Current Topics in the Theory and Application of Latent Variable Models
Herausgeber: Edwards, Michael C; MacCallum, Robert C
Current Topics in the Theory and Application of Latent Variable Models
Herausgeber: Edwards, Michael C; MacCallum, Robert C
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First Published in 2013. Routledge is an imprint of Taylor & Francis, an informa company.
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First Published in 2013. Routledge is an imprint of Taylor & Francis, an informa company.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 272
- Erscheinungstermin: 6. Dezember 2012
- Englisch
- Abmessung: 228mm x 151mm x 22mm
- Gewicht: 405g
- ISBN-13: 9780415637787
- ISBN-10: 0415637783
- Artikelnr.: 36646588
- Verlag: Taylor & Francis
- Seitenzahl: 272
- Erscheinungstermin: 6. Dezember 2012
- Englisch
- Abmessung: 228mm x 151mm x 22mm
- Gewicht: 405g
- ISBN-13: 9780415637787
- ISBN-10: 0415637783
- Artikelnr.: 36646588
Michael C. Edwards is an Associate Professor in the Quantitative Area of the Department of Psychology at The Ohio State University. He received his PhD in 2005 from the L.L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. His research focuses on measurement issues in the social sciences with specific topics including multidimensional item response theory, computerized adaptive testing, local dependence, and measurement invariance. Robert C. MacCallum is Professor Emeritus of Psychology at both the University of North Carolina at Chapel Hill and Ohio State University. He received his graduate training at the University of Illinois and then spent 28 years on the faculty in the Quantitative Psychology program at Ohio State University, moving to UNC in 2003. His research interests focus on methods for analysis and modeling of correlational and longitudinal data, including factor analysis, structural equation modeling, and latent curve models. Within these areas he has worked on various issues including model estimation and evaluation, power analysis for testing models, and the nature and management of sources of error in modeling. His current interests involve the study of uncertainty inherent in results of statistical models. He is former Director of the L. L. Thurstone Psychometric Laboratory at UNC, and former president of the Society for Multivariate Experimental Psychology. In 2011 he received the Samuel J. Messick Award for distinguished scientific contributions from Division 5 of the American Psychological Association.
M. C. Edwards
R. C. MacCallum
Introduction: Complexity and Meaning in Latent Variable Modeling. Part I. Complexities in Latent Variable Modeling. R. Cudeck
J. R. Harring
Estimating the Correlation between Two Variables when Individuals are Measured Repeatedly. R. Gonzalez
D. Griffin
Deriving Estimators and Their Standard Errors in Dyadic Data Analysis: Examples Using a Symbolic Computation Program. P. F. Craigmile
M. Peruggia
T. Van Zandt
A Bayesian Hierarchical Model for Response Time Data Providing Evidence for Criteria Changes Over Time. I. Moustaki
A Review of Estimation Methods for Latent Variable Models. G. Zhang
C.T. Lee
Standard Errors for Ordinary Least Squares Estimates of Parameters in Structural Equation Modeling. L. Cai
Three Cheers for the Asymptotically Distribution Free Theory of Estimation and Inference: Some Recent Applications in Linear and Nonlinear Latent Variable Modeling. K. A. Duncan
S. N. MacEachern
Nonparametric Bayesian Modeling of Item Response Curves with a Three Parameter Logistic Prior Mean. W. A. Nicewander
Exact Solutions for IRT Latent Regression Slopes and Latent Variable Intercorrelations. S. du Toit
Analysis of Structural Equation Models Based on a Mixture of Continuous and Ordinal Random Variables in the Case of Complex Survey Data. Part II. Drawing Meaning from Latent Variable Models. R. E. Millsap
A Simulation Paradigm for Evaluating Approximate Fit. R. C. MacCallum
T. Lee
M. W. Browne
Fungible Parameter Values in Latent Curve Models. A. Shapiro
Statistical Inference of Moment/Covariance Structures. J. L. Rodgers
W. H. Beasley
Fisher
Gosset
and Alternative Hypothesis Significance Testing (AHST): Using the Bootstrap to Test Scientific Hypotheses about the Multiple Correlation. S. M. Boker
M. Martin
On The Equilibrium Dynamics of Meaning. K. Tateneni
M. Schiller
Applying Components Analysis to Attitudinal Segmentation.
R. C. MacCallum
Introduction: Complexity and Meaning in Latent Variable Modeling. Part I. Complexities in Latent Variable Modeling. R. Cudeck
J. R. Harring
Estimating the Correlation between Two Variables when Individuals are Measured Repeatedly. R. Gonzalez
D. Griffin
Deriving Estimators and Their Standard Errors in Dyadic Data Analysis: Examples Using a Symbolic Computation Program. P. F. Craigmile
M. Peruggia
T. Van Zandt
A Bayesian Hierarchical Model for Response Time Data Providing Evidence for Criteria Changes Over Time. I. Moustaki
A Review of Estimation Methods for Latent Variable Models. G. Zhang
C.T. Lee
Standard Errors for Ordinary Least Squares Estimates of Parameters in Structural Equation Modeling. L. Cai
Three Cheers for the Asymptotically Distribution Free Theory of Estimation and Inference: Some Recent Applications in Linear and Nonlinear Latent Variable Modeling. K. A. Duncan
S. N. MacEachern
Nonparametric Bayesian Modeling of Item Response Curves with a Three Parameter Logistic Prior Mean. W. A. Nicewander
Exact Solutions for IRT Latent Regression Slopes and Latent Variable Intercorrelations. S. du Toit
Analysis of Structural Equation Models Based on a Mixture of Continuous and Ordinal Random Variables in the Case of Complex Survey Data. Part II. Drawing Meaning from Latent Variable Models. R. E. Millsap
A Simulation Paradigm for Evaluating Approximate Fit. R. C. MacCallum
T. Lee
M. W. Browne
Fungible Parameter Values in Latent Curve Models. A. Shapiro
Statistical Inference of Moment/Covariance Structures. J. L. Rodgers
W. H. Beasley
Fisher
Gosset
and Alternative Hypothesis Significance Testing (AHST): Using the Bootstrap to Test Scientific Hypotheses about the Multiple Correlation. S. M. Boker
M. Martin
On The Equilibrium Dynamics of Meaning. K. Tateneni
M. Schiller
Applying Components Analysis to Attitudinal Segmentation.
M. C. Edwards
R. C. MacCallum
Introduction: Complexity and Meaning in Latent Variable Modeling. Part I. Complexities in Latent Variable Modeling. R. Cudeck
J. R. Harring
Estimating the Correlation between Two Variables when Individuals are Measured Repeatedly. R. Gonzalez
D. Griffin
Deriving Estimators and Their Standard Errors in Dyadic Data Analysis: Examples Using a Symbolic Computation Program. P. F. Craigmile
M. Peruggia
T. Van Zandt
A Bayesian Hierarchical Model for Response Time Data Providing Evidence for Criteria Changes Over Time. I. Moustaki
A Review of Estimation Methods for Latent Variable Models. G. Zhang
C.T. Lee
Standard Errors for Ordinary Least Squares Estimates of Parameters in Structural Equation Modeling. L. Cai
Three Cheers for the Asymptotically Distribution Free Theory of Estimation and Inference: Some Recent Applications in Linear and Nonlinear Latent Variable Modeling. K. A. Duncan
S. N. MacEachern
Nonparametric Bayesian Modeling of Item Response Curves with a Three Parameter Logistic Prior Mean. W. A. Nicewander
Exact Solutions for IRT Latent Regression Slopes and Latent Variable Intercorrelations. S. du Toit
Analysis of Structural Equation Models Based on a Mixture of Continuous and Ordinal Random Variables in the Case of Complex Survey Data. Part II. Drawing Meaning from Latent Variable Models. R. E. Millsap
A Simulation Paradigm for Evaluating Approximate Fit. R. C. MacCallum
T. Lee
M. W. Browne
Fungible Parameter Values in Latent Curve Models. A. Shapiro
Statistical Inference of Moment/Covariance Structures. J. L. Rodgers
W. H. Beasley
Fisher
Gosset
and Alternative Hypothesis Significance Testing (AHST): Using the Bootstrap to Test Scientific Hypotheses about the Multiple Correlation. S. M. Boker
M. Martin
On The Equilibrium Dynamics of Meaning. K. Tateneni
M. Schiller
Applying Components Analysis to Attitudinal Segmentation.
R. C. MacCallum
Introduction: Complexity and Meaning in Latent Variable Modeling. Part I. Complexities in Latent Variable Modeling. R. Cudeck
J. R. Harring
Estimating the Correlation between Two Variables when Individuals are Measured Repeatedly. R. Gonzalez
D. Griffin
Deriving Estimators and Their Standard Errors in Dyadic Data Analysis: Examples Using a Symbolic Computation Program. P. F. Craigmile
M. Peruggia
T. Van Zandt
A Bayesian Hierarchical Model for Response Time Data Providing Evidence for Criteria Changes Over Time. I. Moustaki
A Review of Estimation Methods for Latent Variable Models. G. Zhang
C.T. Lee
Standard Errors for Ordinary Least Squares Estimates of Parameters in Structural Equation Modeling. L. Cai
Three Cheers for the Asymptotically Distribution Free Theory of Estimation and Inference: Some Recent Applications in Linear and Nonlinear Latent Variable Modeling. K. A. Duncan
S. N. MacEachern
Nonparametric Bayesian Modeling of Item Response Curves with a Three Parameter Logistic Prior Mean. W. A. Nicewander
Exact Solutions for IRT Latent Regression Slopes and Latent Variable Intercorrelations. S. du Toit
Analysis of Structural Equation Models Based on a Mixture of Continuous and Ordinal Random Variables in the Case of Complex Survey Data. Part II. Drawing Meaning from Latent Variable Models. R. E. Millsap
A Simulation Paradigm for Evaluating Approximate Fit. R. C. MacCallum
T. Lee
M. W. Browne
Fungible Parameter Values in Latent Curve Models. A. Shapiro
Statistical Inference of Moment/Covariance Structures. J. L. Rodgers
W. H. Beasley
Fisher
Gosset
and Alternative Hypothesis Significance Testing (AHST): Using the Bootstrap to Test Scientific Hypotheses about the Multiple Correlation. S. M. Boker
M. Martin
On The Equilibrium Dynamics of Meaning. K. Tateneni
M. Schiller
Applying Components Analysis to Attitudinal Segmentation.