VARIANCE COMPONENT TESTING IN GENERALIZED LINEAR MIXED MODELS
نویسندگان
چکیده
منابع مشابه
Variance Component Testing in Generalized Linear Mixed Models
Generalized linear mixed models (GLMM) are used in situations where a number of characteristics (covariates) affect a nonnormal response variable and the responses are correlated. For example, in a number of biological applications, the responses are correlated due to common genetic or environmental factors. In many applications, the magnitude of the variance components corresponding to one or ...
متن کاملSIMEX variance component tests in generalized linear mixed measurement error models.
In the analysis of clustered data with covariates measured with error, a problem of common interest is to test for correlation within clusters and heterogeneity across clusters. We examined this problem in the framework of generalized linear mixed measurement error models. We propose using the simulation extrapolation (SIMEX) method to construct a score test for the null hypothesis that all var...
متن کاملTesting multiple variance components in linear mixed-effects models.
Testing zero variance components is one of the most challenging problems in the context of linear mixed-effects (LME) models. The usual asymptotic chi-square distribution of the likelihood ratio and score statistics under this null hypothesis is incorrect because the null is on the boundary of the parameter space. During the last two decades many tests have been proposed to overcome this diffic...
متن کاملBayesian and Generalized Confidence Intervals on Variance Ratio and on the Variance Component in Mixed Linear Models
The paper deals with construction of exact confidence intervals for the variance component σ 1 and ratio θ of variance components σ 1 and σ in mixed linear models for the family of normal distributions Nt (0, σ 2 1 W + σ2It). This problem essentially depends on algebraic structure of the covariance matrix W (see Gnot and Michalski, 1994, Michalski and Zmyślony, 1996). In the paper we give two c...
متن کاملTesting for misspecification in generalized linear mixed models.
Generalized linear mixed models have become a frequently used tool for the analysis of non-Gaussian longitudinal data. Estimation is often based on maximum likelihood theory, which assumes that the underlying probability model is correctly specified. Recent research shows that the results obtained from these models are not always robust against departures from the assumptions on which they are ...
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: ETS Research Report Series
سال: 2003
ISSN: 2330-8516
DOI: 10.1002/j.2333-8504.2003.tb01906.x