Article Title
Reducing Selection Bias in Analyzing Longitudinal Health Data with High Mortality Rates
Abstract
Two longitudinal regression models, one parametric and one nonparametric, are developed to reduce selection bias when analyzing longitudinal health data with high mortality rates. The parametric mixed model is a two-step linear regression approach, whereas the nonparametric mixed-effects regression model uses a retransformation method to handle random errors across time.
DOI
10.22237/jmasm/1288584480
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
