方法证据记录
Matched Survival Analysis
Matched survival analysis combines a matching design — typically propensity score matching or exact matching on key covariates — with time-to-event methods such as Kaplan-Meier estimation and the Cox proportional hazards model. By pairing treated and control subjects who are similar on observed confounders before estimating survival curves or hazard ratios, the approach reduces confounding bias in non-randomised studies and produces more credible comparisons of event-free survival between exposure groups.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Matched Cohort Survival Analysis
分类方法记录 · process-pipeline / epidemiology
- Austin, P. C. (2014). Graphical assessments of the balance of propensity score matched samples: A SAS macro. Journal of Statistical Software, 58(7), 1-29. Also see Austin, P. C. (2017). A tutorial on multilevel survival analysis: Methods, models and applications. International Statistical Review, 85(2), 185-203. · URL
- Collett, D. (2015). Modelling Survival Data in Medical Research (3rd ed.). CRC Press. · ISBN 9781439856789
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