Evaluation studies aim to provide answers to important questions like: How does this program or policy intervention affect the outcome variables of interest? In order to answer such questions, using the traditional statistical evaluation (or causal inference) methods, some conditions must be...

Evaluation studies aim to provide answers to important questions like: How does this program or policy intervention affect the outcome variables of interest? In order to answer such questions, using the traditional statistical evaluation (or causal inference) methods, some conditions must be...

Causal effects are usually estimated under the assumption of no interference between individuals. This assumption means that the potential outcomes for one individual are unaffected by the treatments received by other individuals. In many situations, this is not reasonable to assume. Moreover,...

Abstract When estimating population attributable fractions (PAF), it is common to partition a naturally continuous exposure into a categorical risk factor. While prior risk factor categorization can help estimation and interpretation, it can result in underestimation of the disease burden...

Abstract A result from a standard linear model course is that the variance of the ordinary least squares (OLS) coefficient of a variable will never decrease when including additional covariates into the regression. The variance inflation factor (VIF) measures the increase of the variance....