Over the last twenty years there have been numerous developments in diagnostic pro- cedures for hierarchical linear models; however, these procedures are not widely imple- mented in statistical software packages, and those packages that do contain a complete framework for model assessment are not open source. The lack of availability of diagnostic procedures for hierarchical linear models has limited their adoption in statistical practice. The R package HLMdiag provides diagnostic tools targeting all aspects and levels of continuous response hierarchical linear models with strictly nested dependence structures fit using the lmer() function in the lme4 package. In this paper we discuss the tools implemented in HLMdiag for both residual and i...
Abstract Previous publications on hierarchical linear modeling (HLM) have provided guidance on how ...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
Over the last twenty years there have been numerous developments in diagnostic pro- cedures for hier...
In social research work, the structure of the data are often hierarchical. Hierarchical linear model...
The R package HGLMMM has been developed to fit generalized linear models with random effects using t...
In this dissertation, I develop a multilevel approach to diagnosing and assessing t in mixed linea...
TEZ8987Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2013.Kaynakça (s. 119-124) var.xiii, 157...
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There...
A general approach for conducting power analysis in two- and three-level hierarchical linear models ...
The R package HGLMMM has been developed to fit generalized linear models with random effects using t...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
In the analysis of clustered or hierarchical data, a variety of statistical techniques can be applie...
The hierarchical linear model (HLM) is the primary tool of multilevel analysis, a set of techniques ...
Description A suite of diagnostic tools for hierarchical (multilevel) linear models. The tools inclu...
Abstract Previous publications on hierarchical linear modeling (HLM) have provided guidance on how ...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
Over the last twenty years there have been numerous developments in diagnostic pro- cedures for hier...
In social research work, the structure of the data are often hierarchical. Hierarchical linear model...
The R package HGLMMM has been developed to fit generalized linear models with random effects using t...
In this dissertation, I develop a multilevel approach to diagnosing and assessing t in mixed linea...
TEZ8987Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2013.Kaynakça (s. 119-124) var.xiii, 157...
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There...
A general approach for conducting power analysis in two- and three-level hierarchical linear models ...
The R package HGLMMM has been developed to fit generalized linear models with random effects using t...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
In the analysis of clustered or hierarchical data, a variety of statistical techniques can be applie...
The hierarchical linear model (HLM) is the primary tool of multilevel analysis, a set of techniques ...
Description A suite of diagnostic tools for hierarchical (multilevel) linear models. The tools inclu...
Abstract Previous publications on hierarchical linear modeling (HLM) have provided guidance on how ...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...