Mixed-Effect Hybrid Models for Longitudinal Data with Nonignorable Dropout
نویسندگان
چکیده
منابع مشابه
Mixed-effect hybrid models for longitudinal data with nonignorable dropout.
SUMMARY Selection models and pattern-mixture models are often used to deal with nonignorable dropout in longitudinal studies. These two classes of models are based on different factorizations of the joint distribution of the outcome process and the dropout process. We consider a new class of models, called mixed-effect hybrid models (MEHMs), where the joint distribution of the outcome process a...
متن کاملMixtures of varying coefficient models for longitudinal data with discrete or continuous nonignorable dropout.
The analysis of longitudinal repeated measures data is frequently complicated by missing data due to informative dropout. We describe a mixture model for joint distribution for longitudinal repeated measures, where the dropout distribution may be continuous and the dependence between response and dropout is semiparametric. Specifically, we assume that responses follow a varying coefficient rand...
متن کاملTransition Models for Analyzing Longitudinal Data with Bivariate Mixed Ordinal and Nominal Responses
In many longitudinal studies, nominal and ordinal mixed bivariate responses are measured. In these studies, the aim is to investigate the effects of explanatory variables on these time-related responses. A regression analysis for these types of data must allow for the correlation among responses during the time. To analyze such ordinal-nominal responses, using a proposed weighting approach, an ...
متن کاملA Comparative Review of Selection Models in Longitudinal Continuous Response Data with Dropout
Missing values occur in studies of various disciplines such as social sciences, medicine, and economics. The missing mechanism in these studies should be investigated more carefully. In this article, some models, proposed in the literature on longitudinal data with dropout are reviewed and compared. In an applied example it is shown that the selection model of Hausman and Wise (1979, Econometri...
متن کاملParametric fractional imputation for mixed models with nonignorable missing data
Inference in the presence of non-ignorable missing data is a widely encountered and difficult problem in statistics. Imputation is often used to facilitate parameter estimation, which allows one to use the complete sample estimators on the imputed data set. We develop a parametric fractional imputation (PFI) method proposed by Kim (2011), which simplifies the computation associated with the EM ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biometrics
سال: 2008
ISSN: 0006-341X
DOI: 10.1111/j.1541-0420.2008.01102.x