… covariate adjustment in simulated logistic regression models with one dichotomous covariate…
Our aim was to identify the pros and the cons of each covariate adjustment strategy, with a …

… Dichotomous Outcomes—James Lee et al suitable for adjusting for 1 or at most 2 confounding
covariates … Moreover, a continuous covariate (age, blood pressure) must be grouped into …

… β is coefficient of the covariate effect, U is random dichotomous value of treatment with 50%
prevalence for treatment A on average, and V is random dichotomous value of covariate at a …

… ; each of these covariates was controlled for in the adjusted analyses. … For our dichotomous
outcome, we attempted to use … and without covariates. In almost all cases, the models without …

… ) adjusting for continuous covariates even if their association with outcome is unknown; (2)
keeping covariates … we assume that the covariate does influence outcome. It should be noted …

… of Covariance) methods as they relate to dichotomous outcomes in this paper, the primary
outcome for this analysis was the Yes/No outcome of whether a patient progressed by 12 …

… the baseline variable in the adjustment model for optimal adjustment. To consider a …
adjustment model. R 2 statistics were calculated to indicate the explained variance of the adjustment …

… and cluster level covariates that must be … adjustment to the standard error of the regression
parameter estimate from the ordinary logistic regression approach, we do get an adjusted …

… in randomized controlled trials with dichotomous outcomes increases statistical power
and reduces sample size requirements. Journal of Clinical Epidemiology 2004; 57(5):454–460. …

… across units, we must usually consider the third type of variable, the covariates, X i . A key …
any adjustments beyond grouping observations that are similar in terms of the covariate. Rubin …