Zobrazeno 1 - 10
of 25 386
pro vyhledávání: '"covariate adjustment"'
The area under the curve (AUC) of the mean cumulative function (MCF) has recently been introduced as a novel estimand for evaluating treatment effects in recurrent event settings, capturing a totality of evidence in relation to disease progression. W
Externí odkaz:
http://arxiv.org/abs/2410.24163
Higher-Order Influence Functions (HOIF), developed in a series of papers over the past twenty years, is a fundamental theoretical device for constructing rate-optimal causal-effect estimators from observational studies. However, the value of HOIF for
Externí odkaz:
http://arxiv.org/abs/2411.08491
Autor:
Fava, Bruno
Important questions for impact evaluation require knowledge not only of average effects, but of the distribution of treatment effects. What proportion of people are harmed? Does a policy help many by a little? Or a few by a lot? The inability to obse
Externí odkaz:
http://arxiv.org/abs/2407.14635
Autor:
Cytrynbaum, Max1 (AUTHOR) max.cytrynbaum@yale.edu
Publikováno v:
Quantitative Economics. Nov2024, Vol. 15 Issue 4, p971-998. 28p.
Autor:
Hesterberg, Tim, Knight, Ben
We describe how to calculate standard errors for A/B tests that include clustered data, ratio metrics, and/or covariate adjustment. We may do this for power analysis/sample size calculations prior to running an experiment using historical data, or af
Externí odkaz:
http://arxiv.org/abs/2406.06834
In May 2023, the U.S. Food and Drug Administration (FDA) released guidance for industry on "Adjustment for Covariates in Randomized Clinical Trials for Drugs and Biological Products". Covariate adjustment is a statistical analysis method for improvin
Externí odkaz:
http://arxiv.org/abs/2404.11150
Autor:
Wang, Bingkai, Li, Fan
Rerandomization is an effective treatment allocation procedure to control for baseline covariate imbalance. For estimating the average treatment effect, rerandomization has been previously shown to improve the precision of the unadjusted and the line
Externí odkaz:
http://arxiv.org/abs/2406.02834
Autor:
Baird, Grayson L., Bieber, Stephen L.
It is often asserted that to control for the effects of confounders, one should include the confounding variables of concern in a statistical model as a covariate. Conversely, it is also asserted that control can only be concluded by design, where th
Externí odkaz:
http://arxiv.org/abs/2405.17224
A Connection Between Covariate Adjustment and Stratified Randomization in Randomized Clinical Trials
Autor:
Zhang, Zhiwei
The statistical efficiency of randomized clinical trials can be improved by incorporating information from baseline covariates (i.e., pre-treatment patient characteristics). This can be done in the design stage using stratified (permutated block) ran
Externí odkaz:
http://arxiv.org/abs/2401.11352
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