For the analysis of a dichotomous outcome variable cross-tables can be used for the comparison of two groups and the comparison of more than two groups. Based on the cross-table different effect estimates can be derived. Relative risk and risk difference can only be used when the study is prospective, while the odds ratio can be used in all study designs. For statistical testing of these effect estimates, the Fisher exact test or chi-square test can be used. For all these situations, also a regression method is available, i.e. logistic regression analysis. Logistic regression analysis is comparable to linear regression analysis in a way that the regression coefficients have the same interpretation, only the outcome variable is different. In a logistic regression analysis, the outcome variable is the natural log of the odds of having the dichotomous outcome variable. Because of that the regression coefficient for an independent variable can be transformed into an odds ratio. In this chapter, furthermore, the evaluation of linearity of the relationship with a continuous independent variable, the adjustment for confounding and the investigation of effect modification are discussed. The way this is done in logistic regression analysis is exactly the same as in linear regression analysis.