A Novel Stratified Analysis Method for Testing and Estimating Overall Treatment Effects on Time-to-Event Outcomes Using Average Hazard with Survival Weight
Zihan Qian, Lu Tian, Miki Horiguchi, Hajime Uno

TL;DR
This paper introduces a new stratified analysis method for estimating treatment effects on time-to-event outcomes using average hazard with survival weight, addressing limitations of traditional methods and allowing for effect size reporting.
Contribution
It proposes a novel stratified analysis approach based on standardization for the average hazard, improving adjustment for stratification factors in time-to-event data.
Findings
The method effectively adjusts for stratification factors.
It provides both absolute and relative treatment effect estimates.
It offers an alternative to the stratified Cox model.
Abstract
Given the limitations of using the Cox hazard ratio to summarize the magnitude of the treatment effect, alternative measures that do not have these limitations are gaining attention. One of the recently proposed alternative methods uses the average hazard with survival weight (AH). This population quantity can be interpreted as the average intensity of the event occurrence in a given time window that does not involve study-specific censoring. Inference procedures for the ratio of AH and difference in AH have already been proposed in simple randomized controlled trial settings to compare two groups. However, methods with stratification factors have not been well discussed, although stratified analysis is often used in practice to adjust for confounding factors and increase the power to detect a between-group difference. The conventional stratified analysis or meta-analysis approach,…
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Taxonomy
TopicsStatistical Methods in Clinical Trials
