D M Kaplan
Biographic Data
| ID | 1109947 |
|---|---|
| NAME | D M Kaplan |
| GIVEN NAMES | D M |
| FAMILY NAME | Kaplan |
| SIGNATURE | KAPLAN D M |
| AFFILIATIONS | University of Delaware |
| ORCID | 0000-0002-2333-1481 |
| VERIFIED | Yes |
| TOTAL WORKS | 15 |
| TOTAL CITATIONS | 23 |
| AUTHOR COUNT | 15 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1985 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 1 |
Representations
Nomadisme des scientifiques et nouvelle géopolitique du savoir
La mobilité des professionnels hautement qualifiés est désormais au cœur de l’actualité en raison de la mondialisation et du rôle accru du savoir dans les relations socio-économiques d’aujourd’hui. Cependant, la propension des scientifiques à se déplacer géographiquement en réponse à des besoins intellectuels, sociaux et autres n’est pas sans antécédents. Les auteurs du présent article étudient la mobilité dans son contexte actuel et à la lumière…
"The Darker Side of the "Original Affluent Society
Hunter-gatherers emerged from the "Man the Hunter" conference in 1966 as the "original affluent society." The main features of this thesis now seem to be widely accepted by anthropologists, despite the strong reservations expressed by certain specialists in foraging societies concerning the data advanced to support the claim. This essay brings together a portion of the data and argumentation in the literature that raise a number of questions abou…
An Extension of the Propensity Score Adjustment Method for the Analysis of Group Differences in MIMIC Models
This article proposes an extension of the propensity score adjustment method to latent variable models. The propensity score was proposed by Rosenbaum and Rubin (1983) as a means of balancing treatment and control groups with respect to observed covariates in non-randomized studies. The propensity score is defined as the conditional probability of assignment to a treatment group given a set of observed covariates. In a typical application of this…
Estimator Conditioning Diagnostics for Covariance Structure Models
This article studies the utility of a general set of diagnostics for assessing conditioning problems in the covariance structure modeling framework. The diagnostics are based on extensions of the condition index and variance decomposition proportions advanced by Belsley and are based on using the covariance matrix of the estimates. A series of simulations with a variety of covariance structure models as well as a real data example show that these…
Comprehensive effects of alcohol: Development and psychometric assessment of a new expectancy questionnaire.
A comprehensive measure of alcohol outcome expectancies was developed through the use of exploratory and confirmatory factor analyses. The questionnaire assesses both positive and negative expected effects of alcohol as well as the subjective evaluation of those effects. The measure was found to demonstrate adequate internal consistency, temporal stability, and construct validity. Criterion validity was demonstrated through structural regression …
Asymptomatic Independence and Separability in Convariance Structure Models: Implications for Specification Error, Power, and Model Modification
This article presents a didactic discussion on the role of asymptotically independent test statistics and separable hypotheses as they pertain to issues of specification error, power, and model modification in the covariance structure modeling framework. Specifically, it is shown that when restricting two parameter estimates on the basis of the multivariate Wald test, the condition of asymptotic independence is necessary but not sufficient for th…
A comparison of some methodologies for the factor analysis of non‐normal Likert variables: A note on the size of the model
This paper expands on a recent study by Muthen & Kaplan (1985) by examining the impact of non‐normal Likert variables on testing and estimation in factor analysis for models of various size. Normal theory GLS and the recently developed ADF estimator are compared for six cases of non‐normality, two sample sizes, and four models of increasing size in a Monte Carlo framework with a large number of replications. Results show that GLS and ADF chi‐squa…
Evaluating and Modifying Covariance Structure Models: A Review and Recommendation
The purpose of this article is to present a strategy for the evaluation and modification of covariance structure models. The approach makes use of recent developments in estimation under non-standard conditions and unified asymptotic theory related to hypothesis testing. Factors affecting the evaluation and modification of these models are reviewed in terms of nonnormality, missing data, specification error, and sensitivity to large sample size. …
A Rejoinder on Evaluating and Modifying Covariance Structure Models
L'auteur propose une reponse a l'ensemble des commentaires et critiques publies dans le meme numero de la revue suite a un article sur l'evaluation et la modelisation des modeles de structure de covariance
Model Modification in Covariance Structure Analysis: Application of the Expected Parameter Change Statistic
This paper examines the problem of model modification in covariance structure analysis. Two methods of model modification are studied: the Modification Index (MI) which suggests modifications based on the largest drop in the overall value of the test statistic, and the Expected Parameter Change Statistic (EPC) which suggests modifications based on the removal of large and interesting specifications errors. Following a detailed discussion of the t…
A Study of the Sampling Variability and z-Values of Parameter Estimates From Misspecified Structural Equation Models
This article considers the sampling variability and z-values of parameter estimates from misspecified structural equation models. A Monte Carlo study is employed wherein a prototype structural model is analyzed under one incorrect restriction and two incorrect restrictions. True values of the misspecified parameters are varied to reflect increasing distances from the null hypothesis. Sample size differences are also considered. Comparisons are ma…
The Impact of Specification Error on the Estimation, Testing, and Improvement of Structural Equation Models
The purpose of this paper is to assess the impact of misspecification on the estimation, testing, and improvement of structural equation models. A population study is conducted whereby a prototypical latent variable model is misspecified in various ways. Measurement model and structural model misspecifications are considered separately and together. The maximum likelihood estimator (ML) is compared to a limited information two-stage least squares…
On Structural Equation Modeling with Data that are not Missing Completely at Random
A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connec…
A comparison of some methodologies for the factor analysis of non‐normal Likert variables
This paper considers the problem of applying factor analysis to non‐normal categorical variables. A Monte Carlo study is conducted where five prototypical cases of non‐normal variables are generated. Two normal theory estimators, ML and GLS, are compared to Browne's (1982) ADF estimator. A categorical variable methodology (CVM) estimator of Muthén (1984) is also considered for the most severely skewed case. Results show that ML and GLS chi‐square…
"The Darker Side of the "Original Affluent Society
Hunter-gatherers emerged from the "Man the Hunter" conference in 1966 as the "original affluent society." The main features of this thesis now seem to be widely accepted by anthropologists, despite the strong reservations expressed by certain specialists in foraging societies concerning the data advanced to support the claim. This essay brings together a portion of the data and argumentation in the literature that raise a number of questions abou…
Estimator Conditioning Diagnostics for Covariance Structure Models
This article studies the utility of a general set of diagnostics for assessing conditioning problems in the covariance structure modeling framework. The diagnostics are based on extensions of the condition index and variance decomposition proportions advanced by Belsley and are based on using the covariance matrix of the estimates. A series of simulations with a variety of covariance structure models as well as a real data example show that these…
A comparison of some methodologies for the factor analysis of non‐normal Likert variables
This paper considers the problem of applying factor analysis to non‐normal categorical variables. A Monte Carlo study is conducted where five prototypical cases of non‐normal variables are generated. Two normal theory estimators, ML and GLS, are compared to Browne's (1982) ADF estimator. A categorical variable methodology (CVM) estimator of Muthén (1984) is also considered for the most severely skewed case. Results show that ML and GLS chi‐square…
On Structural Equation Modeling with Data that are not Missing Completely at Random
A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connec…
The Impact of Specification Error on the Estimation, Testing, and Improvement of Structural Equation Models
The purpose of this paper is to assess the impact of misspecification on the estimation, testing, and improvement of structural equation models. A population study is conducted whereby a prototypical latent variable model is misspecified in various ways. Measurement model and structural model misspecifications are considered separately and together. The maximum likelihood estimator (ML) is compared to a limited information two-stage least squares…
Model Modification in Covariance Structure Analysis: Application of the Expected Parameter Change Statistic
This paper examines the problem of model modification in covariance structure analysis. Two methods of model modification are studied: the Modification Index (MI) which suggests modifications based on the largest drop in the overall value of the test statistic, and the Expected Parameter Change Statistic (EPC) which suggests modifications based on the removal of large and interesting specifications errors. Following a detailed discussion of the t…
A Study of the Sampling Variability and z-Values of Parameter Estimates From Misspecified Structural Equation Models
This article considers the sampling variability and z-values of parameter estimates from misspecified structural equation models. A Monte Carlo study is employed wherein a prototype structural model is analyzed under one incorrect restriction and two incorrect restrictions. True values of the misspecified parameters are varied to reflect increasing distances from the null hypothesis. Sample size differences are also considered. Comparisons are ma…
Evaluating and Modifying Covariance Structure Models: A Review and Recommendation
The purpose of this article is to present a strategy for the evaluation and modification of covariance structure models. The approach makes use of recent developments in estimation under non-standard conditions and unified asymptotic theory related to hypothesis testing. Factors affecting the evaluation and modification of these models are reviewed in terms of nonnormality, missing data, specification error, and sensitivity to large sample size. …
A Rejoinder on Evaluating and Modifying Covariance Structure Models
L'auteur propose une reponse a l'ensemble des commentaires et critiques publies dans le meme numero de la revue suite a un article sur l'evaluation et la modelisation des modeles de structure de covariance
A comparison of some methodologies for the factor analysis of non‐normal Likert variables: A note on the size of the model
This paper expands on a recent study by Muthen & Kaplan (1985) by examining the impact of non‐normal Likert variables on testing and estimation in factor analysis for models of various size. Normal theory GLS and the recently developed ADF estimator are compared for six cases of non‐normality, two sample sizes, and four models of increasing size in a Monte Carlo framework with a large number of replications. Results show that GLS and ADF chi‐squa…
Comprehensive effects of alcohol: Development and psychometric assessment of a new expectancy questionnaire.
A comprehensive measure of alcohol outcome expectancies was developed through the use of exploratory and confirmatory factor analyses. The questionnaire assesses both positive and negative expected effects of alcohol as well as the subjective evaluation of those effects. The measure was found to demonstrate adequate internal consistency, temporal stability, and construct validity. Criterion validity was demonstrated through structural regression …
Asymptomatic Independence and Separability in Convariance Structure Models: Implications for Specification Error, Power, and Model Modification
This article presents a didactic discussion on the role of asymptotically independent test statistics and separable hypotheses as they pertain to issues of specification error, power, and model modification in the covariance structure modeling framework. Specifically, it is shown that when restricting two parameter estimates on the basis of the multivariate Wald test, the condition of asymptotic independence is necessary but not sufficient for th…
Estimator Conditioning Diagnostics for Covariance Structure Models
This article studies the utility of a general set of diagnostics for assessing conditioning problems in the covariance structure modeling framework. The diagnostics are based on extensions of the condition index and variance decomposition proportions advanced by Belsley and are based on using the covariance matrix of the estimates. A series of simulations with a variety of covariance structure models as well as a real data example show that these…
An Extension of the Propensity Score Adjustment Method for the Analysis of Group Differences in MIMIC Models
This article proposes an extension of the propensity score adjustment method to latent variable models. The propensity score was proposed by Rosenbaum and Rubin (1983) as a means of balancing treatment and control groups with respect to observed covariates in non-randomized studies. The propensity score is defined as the conditional probability of assignment to a treatment group given a set of observed covariates. In a typical application of this…
"The Darker Side of the "Original Affluent Society
Hunter-gatherers emerged from the "Man the Hunter" conference in 1966 as the "original affluent society." The main features of this thesis now seem to be widely accepted by anthropologists, despite the strong reservations expressed by certain specialists in foraging societies concerning the data advanced to support the claim. This essay brings together a portion of the data and argumentation in the literature that raise a number of questions abou…
Nomadisme des scientifiques et nouvelle géopolitique du savoir
La mobilité des professionnels hautement qualifiés est désormais au cœur de l’actualité en raison de la mondialisation et du rôle accru du savoir dans les relations socio-économiques d’aujourd’hui. Cependant, la propension des scientifiques à se déplacer géographiquement en réponse à des besoins intellectuels, sociaux et autres n’est pas sans antécédents. Les auteurs du présent article étudient la mobilité dans son contexte actuel et à la lumière…
Representations
Mathematics (11 works) · Statistics (11 works) · Econometrics (10 works) · Computer Science (8 works) · Advanced Statistical Methods and Models (6 works) · Covariance (5 works) · Psychometric Methodologies and Testing (5 works) · Statistical Methods and Bayesian Inference (5 works) · Estimator (4 works) · Psychology (4 works)