03587nam 22005291 450 991079172850332120170308170817.81-5063-2035-X1-4833-4510-61-4522-5020-0(CKB)2560000000089869(EBL)997200(OCoLC)809774252(MiAaPQ)EBC997200(OCoLC)811140594(CaToSAGE)SAGE000001280(StDuBDS)EDZ0000159001(PPN)198710445(EXLCZ)99256000000008986920170308d1998 fy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierBasics of structural equation modeling /Geoffrey M. MaruyamaLos Angeles, CA :SAGE Publications, Inc.,1998.1 online resource (311 pages) illustrationsDescription based upon print version of record.1-322-30717-2 0-8039-7409-4 Includes bibliographical references (p. 299-305) and indexes.Background. What does it mean to model hypothesized causal processes with nonexperimental data? -- History and logic of structural equation modeling -- Basic approaches to modeling with single observed measures of theoretical variables. The basics: path analysis and partitioning of variance -- Effects of collinearity on regression and path analysis -- Effects of random and nonrandom error on path models -- Recursive and longitudinal models: where causality goes in more than one direction and where data are collected over time -- Factor analysis and path modeling. Introducing the logic of factor analysis and multiple indicators to path modeling -- Latent variable structural equation models. Putting it all together: latent variable structural equation modeling -- Using latent variable structural equation modeling to examine plausibility of models -- Logic of alternative models and significance tests -- Variations on the basic latent variable structural equation model -- Wrapping up -- Appendix A: A brief introduction to matrix algebra and structural equation modeling.With the availability of software programs such as LISREL, EQS, and AMOS modeling techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. The popularity of these techniques, however, has often led to misunderstandings of them, particularly by students being exposed to them for the first time. Through the use of careful narrative explanation, Basics of Structural Equation Modeling describes the logic underlying structural equation modeling (SEM) approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores the various methodologies for analyzing structural equation data.Structural equation modelingStructural equation modelingComputer programsStructural equation modeling.Structural equation modelingComputer programs.519.535Maruyama Geoffrey M.496041CaToSAGECaToSAGEUtOrBLWBOOK9910791728503321Basics of structural equation modeling748778UNINA