Title | Reducing selection bias in analyzing longitudinal health data with high mortality rates |
Publication Type | Journal Article |
Year of Publication | 2010 |
Authors | Li, X, Engel, CC, Kang, H, Gore, KL |
Journal | Journal of Modern Applied Statistical Methods |
Volume | 9 |
Issue | 2 |
Pagination | Article 2 |
Keywords | Bias, Meta-analyses, Mortality, Older Adults |
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. |
URL | http://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1394&context=jmasm |
Citation Key | 8760 |