David W Gerbing
Dados Biográficos
| ID | 333801 |
|---|---|
| NOME | David W Gerbing |
| PRENOMES | David W |
| SOBRENOME | Gerbing |
| ASSINATURA | GERBING D W |
| AFILIAÇÕES | Portland State University |
| ORCID | 0000-0001-6998-8350 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 17 |
| TOTAL DE CITAÇÕES | 56 |
| TOTAL COMO AUTOR | 17 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1982 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 1996 |
| ÍNDICE H | 4 |
Viability of exploratory factor analysis as a precursor to confirmatory factor analysis
As part of the development of a comprehensive strategy for structural equation model building and assessment, a Monte Carlo study evaluated the effectiveness of different exploratory factor analysis extraction and rotation methods for correctly identifying the known population multiple‐indicator measurement model. The exploratory methods fared well in recovering the model except in small sample sizes with highly correlated factors, and even in th…
Monte Carlo Evaluations of Goodness of Fit Indices for Structural Equation Models
This article reviews proposed goodness-of-fit indices for structural equation models and the Monte Carlo studies that have empirically assessed their distributional properties. The cumulative contributions of the studies are summarized, and the variables under which the indices are studied are noted. A primary finding is that many of the indices used until the late 1980s, including Jöreskog and Sörbom's (1981) GFI and Bentler and Bonett's (1980) …
Assumptions and Comparative Strengths of the Two-Step Approach
Fornell and Yi (1992 [this issue]) have discussed four assumptions that they contend underlie two-step approaches to structural equation modeling. Each of these assumptions is demonstrated to not be an assumption of the two-step approach recommended by Anderson and Gerbing (1988). In doing so, an attempt is made to provide some clarification and guidance to researchers interested in employing structural equation modeling to test and develop theor…
Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities.
The 16PF Related to the Five-Factor Model of Personality
This article examines the Sixteen Personality Factor Inventory (16PF; Cattell, Eber, & Tatsuoka, 1970) in terms of recent methodological and substantive developments: restricted (confirmatory) factor analysis and the five-factor model of personality as operationalized by the NEO-PI (NEO Personality Inventory). A multiple-indicator measurement model of the 16PF was constructed and analyzed with a restricted factor analysis and then cross-validated…
Psychologists in business schools
Psychologists in business schools
An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment
An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment
The authors outline an updated paradigm for scale development that incorporates confirmatory factor analysis for the assessment of unidimensionality. Under this paradigm, item-total correlations and exploratory factor analysis are used to provide preliminary scales. The unidimensionality of each scale then is assessed simultaneously with confirmatory factor analysis. After unidimensional measurement has been acceptably achieved, the reliability o…
Structural equation modeling in practice
Structural equation modeling in practice
In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of …
Toward a Conceptualization of Impulsivity
The components underlying items from a comprehensive but diverse domain of impulsivity measures were investigated. The disparity of items within this domain attests to the lack of a coherent framework from which to conceptualize impulsivity. The self-report measures included in this study were the 16PF Impulsivity scale, the GZTS Restraint, Thoughtfulness and General Activity scales, the PRF Impulsivity scale, the EASI-III Impulsivity scale, the …
The Effects of Sampling Error and Model Characteristics on Parameter Estimation for Maximum Likelihood Confirmatory Factor Analysis
Monte Carlo methods were used to systematically study the effects of sampling error and model characteristics upon parameter estimates and their associated standard errors in maximum likelihood confirmatory factor analysis. Sample sizes were varied from 50 to 300 for models defined by different numbers of indicators per factor, numbers of factors, correlations between factors, and indicator reliabilities. The measurement and structural parameter …
The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis
A Monte Carlo study assessed the effect of sampling error and model characteristics on the occurrence of nonconvergent solutions, improper solutions and the distribution of goodness-of-fit indices in maximum likelihood confirmatory factor analysis. Nonconvergent and improper solutions occurred more frequently for smaller sample sizes and for models with fewer indicators of each factor. Effects of practical significance due to sample size, the num…
On the Meaning of within-Factor Correlated Measurement Errors
The meaning of correlated measurement errors is discussed within a hierarchical framework of error terms provided by true score, first-order factor, and second-order factor models: random error, indicator specific error, and group specific error, respectively. Group specific error can be represented either as extraneous first-order factors or as unwanted components of first-order factors that define a second-order factor. The uncritical use of co…
The Metric of the Latent Variables in a Lisrel-IV Analysis
A potential source of confusion in the interpretation of a LISREL-IV analysis is the metric of the latent variables. This paper demonstrates that fixing the pattern coefficient of one of the indicators of each latent variable to 1.0 results in an arbitrary and meaningless metric which is usually different for each latent variable. Since many of the parameter estimates such as the pattern coefficients, the factor loadings, and the variance-covaria…
Machiavellian beliefs and personality
Assumptions and Comparative Strengths of the Two-Step Approach
Fornell and Yi (1992 [this issue]) have discussed four assumptions that they contend underlie two-step approaches to structural equation modeling. Each of these assumptions is demonstrated to not be an assumption of the two-step approach recommended by Anderson and Gerbing (1988). In doing so, an attempt is made to provide some clarification and guidance to researchers interested in employing structural equation modeling to test and develop theor…
On the Meaning of within-Factor Correlated Measurement Errors
The meaning of correlated measurement errors is discussed within a hierarchical framework of error terms provided by true score, first-order factor, and second-order factor models: random error, indicator specific error, and group specific error, respectively. Group specific error can be represented either as extraneous first-order factors or as unwanted components of first-order factors that define a second-order factor. The uncritical use of co…
Monte Carlo Evaluations of Goodness of Fit Indices for Structural Equation Models
This article reviews proposed goodness-of-fit indices for structural equation models and the Monte Carlo studies that have empirically assessed their distributional properties. The cumulative contributions of the studies are summarized, and the variables under which the indices are studied are noted. A primary finding is that many of the indices used until the late 1980s, including Jöreskog and Sörbom's (1981) GFI and Bentler and Bonett's (1980) …
Machiavellian beliefs and personality
The Metric of the Latent Variables in a Lisrel-IV Analysis
A potential source of confusion in the interpretation of a LISREL-IV analysis is the metric of the latent variables. This paper demonstrates that fixing the pattern coefficient of one of the indicators of each latent variable to 1.0 results in an arbitrary and meaningless metric which is usually different for each latent variable. Since many of the parameter estimates such as the pattern coefficients, the factor loadings, and the variance-covaria…
Machiavellian beliefs and personality
The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis
A Monte Carlo study assessed the effect of sampling error and model characteristics on the occurrence of nonconvergent solutions, improper solutions and the distribution of goodness-of-fit indices in maximum likelihood confirmatory factor analysis. Nonconvergent and improper solutions occurred more frequently for smaller sample sizes and for models with fewer indicators of each factor. Effects of practical significance due to sample size, the num…
On the Meaning of within-Factor Correlated Measurement Errors
The meaning of correlated measurement errors is discussed within a hierarchical framework of error terms provided by true score, first-order factor, and second-order factor models: random error, indicator specific error, and group specific error, respectively. Group specific error can be represented either as extraneous first-order factors or as unwanted components of first-order factors that define a second-order factor. The uncritical use of co…
The Effects of Sampling Error and Model Characteristics on Parameter Estimation for Maximum Likelihood Confirmatory Factor Analysis
Monte Carlo methods were used to systematically study the effects of sampling error and model characteristics upon parameter estimates and their associated standard errors in maximum likelihood confirmatory factor analysis. Sample sizes were varied from 50 to 300 for models defined by different numbers of indicators per factor, numbers of factors, correlations between factors, and indicator reliabilities. The measurement and structural parameter …
Toward a Conceptualization of Impulsivity
The components underlying items from a comprehensive but diverse domain of impulsivity measures were investigated. The disparity of items within this domain attests to the lack of a coherent framework from which to conceptualize impulsivity. The self-report measures included in this study were the 16PF Impulsivity scale, the GZTS Restraint, Thoughtfulness and General Activity scales, the PRF Impulsivity scale, the EASI-III Impulsivity scale, the …
An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment
An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment
The authors outline an updated paradigm for scale development that incorporates confirmatory factor analysis for the assessment of unidimensionality. Under this paradigm, item-total correlations and exploratory factor analysis are used to provide preliminary scales. The unidimensionality of each scale then is assessed simultaneously with confirmatory factor analysis. After unidimensional measurement has been acceptably achieved, the reliability o…
Structural equation modeling in practice
Structural equation modeling in practice
In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of …
Psychologists in business schools
Psychologists in business schools
Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities.
The 16PF Related to the Five-Factor Model of Personality
This article examines the Sixteen Personality Factor Inventory (16PF; Cattell, Eber, & Tatsuoka, 1970) in terms of recent methodological and substantive developments: restricted (confirmatory) factor analysis and the five-factor model of personality as operationalized by the NEO-PI (NEO Personality Inventory). A multiple-indicator measurement model of the 16PF was constructed and analyzed with a restricted factor analysis and then cross-validated…
Monte Carlo Evaluations of Goodness of Fit Indices for Structural Equation Models
This article reviews proposed goodness-of-fit indices for structural equation models and the Monte Carlo studies that have empirically assessed their distributional properties. The cumulative contributions of the studies are summarized, and the variables under which the indices are studied are noted. A primary finding is that many of the indices used until the late 1980s, including Jöreskog and Sörbom's (1981) GFI and Bentler and Bonett's (1980) …
Assumptions and Comparative Strengths of the Two-Step Approach
Fornell and Yi (1992 [this issue]) have discussed four assumptions that they contend underlie two-step approaches to structural equation modeling. Each of these assumptions is demonstrated to not be an assumption of the two-step approach recommended by Anderson and Gerbing (1988). In doing so, an attempt is made to provide some clarification and guidance to researchers interested in employing structural equation modeling to test and develop theor…
Viability of exploratory factor analysis as a precursor to confirmatory factor analysis
As part of the development of a comprehensive strategy for structural equation model building and assessment, a Monte Carlo study evaluated the effectiveness of different exploratory factor analysis extraction and rotation methods for correctly identifying the known population multiple‐indicator measurement model. The exploratory methods fared well in recovering the model except in small sample sizes with highly correlated factors, and even in th…
Mathematics (12 obras) · Computer Science (11 obras) · Psychology (11 obras) · Structural equation modeling (11 obras) · Econometrics (10 obras) · Statistics (9 obras) · Psychometric Methodologies and Testing (7 obras) · Confirmatory factor analysis (6 obras) · Social Psychology (6 obras) · Psychometrics (5 obras)