Using ODA in the Evaluation of Randomized Controlled Trials: Application to Survival Outcomes

Ariel Linden & Paul R. Yarnold

Linden Consulting Group, LLC & Optimal Data Analysis, LLC

In a recent series of papers, ODA has been applied to observational data to draw causal inferences about treatment effects. Presently, ODA is applied to survival outcomes from a randomized controlled trial, with a reanalysis of a study by Linden and Butterworth [2014] that investigated (as a secondary outcome) the effect of a comprehensive hospital-based intervention in reducing mortality at 90 days for chronically ill patients. In the original analysis, differences in mortality rates between treatment and control groups were estimated using logistic regression and calculated as both risk differences and risk ratios, and a treatment effect was found in the subgroup of patients with chronic obstructive pulmonary disease (COPD), but not in the other subgroup of patients with congestive heart failure (CHF). In the present study, we reanalyze these results using both Cox regression, and weighted ODA, wherein the weight of every subject is their follow-up time (i.e., number of days of follow-up).

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