I am analyzing a set of clinical data where I try to predict an outcome by using certain covariates. I have already done univariate analysis and now am progressing to binary logistic regression, incorporating the covariates that have a p < 0.1 in univariate tests to the model. In doing binary logisitic regression, which method is better enter or one of the forward or backward elimination methods?
If I use the enter method, should I manually include and exclude different covariates until all covariates with a final significant contribution to outcome are included in the model?
Which ever the method used, what are the factors/statistical measures to consider in selecting the best method?