2007, 1. Aufl., Wiley series in probability and statistics, ISBN 9780470024232, xv, 432

***Winner of the 2008 Ziegel Prize for outstanding new book of the year***Structural equation modeling (SEM) is a powerful multivariate method allowing the...

Bayesian statistical decision theory | Structural equation modeling | Lehrbuch | Variable | Wahrscheinlichkeitsrechnung | Faktorenanalyse | Entscheidungstheorie | Computerunterstütztes Verfahren | Datenanalyse | Daten | Vergleich | Statistische Methode | Algorithmus | Modell | Software | Statistik | Gleichung (Math) | Varianzanalyse

Bayesian statistical decision theory | Structural equation modeling | Lehrbuch | Variable | Wahrscheinlichkeitsrechnung | Faktorenanalyse | Entscheidungstheorie | Computerunterstütztes Verfahren | Datenanalyse | Daten | Vergleich | Statistische Methode | Algorithmus | Modell | Software | Statistik | Gleichung (Math) | Varianzanalyse

Book

2012, 1. Aufl., ISBN 9780470669525, 397

This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed...

Probability & Statistics | General | Mathematics | MATHEMATICS / Probability & Statistics / General

Probability & Statistics | General | Mathematics | MATHEMATICS / Probability & Statistics / General

eBook

Sociological methods & research, ISSN 1552-8294, 2016, Volume 35, Issue 3, pp. 352 - 381

...A Unified Maximum
Likelihood Approach for
Analyzing Structural
Equation Models With
Missing Nonstandard Data
Sik-Yum Lee
Xin-Yuan Song
The Chinese University...

Gibbs sampler | Bayesian information criterion | Path sampling | MCEM algorithm | CARLO EM ALGORITHM | MIXED MODELS | NORMALIZING CONSTANTS | path sampling | DICHOTOMOUS-VARIABLES | POLYTOMOUS DATA | BAYESIAN-ANALYSIS | LATENT VARIABLE MODELS | RESPONSES | SOCIAL SCIENCES, MATHEMATICAL METHODS | SOCIOLOGY | Monte Carlo method | Approaches | Data | Structural equation models | Sampling | Bayesian analysis | Structural models

Gibbs sampler | Bayesian information criterion | Path sampling | MCEM algorithm | CARLO EM ALGORITHM | MIXED MODELS | NORMALIZING CONSTANTS | path sampling | DICHOTOMOUS-VARIABLES | POLYTOMOUS DATA | BAYESIAN-ANALYSIS | LATENT VARIABLE MODELS | RESPONSES | SOCIAL SCIENCES, MATHEMATICAL METHODS | SOCIOLOGY | Monte Carlo method | Approaches | Data | Structural equation models | Sampling | Bayesian analysis | Structural models

Journal Article

Statistics in medicine, ISSN 1097-0258, 2003, Volume 22, Issue 19, pp. 3073 - 3088

Structural equation modelling has been used extensively in the behavioural and social sciences for studying interrelationships among manifest and latent...

Gibbs sampler | posterior analysis | latent variables | non‐adherence | conditional distributions | Latent variables | Conditional distributions | Non-adherence | Posterior analysis | MEDICINE, RESEARCH & EXPERIMENTAL | non-adherence | LONGITUDINAL BINARY | MEDICAL INFORMATICS | STATISTICS & PROBABILITY | POLYTOMOUS DATA | MAXIMUM LIKELIHOOD | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | MEASUREMENT ERROR | EM ALGORITHM | OUTCOMES | LINEAR-MODEL | Antihypertensive Agents - administration & dosage | Hypertension - drug therapy | Algorithms | Humans | Bayes Theorem | Patient Compliance - statistics & numerical data

Gibbs sampler | posterior analysis | latent variables | non‐adherence | conditional distributions | Latent variables | Conditional distributions | Non-adherence | Posterior analysis | MEDICINE, RESEARCH & EXPERIMENTAL | non-adherence | LONGITUDINAL BINARY | MEDICAL INFORMATICS | STATISTICS & PROBABILITY | POLYTOMOUS DATA | MAXIMUM LIKELIHOOD | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | MEASUREMENT ERROR | EM ALGORITHM | OUTCOMES | LINEAR-MODEL | Antihypertensive Agents - administration & dosage | Hypertension - drug therapy | Algorithms | Humans | Bayes Theorem | Patient Compliance - statistics & numerical data

Journal Article

Biometrics, ISSN 0006-341X, 09/2004, Volume 60, Issue 3, pp. 624 - 636

A general two-level latent variable model is developed to provide a comprehensive framework for model comparison of various submodels. Nonlinear relationships...

Path sampling | Covariates | MCEM algorithm | Model comparison | Nonlinear structural equations | Dichotomous and polytomous data | Two-level latent variable model | Biometrics | Datasets | Factor analysis | Multilevel models | Mathematical independent variables | Matrices | Standard error | Data models | Condoms | Modeling | Two‐level latent variable model | dichotomous and polytomous data | model comparison | NORMALIZING CONSTANTS | ALGORITHM | STATISTICS & PROBABILITY | path sampling | two-level latent variable model | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY | covariates | STRUCTURAL EQUATION MODELS | nonlinear structural equations | Data Interpretation, Statistical | Acquired Immunodeficiency Syndrome - transmission | Humans | Philippines | Acquired Immunodeficiency Syndrome - prevention & control | Acquired Immunodeficiency Syndrome - psychology | Male | Models, Statistical | Health Knowledge, Attitudes, Practice | Sex Work - psychology | Biometry | Likelihood Functions | Algorithms | Sex Work - statistics & numerical data | Female | Condoms - utilization | Monte Carlo Method

Path sampling | Covariates | MCEM algorithm | Model comparison | Nonlinear structural equations | Dichotomous and polytomous data | Two-level latent variable model | Biometrics | Datasets | Factor analysis | Multilevel models | Mathematical independent variables | Matrices | Standard error | Data models | Condoms | Modeling | Two‐level latent variable model | dichotomous and polytomous data | model comparison | NORMALIZING CONSTANTS | ALGORITHM | STATISTICS & PROBABILITY | path sampling | two-level latent variable model | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY | covariates | STRUCTURAL EQUATION MODELS | nonlinear structural equations | Data Interpretation, Statistical | Acquired Immunodeficiency Syndrome - transmission | Humans | Philippines | Acquired Immunodeficiency Syndrome - prevention & control | Acquired Immunodeficiency Syndrome - psychology | Male | Models, Statistical | Health Knowledge, Attitudes, Practice | Sex Work - psychology | Biometry | Likelihood Functions | Algorithms | Sex Work - statistics & numerical data | Female | Condoms - utilization | Monte Carlo Method

Journal Article

Journal of multivariate analysis, ISSN 0047-259X, 07/2002, Volume 82, Issue 1, pp. 166 - 188

Varying coefficient models are useful extensions of the classical linear models. Under the condition that the coefficient functions possess about the same...

varying-coefficient models | one-step method | local polynomial fit | optimal rate of convergence | two-step method | mean squared errors | semivarying-coefficient models | Two-step method | Mean squared errors | Semivarying-coefficient models | Optimal rate of convergence | Local polynomial fit | Varying-coefficient models | One-step method | models local polynomial fit | MULTIPLE-REGRESSION | varying-coefficient | STATISTICS & PROBABILITY | VARIABLE BANDWIDTH | BANDWIDTH SELECTION | semivarying-coefficient models varying-coefficient models local polynomial fit one-step method two-step method optimal rate of convergence mean squared errors

varying-coefficient models | one-step method | local polynomial fit | optimal rate of convergence | two-step method | mean squared errors | semivarying-coefficient models | Two-step method | Mean squared errors | Semivarying-coefficient models | Optimal rate of convergence | Local polynomial fit | Varying-coefficient models | One-step method | models local polynomial fit | MULTIPLE-REGRESSION | varying-coefficient | STATISTICS & PROBABILITY | VARIABLE BANDWIDTH | BANDWIDTH SELECTION | semivarying-coefficient models varying-coefficient models local polynomial fit one-step method two-step method optimal rate of convergence mean squared errors

Journal Article

Statistics in Medicine, ISSN 0277-6715, 07/2008, Volume 27, Issue 16, pp. 3017 - 3041

The analysis of longitudinal data to study changes in variables measured repeatedly over time has received considerable attention in many fields. This paper...

latent variables | longitudinal study on cocaine use | model comparison | ordered categorical variables | maximum likelihood | MCEM algorithm | Latent variables | Ordered categorical variables | Model comparison | Maximum likelihood | Longitudinal study on cocaine use | MEDICINE, RESEARCH & EXPERIMENTAL | COCAINE ABUSERS | MEDICAL INFORMATICS | NORMALIZING CONSTANTS | TREATMENT OUTCOMES | FOLLOW-UP | STATISTICS & PROBABILITY | DEPENDENCE | LATENT VARIABLE MODELS | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | ALCOHOL | EM ALGORITHM | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Multivariate Analysis | Algorithms | Computer Simulation | Humans | Cocaine-Related Disorders - therapy | Models, Statistical | Longitudinal Studies | Index Medicus

latent variables | longitudinal study on cocaine use | model comparison | ordered categorical variables | maximum likelihood | MCEM algorithm | Latent variables | Ordered categorical variables | Model comparison | Maximum likelihood | Longitudinal study on cocaine use | MEDICINE, RESEARCH & EXPERIMENTAL | COCAINE ABUSERS | MEDICAL INFORMATICS | NORMALIZING CONSTANTS | TREATMENT OUTCOMES | FOLLOW-UP | STATISTICS & PROBABILITY | DEPENDENCE | LATENT VARIABLE MODELS | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | ALCOHOL | EM ALGORITHM | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Multivariate Analysis | Algorithms | Computer Simulation | Humans | Cocaine-Related Disorders - therapy | Models, Statistical | Longitudinal Studies | Index Medicus

Journal Article

British journal of mathematical & statistical psychology, ISSN 0007-1102, 2004, Volume 57, Issue 1, pp. 131 - 150

Missing data are very common in behavioural and psychological research. In this paper, we develop a Bayesian approach in the context of a general nonlinear...

LATENT VARIABLE MODELS | REGRESSION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | MARGINAL LIKELIHOOD | STATE | STATISTICS & PROBABILITY | PSYCHOLOGY, MATHEMATICAL | SIMULATION | PSYCHOLOGY, EXPERIMENTAL | POSTERIOR DISTRIBUTIONS | Models, Theoretical | Algorithms | Nonlinear Dynamics | Humans | Bayes Theorem | Psychology - statistics & numerical data | Mathematical models | Simulation | Comparative analysis | Bayesian analysis

LATENT VARIABLE MODELS | REGRESSION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | MARGINAL LIKELIHOOD | STATE | STATISTICS & PROBABILITY | PSYCHOLOGY, MATHEMATICAL | SIMULATION | PSYCHOLOGY, EXPERIMENTAL | POSTERIOR DISTRIBUTIONS | Models, Theoretical | Algorithms | Nonlinear Dynamics | Humans | Bayes Theorem | Psychology - statistics & numerical data | Mathematical models | Simulation | Comparative analysis | Bayesian analysis

Journal Article

Multivariate behavioral research, ISSN 1532-7906, 2006, Volume 41, Issue 3, pp. 337 - 365

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of...

DISTRIBUTIONS | MAXIMUM-LIKELIHOOD-ESTIMATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | ALGORITHM | INDICATOR | STATE | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, EXPERIMENTAL | Structural Equation Models | Error of Measurement | Bayesian Statistics | Markov Processes | Monte Carlo Methods | Methods Research | Research Methodology | Demonstration Programs | Latent Variables | Simulation | Computation | Models | Evaluation Methods

DISTRIBUTIONS | MAXIMUM-LIKELIHOOD-ESTIMATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | ALGORITHM | INDICATOR | STATE | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, EXPERIMENTAL | Structural Equation Models | Error of Measurement | Bayesian Statistics | Markov Processes | Monte Carlo Methods | Methods Research | Research Methodology | Demonstration Programs | Latent Variables | Simulation | Computation | Models | Evaluation Methods

Journal Article

Biometrika, ISSN 0006-3444, 9/2001, Volume 88, Issue 3, pp. 727 - 737

This paper proposes several case-deletion measures for assessing the influence of an observation for complicated models with real missing data or hypothetical...

Tanneries | Datasets | Missing data | Maximum likelihood estimation | Approximation | Statistical models | Linear regression | Maximum likelihood estimators | Data models | Regression analysis | β-function | Case-deletion measure | EM algorithm | LINEAR-REGRESSION | MATHEMATICS, APPLIED | MAXIMUM-LIKELIHOOD | case-deletion measure | Q-function | STATISTICS & PROBABILITY | BIOLOGY, MISCELLANEOUS | missing data | DIAGNOSTICS

Tanneries | Datasets | Missing data | Maximum likelihood estimation | Approximation | Statistical models | Linear regression | Maximum likelihood estimators | Data models | Regression analysis | β-function | Case-deletion measure | EM algorithm | LINEAR-REGRESSION | MATHEMATICS, APPLIED | MAXIMUM-LIKELIHOOD | case-deletion measure | Q-function | STATISTICS & PROBABILITY | BIOLOGY, MISCELLANEOUS | missing data | DIAGNOSTICS

Journal Article

Biometrics, ISSN 0006-341X, 09/2001, Volume 57, Issue 3, pp. 787 - 794

Two-level data with hierarchical structure and mixed continuous and polytomous data are very common in biomedical research. In this article, we propose a...

Monte Carlo EM algorithm | Factor analysis | Two-level latent variable models | Mixed continuous and polytomous data | Biometrics | Datasets | Maximum likelihood estimation | Mathematical independent variables | Sample mean | Condoms | Modeling | Covariance matrices | Parametric models | Two‐level latent variable models | factor analysis | MATHEMATICS, APPLIED | EM ALGORITHM | DISCRETE | mixed continuous and polytomous data | STRUCTURAL EQUATION MODELS | CONTINUOUS OUTCOMES | STATISTICS & PROBABILITY | two-level latent variable models | BIOLOGY, MISCELLANEOUS | Likelihood Functions | Algorithms | Sex Work | Acquired Immunodeficiency Syndrome - transmission | Humans | Risk Factors | Acquired Immunodeficiency Syndrome - prevention & control | Female | Monte Carlo Method | Biometry

Monte Carlo EM algorithm | Factor analysis | Two-level latent variable models | Mixed continuous and polytomous data | Biometrics | Datasets | Maximum likelihood estimation | Mathematical independent variables | Sample mean | Condoms | Modeling | Covariance matrices | Parametric models | Two‐level latent variable models | factor analysis | MATHEMATICS, APPLIED | EM ALGORITHM | DISCRETE | mixed continuous and polytomous data | STRUCTURAL EQUATION MODELS | CONTINUOUS OUTCOMES | STATISTICS & PROBABILITY | two-level latent variable models | BIOLOGY, MISCELLANEOUS | Likelihood Functions | Algorithms | Sex Work | Acquired Immunodeficiency Syndrome - transmission | Humans | Risk Factors | Acquired Immunodeficiency Syndrome - prevention & control | Female | Monte Carlo Method | Biometry

Journal Article

Structural Equation Modeling: A Multidisciplinary Journal, ISSN 1070-5511, 04/2009, Volume 16, Issue 2, pp. 245 - 266

In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in...

VARIABLE MODELS | STRUCTURAL EQUATION MODELS | COCAINE | SOCIAL SCIENCES, MATHEMATICAL METHODS | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | Multivariate Analysis | Structural Equation Models | Simulation | Longitudinal Studies | Bayesian Statistics | Medical Research

VARIABLE MODELS | STRUCTURAL EQUATION MODELS | COCAINE | SOCIAL SCIENCES, MATHEMATICAL METHODS | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | Multivariate Analysis | Structural Equation Models | Simulation | Longitudinal Studies | Bayesian Statistics | Medical Research

Journal Article

Multivariate Behavioral Research, ISSN 0027-3171, 01/2004, Volume 39, Issue 1, pp. 37 - 67

Various approaches using the maximum likelihood (ML) option of the LISREL program and products of indicators have been proposed to analyze structural equation...

REGRESSION | MAXIMUM-LIKELIHOOD-ESTIMATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | MODELS | ALGORITHM | STATE | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, EXPERIMENTAL | STATISTICAL-ANALYSIS | Comparative Analysis | Evaluation Methods | Structural Equation Models | Simulation | Statistical Analysis

REGRESSION | MAXIMUM-LIKELIHOOD-ESTIMATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | MODELS | ALGORITHM | STATE | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, EXPERIMENTAL | STATISTICAL-ANALYSIS | Comparative Analysis | Evaluation Methods | Structural Equation Models | Simulation | Statistical Analysis

Journal Article

Psychometrika, ISSN 1860-0980, 2006, Volume 71, Issue 3, pp. 565 - 585

... -TAILED DISTRIBUTIONS FOR NONLINEAR
STRUCTURAL EQUA TION MODELS WITH MISSING DA TA
SIK-YUM LEE
THE CHINESE UNIVERSITY OF HONG KONG
YE-MAO XIA
THE CHINESE UNIVERSITY...

heavy-tailed distributions | Gibbs sampler | Psychology | Assessment, Testing and Evaluation | MCEM algorithm | Statistical Theory and Methods | Psychometrics | path sampling | outliers | Bayesian information criterion | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | Outliers | Path sampling | Heavy-tailed distributions | ROBUSTNESS | COVARIANCE STRUCTURE-ANALYSIS | STATISTICAL-INFERENCE | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | EM ALGORITHM | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, MATHEMATICAL | Social Science Research | Educational Research | Comparative Analysis | Structural Equation Models | Error of Measurement | Statistical Distributions | Bayesian Statistics | Psychological Studies | Monte Carlo Methods | Robustness (Statistics) | Behavioral Science Research | Maximum Likelihood Statistics | Analysis | Methods | Algorithms

heavy-tailed distributions | Gibbs sampler | Psychology | Assessment, Testing and Evaluation | MCEM algorithm | Statistical Theory and Methods | Psychometrics | path sampling | outliers | Bayesian information criterion | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | Outliers | Path sampling | Heavy-tailed distributions | ROBUSTNESS | COVARIANCE STRUCTURE-ANALYSIS | STATISTICAL-INFERENCE | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | EM ALGORITHM | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, MATHEMATICAL | Social Science Research | Educational Research | Comparative Analysis | Structural Equation Models | Error of Measurement | Statistical Distributions | Bayesian Statistics | Psychological Studies | Monte Carlo Methods | Robustness (Statistics) | Behavioral Science Research | Maximum Likelihood Statistics | Analysis | Methods | Algorithms

Journal Article

Organizational research methods, ISSN 1094-4281, 07/2002, Volume 5, Issue 3, pp. 275 - 298

This article discusses the use of an approach advocated in the psychometrics and statistics literature for analyzing square contingency tables with ordered and...

STRUCTURAL EQUATION MODELS | MANAGEMENT | PSYCHOLOGY, APPLIED | Studies | Organizational behavior | Models | Statistical analysis

STRUCTURAL EQUATION MODELS | MANAGEMENT | PSYCHOLOGY, APPLIED | Studies | Organizational behavior | Models | Statistical analysis

Journal Article

2007, ISBN 0444520449, xxii, 435

This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and...

Latent structure analysis

Latent structure analysis

Book

Journal of educational and behavioral statistics, ISSN 1935-1054, 2016, Volume 28, Issue 2, pp. 111 - 134

The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among...

Preliminary estimates | Missing data | Maximum likelihood estimation | Algorithms | Sample size | Educational research | Maximum likelihood estimators | Metropolitan areas | Standard error | Structural equation models | Gibbs sampler | Metropolis-Hastings algorithm | MCEM algorithm | Nonlinear structural equation models | DISTRIBUTIONS | EDUCATION & EDUCATIONAL RESEARCH | EM ALGORITHM | STATE | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, MATHEMATICAL | INCOMPLETE-DATA | missing data | Sample Size | Structural Equation Models | Simulation | Factor Analysis | Hong Kong | Computation | Behavioral Sciences | Computer Software | Mathematics | Foreign Countries | Latent variables | Properties | Nonlinear functional analysis | Maximum likelihood estimates (Statistics) | Methods

Preliminary estimates | Missing data | Maximum likelihood estimation | Algorithms | Sample size | Educational research | Maximum likelihood estimators | Metropolitan areas | Standard error | Structural equation models | Gibbs sampler | Metropolis-Hastings algorithm | MCEM algorithm | Nonlinear structural equation models | DISTRIBUTIONS | EDUCATION & EDUCATIONAL RESEARCH | EM ALGORITHM | STATE | SOCIAL SCIENCES, MATHEMATICAL METHODS | PSYCHOLOGY, MATHEMATICAL | INCOMPLETE-DATA | missing data | Sample Size | Structural Equation Models | Simulation | Factor Analysis | Hong Kong | Computation | Behavioral Sciences | Computer Software | Mathematics | Foreign Countries | Latent variables | Properties | Nonlinear functional analysis | Maximum likelihood estimates (Statistics) | Methods

Journal Article