As the use of structural equation modeling (SEM) has increased, confusion has grown concerning the correct use of and the conclusions that can be legitimately drawn from these methodologies. It appears that much of the controversy surrounding SEM is related to the degree of certainty with which causal statements can be drawn from these procedures. SEM is discussed in relation to the conditions necessary for providing causal evidence. Both the weaknesses and the strengths of SEM are examined. Although structural modeling cannot ensure that necessary causal conditions have been met, it is argued that SEM methods may offer the potential for tentative causal inferences to be drawn when used with carefully specified and controlled designs. Keepi...
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complet...
tructural equation modeling (SEM) has evolved into a mature and popular methodology to investigate t...
A researcher mostly needs some statistical technique for the interpretation of the data at hand. Thi...
In their introductory marketing, management, and social psychology courses, undergraduates learn tha...
Abstract Causality was at the center of the early history of structural equation models (SEMs) which...
The role of causality in SEM research is widely perceived to be, on the one hand, of pivotal methodo...
Social scientists ’ interest in causal effects is as old as the social sciences. Attention to the ph...
My goal is to provide background and perspective on the use and interpretation of structural equatio...
With the availability of software programs, such as LISREL, EQS, and AMOS, modeling (SEM) techniques...
Structural Equation Modeling (SEM) represents a series of cause-effect relationships between variabl...
Designed for students and researchers without an extensive quantitative background, this book offers...
Structural Equation Modeling for SEM is second generation statistical analysis techniques for analyz...
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research ...
Although structural equation modeling (SEM) is a powerful statistical technique, understanding its m...
Structural Equation Model (SEM) is a multivariate statistical technique that has been explored to te...
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complet...
tructural equation modeling (SEM) has evolved into a mature and popular methodology to investigate t...
A researcher mostly needs some statistical technique for the interpretation of the data at hand. Thi...
In their introductory marketing, management, and social psychology courses, undergraduates learn tha...
Abstract Causality was at the center of the early history of structural equation models (SEMs) which...
The role of causality in SEM research is widely perceived to be, on the one hand, of pivotal methodo...
Social scientists ’ interest in causal effects is as old as the social sciences. Attention to the ph...
My goal is to provide background and perspective on the use and interpretation of structural equatio...
With the availability of software programs, such as LISREL, EQS, and AMOS, modeling (SEM) techniques...
Structural Equation Modeling (SEM) represents a series of cause-effect relationships between variabl...
Designed for students and researchers without an extensive quantitative background, this book offers...
Structural Equation Modeling for SEM is second generation statistical analysis techniques for analyz...
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research ...
Although structural equation modeling (SEM) is a powerful statistical technique, understanding its m...
Structural Equation Model (SEM) is a multivariate statistical technique that has been explored to te...
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complet...
tructural equation modeling (SEM) has evolved into a mature and popular methodology to investigate t...
A researcher mostly needs some statistical technique for the interpretation of the data at hand. Thi...