In the analysis of clustered or hierarchical data, a variety of statistical techniques can be applied. Most of these techniques have assumptions that are crucial to the validity of their outcome. Mixed models rely on the correct specification of the random effects structure. Generalized estimating equations are most efficient when the working correlation form is chosen correctly and are not feasible when the within-subject variable is non-factorial. Assumptions and limitations of another common approach, ANOVA for repeated measurements, are even more worrisome: listwise deletion when data are missing, the sphericity assumption, inability to model an unevenly spaced time variable and time-varying covariates, and the limitation to normally di...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The analysis of change within subjects over time is an ever more important research topic. Besides m...
Various bootstraps have been proposed for bootstrapping clustered data from one-way arrays. The simu...
This paper describes the core features of the R package geepack, which implements the generalized es...
This paper describes the core features of the R package geepack, which implements the generalized es...
This paper describes the core features of the R package geepack, which implements the generalized es...
Nested data structure obtained from a cluster sampling design often calls for hierarchical linear mo...
Over the last twenty years there have been numerous developments in diagnostic pro- cedures for hier...
In this paper, we demonstrate the importance of conducting well-thought-out sensitivity analyses for...
One of the innovative approaches in the use of hierarchical linear models (HLM) is to use HLM for Sl...
Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the general...
We apply the generalized cluster bootstrap to both Gaussian quasi-likelihood and robust estimates in...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The analysis of change within subjects over time is an ever more important research topic. Besides m...
Various bootstraps have been proposed for bootstrapping clustered data from one-way arrays. The simu...
This paper describes the core features of the R package geepack, which implements the generalized es...
This paper describes the core features of the R package geepack, which implements the generalized es...
This paper describes the core features of the R package geepack, which implements the generalized es...
Nested data structure obtained from a cluster sampling design often calls for hierarchical linear mo...
Over the last twenty years there have been numerous developments in diagnostic pro- cedures for hier...
In this paper, we demonstrate the importance of conducting well-thought-out sensitivity analyses for...
One of the innovative approaches in the use of hierarchical linear models (HLM) is to use HLM for Sl...
Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the general...
We apply the generalized cluster bootstrap to both Gaussian quasi-likelihood and robust estimates in...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The goal of this paper is to broaden general knowledge on nested data analysis, its problems of depe...
The analysis of change within subjects over time is an ever more important research topic. Besides m...
Various bootstraps have been proposed for bootstrapping clustered data from one-way arrays. The simu...