Basics of 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 pop...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Thousand Oaks, Calif. ; London :
Sage,
©1998.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 online resource (xvi, 311 pages) : illustrations |
| Bibliographie: | Includes bibliographical references (pages 299-305) and index. |
| ISBN: | 9781452250205 1452250200 9781483345109 1483345106 |
Internformat
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| 300 | |a 1 online resource (xvi, 311 pages) : |b illustrations | ||
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| 504 | |a Includes bibliographical references (pages 299-305) and index. | ||
| 520 | |a 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. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | 0 | |g 1. |t What Does It Mean to Model Hypothesized Causal Processes With Nonexperimental Data? -- |g 2. |t History and Logic of Structural Equation Modeling -- |g 3. |t Basics: Path Analysis and Partitioning of Variance -- |g 4. |t Effects of Collinearity on Regression and Path Analysis -- |g 5. |t Effects of Random and Nonrandom Error on Path Models -- |g 6. |t Recursive and Longitudinal Models: Where Causality Goes in More Than One Direction and Where Data Are Collected Over Time -- |g 7. |t Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling -- |g 8. |t Putting It All Together: Latent Variable Structural Equation Modeling -- |g 9. |t Using Latent Variable Structural Equation Modeling to Examine Plausibility of Models -- |g 10. |t Logic of Alternative Models and Significance Tests -- |g 11. |t Variations on the Basic Latent Variable Structural Equation Model -- |g 12. |t Wrapping Up -- |g App. A |t Brief Introduction to Matrix Algebra and Structural Equation Modeling. |
| 650 | 0 | |a Multivariate analysis. |0 http://id.loc.gov/authorities/subjects/sh85088390 | |
| 650 | 0 | |a Social sciences |x Statistical methods. |0 http://id.loc.gov/authorities/subjects/sh85124018 | |
| 650 | 6 | |a Analyse multivariée. | |
| 650 | 6 | |a Sciences sociales |x Méthodes statistiques. | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Multivariate Analysis. |2 bisacsh | |
| 650 | 7 | |a Multivariate analysis |2 fast | |
| 650 | 7 | |a Social sciences |x Statistical methods |2 fast | |
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| 650 | 1 | 7 | |a Structurele vergelijkingen. |2 gtt |
| 650 | 1 | 7 | |a Multivariate analyse. |2 gtt |
| 776 | 0 | 8 | |i Print version: |a Maruyama, Geoffrey. |t Basics of structural equation modeling. |d Thousand Oaks, Calif. ; London : Sage, ©1998 |z 0803974086 |w (DLC) 97004839 |w (OCoLC)38885110 |
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| contents | What Does It Mean to Model Hypothesized Causal Processes With Nonexperimental Data? -- History and Logic of Structural Equation Modeling -- 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 -- Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling -- 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 -- Brief Introduction to Matrix Algebra and Structural Equation Modeling. |
| ctrlnum | (OCoLC)811140594 |
| dewey-full | 519.535 |
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| dewey-raw | 519.535 |
| dewey-search | 519.535 |
| dewey-sort | 3519.535 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| illustrated | Illustrated |
| indexdate | 2024-11-27T13:24:57Z |
| institution | BVB |
| isbn | 9781452250205 1452250200 9781483345109 1483345106 |
| language | English |
| oclc_num | 811140594 |
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| spelling | Maruyama, Geoffrey. Basics of structural equation modeling / Geoffrey M. Maruyama. Thousand Oaks, Calif. ; London : Sage, ©1998. 1 online resource (xvi, 311 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references (pages 299-305) and index. 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. Print version record. 1. What Does It Mean to Model Hypothesized Causal Processes With Nonexperimental Data? -- 2. History and Logic of Structural Equation Modeling -- 3. Basics: Path Analysis and Partitioning of Variance -- 4. Effects of Collinearity on Regression and Path Analysis -- 5. Effects of Random and Nonrandom Error on Path Models -- 6. Recursive and Longitudinal Models: Where Causality Goes in More Than One Direction and Where Data Are Collected Over Time -- 7. Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling -- 8. Putting It All Together: Latent Variable Structural Equation Modeling -- 9. Using Latent Variable Structural Equation Modeling to Examine Plausibility of Models -- 10. Logic of Alternative Models and Significance Tests -- 11. Variations on the Basic Latent Variable Structural Equation Model -- 12. Wrapping Up -- App. A Brief Introduction to Matrix Algebra and Structural Equation Modeling. Multivariate analysis. http://id.loc.gov/authorities/subjects/sh85088390 Social sciences Statistical methods. http://id.loc.gov/authorities/subjects/sh85124018 Analyse multivariée. Sciences sociales Méthodes statistiques. MATHEMATICS Probability & Statistics Multivariate Analysis. bisacsh Multivariate analysis fast Social sciences Statistical methods fast Strukturgleichungsmodell gnd http://d-nb.info/gnd/4252999-2 Multivariate Analyse gnd http://d-nb.info/gnd/4040708-1 Sozialwissenschaften gnd http://d-nb.info/gnd/4055916-6 Structurele vergelijkingen. gtt Multivariate analyse. gtt Print version: Maruyama, Geoffrey. Basics of structural equation modeling. Thousand Oaks, Calif. ; London : Sage, ©1998 0803974086 (DLC) 97004839 (OCoLC)38885110 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=478015 Volltext |
| spellingShingle | Maruyama, Geoffrey Basics of structural equation modeling / What Does It Mean to Model Hypothesized Causal Processes With Nonexperimental Data? -- History and Logic of Structural Equation Modeling -- 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 -- Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling -- 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 -- Brief Introduction to Matrix Algebra and Structural Equation Modeling. Multivariate analysis. http://id.loc.gov/authorities/subjects/sh85088390 Social sciences Statistical methods. http://id.loc.gov/authorities/subjects/sh85124018 Analyse multivariée. Sciences sociales Méthodes statistiques. MATHEMATICS Probability & Statistics Multivariate Analysis. bisacsh Multivariate analysis fast Social sciences Statistical methods fast Strukturgleichungsmodell gnd http://d-nb.info/gnd/4252999-2 Multivariate Analyse gnd http://d-nb.info/gnd/4040708-1 Sozialwissenschaften gnd http://d-nb.info/gnd/4055916-6 Structurele vergelijkingen. gtt Multivariate analyse. gtt |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85088390 http://id.loc.gov/authorities/subjects/sh85124018 http://d-nb.info/gnd/4252999-2 http://d-nb.info/gnd/4040708-1 http://d-nb.info/gnd/4055916-6 |
| title | Basics of structural equation modeling / |
| title_alt | What Does It Mean to Model Hypothesized Causal Processes With Nonexperimental Data? -- History and Logic of Structural Equation Modeling -- 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 -- Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling -- 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 -- Brief Introduction to Matrix Algebra and Structural Equation Modeling. |
| title_auth | Basics of structural equation modeling / |
| title_exact_search | Basics of structural equation modeling / |
| title_full | Basics of structural equation modeling / Geoffrey M. Maruyama. |
| title_fullStr | Basics of structural equation modeling / Geoffrey M. Maruyama. |
| title_full_unstemmed | Basics of structural equation modeling / Geoffrey M. Maruyama. |
| title_short | Basics of structural equation modeling / |
| title_sort | basics of structural equation modeling |
| topic | Multivariate analysis. http://id.loc.gov/authorities/subjects/sh85088390 Social sciences Statistical methods. http://id.loc.gov/authorities/subjects/sh85124018 Analyse multivariée. Sciences sociales Méthodes statistiques. MATHEMATICS Probability & Statistics Multivariate Analysis. bisacsh Multivariate analysis fast Social sciences Statistical methods fast Strukturgleichungsmodell gnd http://d-nb.info/gnd/4252999-2 Multivariate Analyse gnd http://d-nb.info/gnd/4040708-1 Sozialwissenschaften gnd http://d-nb.info/gnd/4055916-6 Structurele vergelijkingen. gtt Multivariate analyse. gtt |
| topic_facet | Multivariate analysis. Social sciences Statistical methods. Analyse multivariée. Sciences sociales Méthodes statistiques. MATHEMATICS Probability & Statistics Multivariate Analysis. Multivariate analysis Social sciences Statistical methods Strukturgleichungsmodell Multivariate Analyse Sozialwissenschaften Structurele vergelijkingen. Multivariate analyse. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=478015 |
| work_keys_str_mv | AT maruyamageoffrey basicsofstructuralequationmodeling |