The Performance of Two Data-Generation Processes for Data with Specified Marginal Treatment Odds Ratios

Autor:	Peter C. Austin, James E. Stafford
Rok vydání:	2008
Předmět:	Statistics and Probability Test data generation Average treatment effect Modeling and Simulation Statistics Econometrics Probability distribution Estimator Regression analysis Conditional probability distribution Marginal distribution Mathematics Odds
Zdroj:	Communications in Statistics - Simulation and Computation. 37:1039-1051
ISSN:	1532-4141 0361-0918
DOI:	10.1080/03610910801942430
Popis:	Monte Carlo simulation methods are increasingly being used to evaluate the property of statistical estimators in a variety of settings. The utility of these methods depends upon the existence of an appropriate data-generating process. Observational studies are increasingly being used to estimate the effects of exposures and interventions on outcomes. Conventional regression models allow for the estimation of conditional or adjusted estimates of treatment effects. There is an increasing interest in statistical methods for estimating marginal or average treatment effects. However, in many settings, conditional treatment effects can differ from marginal treatment effects. Therefore, existing data-generating processes for conditional treatment effects are of little use in assessing the performance of methods for estimating marginal treatment effects. In the current study, we describe and evaluate the performance of two different data-generation processes for generating data with a specified marginal odds rati...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::db8b1dfd6459f66eb3c6d6f5813c0420 https://doi.org/10.1080/03610910801942430 Zobrazit plný text záznamu