthetic control analysis for Quadrant 1 country: Zambia. Table S2.5a. Predictor means (Web application). Table S2.5b. Weight of control units. Fig. S2.5a. Web application treatment effect by path and gap between treatment and control. Table S2.5c. Bootstrapped confidence intervals for the intervention effect, nonparametric and parametric models. Fig. S2.5b. Placebo test plot for all units (web application). Fig. S2.5c. Boostrap of donor pool (web application). Fig. S2.5d. Nonparametric estimation of treatment effect (web application). Fig. S2.5e. Parametric estimation of treatment effect (web application). Table S2.5d. Predictor means (Stata Replication). Fig. S2.5f. Synthetic control analysis in STATA replicating approach used in web application above. Fig. S2.6a. ‘In-time’ placebo test by path and gap between treatment and control groups. Fig. S2.6b. Nonparametric estimation of treatment effect (in-time placebo test). Fig. S2.6c. Parametric estimation of treatment effect (in-time placebo test). Table S2.7. Weighted average treatment effects in the pre-treatment (1980–1998) and treatment periods (1999–2016). Figs. S2.8a, b and c. Total average per capita funding and total health expenditures per capita. Table S2.9a. Treatment effect estimates under two scenarios: (1) donor pool limited to countries with less than four years of USAID funding in the treatment period; and (2) donor pool limited to countries with no USAID funding during the treatment period. Fig. S2.9a. Synthetic control analysis using a donor pool limited to countries with less than four years of USAID funding in the treatment period. Table S2.9b. Predictor means between synthetic and test case in pre-intervention period, Donor pool with less than four years of funding. Fig. S2.9b. Synthetic control analysis using a donor pool limited to countries no USAID funding in the treatment period. Table S2.9c. Predictor means between synthetic and test case in pre-intervention period, donor pool with no USAID funding. Table S2.10a. Treatment effect estimates using grouped average donor units for placebo testing. Effect size estimates are in units of U5MR. p values are exact, empirical p values based on grouped unit placebo testing. Standardization involves dividing the effect size by RMSPE. Fig. S2.10a. Synthetic control analysis using a donor pool of 48 groups of eight randomly selected countries. Fig. S2.10b. Placebo testing using a donor pool of 48 groups of eight randomly selected countries. Table S2.11.a. Treatment effects (incidence rate ratios) using a difference-in-difference analysis.