Generalizing Cluster Randomized Control Trial Results to a Target PopulationdissertationsOjiambo, RophencecreatorSteingrimsson, JonAdvisorHogan, JosephReaderBrown University. Department of Biostatisticssponsor2023xi, 36 p.born digitalThesis (Sc. M.)--Brown University, 2023thesesBackground: The treatment effect observed in randomized controlled trials may not reflect the actual effect in the target population if the trial and target populations have differently distributed treatment effect modifiers. The Bridging Income Generation with Group Integrated Care (BIGPIC) study was a cluster randomized trial for cardiovascular risk reduction that assessed the effectiveness of group medical visits (GMVs) and microfinance (MF) relative to the Usual Care (UC) arms on blood pressure reduction. Objective: To generalize the population average treatment effects from the BIGPIC study to a sample target population obtained from the Primary Health Integrated Care Project for Chronic Conditions (PIC4C) project. Methods: To compare the distribution of baseline characteristics between the two populations, standardized mean differences were utilized. A weighted linear mixed-effects model was employed on the BIGPIC data to analyze the primary and secondary outcomes, with inverse estimated odds of trial participation used as weights. We obtained confidence intervals and adjusted for multiple comparisons using a Bonferroni correction. Results: The transportability analyses showed that compared to the UC arm, the mean reduction in systolic blood pressure was 0.2 mm Hg lesser in the GMV-MF arm (98.3% CI, -5.0 to 5.4 mm Hg), 0.6 mm Hg greater in the GMV arm (98.3% CI, -5.7 to 4.5 mm Hg), and 0.3 mm Hg lesser in the MF arm (98.3% CI, -5.1 to 5.6 mm Hg). Conclusion: The attenuated point estimates of the treatment effect and increased uncertainties in the target population estimates compared to the BIGPIC study reflect the major differences in demographics and comorbidities between the two populations.causal inferencetransportabilitygeneralizabilityEnglishRPB20230602