Comparing Regression Adjustment, Matching, and Inverse Probability Weights in Small Sub-Populations in the HIV SUCCESS Consortium: A Real-World Data Example

作者：Lydia N. Drumright, George A. Yendewa, Mari M. Kitahata, Edward Cachay, Heidi M. Crane, Kenneth H. Mayer, Rob J. Fredericksen, Laura Bamford, Michele Kipke, Brian Mustanski, Marianna Baum, Geetanjali Chander, Ross Baiers, Joseph A. Delaney, Sari Reisner, Dominique Heinke, Richard D. Moore, Michael S. Saag, Katerina Christopoulos, S Napravnik, Catherine R. Lesko, Bridget M. Whitney, Ryan P. Kyle, Luis Parra · 发表于：UNC Libraries · 年份：2026 · DOI：10.17615/2j6n-bk57 · 研究领域：Statistical Methods and Bayesian Inference、Survey Methodology and Nonresponse、Advanced Causal Inference Techniques

Objectives: To understand the trade-offs between different statistical modeling approaches, using real world data with small sub-populations, with rare exposures and increasingly rare outcomes. In particular, to compare adjusted regression, inverse probability weighting, and matching. Methods: Data for these analyses came from the RADAR (N=1,134) and combined CNICS/JHHCC (N=14,434) cohorts. We estimated prevalence ratios (PRs) for self-reported use of specific substances comparing subpopulations (SP), SP-1 vs SP-3 and SP-2 vs SP-3, where SP-1 was the largest proportion (92% in RADAR, 81% in CNICS/JHHCC), SP2 was moderate proportion (18% in CNICS/JHHCC) and SP-3 was the smallest proportion (8% in RADAR, 1% in CNICS/JHHCC) of the population. We calculated PRs using 1) unadjusted relative risk regression (RR); and adjusted estimates controlling for age, race/ethnicity, study site, and year of interview using: 2) standard adjustment in RR; 3) stabilized inverse probability of treatment weighting (IPTW); and 4) matching with up to 3 matches from SP-1 or SP-2 per SP-3 participant. Results: For most substances, all methods yielded consistent estimates. There were large weights in some of the IPTW analyses and in three cases these resulted in substantially divergent estimates. For the comparison between SP-1 and SP-3, the estimate for smoking was 1.3-fold greater in the matched analysis (PR=1.33, 95% CI: 1.02-1.75) than in IPTW (PR=1.03, 95% CI: 0.78-1.37 ATE and PR=1.05, 95% CI: 0.8...