Structural equation models are routinely applied to data collected from complex samples. Methods to take account of the sample design and weights are discussed in a growing literature on the topic. This paper provides a literature review of the analysis of complex samples using structural equation models. The goal of the paper is to extract the points of agreement and disagreement from these publications; to assess and evaluate those areas of consensus; and to propose the research areas most in need of further research
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex...
Individuals may differ in their parameter values. This article discusses a three-step method of stud...
In scientic research, data acquired in time-series and cross-sectional form or from experiments with...
Survey data in social, behavioral, and health sciences often contain many variables (p). Structural ...
In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vig...
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex...
A researcher mostly needs some statistical technique for the interpretation of the data at hand. Thi...
ABSTRACT. Complex survey designs often employ multistage cluster sampling designs and oversample par...
The primary objective of this book is to study some of the research topics in the area of analysis o...
The fact that survey data are obtained from units selected with complex sample designs needs to be t...
Structural Equation Model (SEM) is a multivariate statistical technique that has been explored to te...
The purpose of this study was to evaluate the performance of estimation methods (Maximum Likelihood,...
As a theory-guided approach, SEM can estimate directional pathways in complex models using longitudi...
Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applicatio...
In the present chapter, we consider the effects of complex sample design used in practice in most sa...
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex...
Individuals may differ in their parameter values. This article discusses a three-step method of stud...
In scientic research, data acquired in time-series and cross-sectional form or from experiments with...
Survey data in social, behavioral, and health sciences often contain many variables (p). Structural ...
In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vig...
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex...
A researcher mostly needs some statistical technique for the interpretation of the data at hand. Thi...
ABSTRACT. Complex survey designs often employ multistage cluster sampling designs and oversample par...
The primary objective of this book is to study some of the research topics in the area of analysis o...
The fact that survey data are obtained from units selected with complex sample designs needs to be t...
Structural Equation Model (SEM) is a multivariate statistical technique that has been explored to te...
The purpose of this study was to evaluate the performance of estimation methods (Maximum Likelihood,...
As a theory-guided approach, SEM can estimate directional pathways in complex models using longitudi...
Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applicatio...
In the present chapter, we consider the effects of complex sample design used in practice in most sa...
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex...
Individuals may differ in their parameter values. This article discusses a three-step method of stud...
In scientic research, data acquired in time-series and cross-sectional form or from experiments with...