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Multiple regression and beyond : an introduction to multiple regression and structural equation modeling / Timothy Z. Keith.

By: Material type: TextTextPublisher: New York : Routledge, 2019Edition: Third EditionDescription: pages cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781138061422 (hardback)
  • 9781138061446 (pbk.)
Subject(s): DDC classification:
  • 519.536 23 KEI/M
LOC classification:
  • HA31.3 .K45 2019
Contents:
Multiple regression -- Simple bivariate regression -- Multiple regression : introduction -- Multiple regression : more detail -- Three and more independent variables and related issues -- Three types of multiple regression -- Analysis of categorical variables -- Regression with categorical and continuous variables -- Testing for interactions and curves with continuous variables -- Mediation, moderation, and common cause -- Multiple regression: summary, assumptions, diagnostics, power, and problems -- Related methods : logistic regression and multilevel modeling -- Beyond multiple regression : structural equation modeling -- Path modeling : structural equation modeling with measured variables -- Path analysis : assumptions and dangers -- Analyzing path models using sem programs -- Error: the scourge of research -- Confirmatory factor analysis I: -- Putting it all together: introduction to latent variable sem -- Latent variable models II: multigroup models, panel models, dangers & assumptions -- Latent means in SEM -- Confirmatory factor analysis II: invariance and latent means -- Latent growth models -- Latent variable interactions and multilevel models in SEM -- Summary: path analysis, cfa, sem, mean structures, and latent growth models -- Appendices.
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Holdings
Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Education New Materials Shelf Dept. of Education 519.536 KEI/M (Browse shelf(Opens below)) Available EDU19138

Revised edition of the author's Multiple regression and beyond, 2015.

Multiple regression -- Simple bivariate regression -- Multiple regression : introduction -- Multiple regression : more detail -- Three and more independent variables and related issues -- Three types of multiple regression -- Analysis of categorical variables -- Regression with categorical and continuous variables -- Testing for interactions and curves with continuous variables -- Mediation, moderation, and common cause -- Multiple regression: summary, assumptions, diagnostics, power, and problems -- Related methods : logistic regression and multilevel modeling -- Beyond multiple regression : structural equation modeling -- Path modeling : structural equation modeling with measured variables -- Path analysis : assumptions and dangers -- Analyzing path models using sem programs -- Error: the scourge of research -- Confirmatory factor analysis I: -- Putting it all together: introduction to latent variable sem -- Latent variable models II: multigroup models, panel models, dangers & assumptions -- Latent means in SEM -- Confirmatory factor analysis II: invariance and latent means -- Latent growth models -- Latent variable interactions and multilevel models in SEM -- Summary: path analysis, cfa, sem, mean structures, and latent growth models -- Appendices.

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