Structural equation modeling with Amos : basic concepts, applications, and programming / Barbara M. Byrne.
Material type:
TextSeries: Multivariate applications seriesPublication details: New York : New York Routledge, c2016.Edition: Third editionDescription: xx, 437 pages : illustrations ; 24 cmISBN: - 9781138797024 (hbk. : alk. paper)
- 1138797022 (hbk. : alk. paper)
- 9781138797031 (pbk. : alk. paper)
- 1138797030 (pbk. : alk. paper)
- 519.535 23 BYS 2016
| Item type | Current library | Call number | Status | Barcode | |
|---|---|---|---|---|---|
Books
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Bangladesh Public Administration Training Centre Library General Stacks | 519.535 BYS 2016 | Available | 111698 |
Includes bibliographical references (page 407-427) and indexes.
Section I. Introduction. Structural equation modeling: the basics --
Using the Amos program --
Section II. Single-group analysis. Confirmatory factor analytic models. Application 1: Testing the factorial validity of a theoretical construct (first-order CFA model) --
Application 2: Testing the factorial validity of scores from a measurement scale (first-order CFA model) --
Application 3: Testing the factorial validity of scores from a measurement scale (second-order CFA model) --
Full latent variable model. Application 4: Testing the validity of a causal structure --
Section III. Multiple-group analysis. Confirmatory factor analytic models. Application 5: Testing factorial invariance of scales from a measurement scale (first-order CFA model) --
Application 6: Testing invariance of latent mean structures (first-order CFA model) --
Full latent variable model --
Application 7: Testing invariance of a causal structure (full structural equation model) --
Section IV. Other important applications. Application 8: Testing evidence of construct validity: the multitrait-multimethod model --
Application 9: Testing change over time: the latent growth curve model --
Section V. Other important topics. Application 10: Use of bootstrapping in addressing nonnormal data --
Application 11: Addressing the issues of missing data.
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