Gerhard Arminger
Dados Biográficos
| ID | 302101 |
|---|---|
| NOME | Gerhard Arminger |
| PRENOMES | Gerhard |
| SOBRENOME | Arminger |
| ASSINATURA | ARMINGER G |
| AFILIAÇÕES | University of Wuppertal |
| VERIFICADO | Não |
| TOTAL DE OBRAS | 19 |
| TOTAL DE CITAÇÕES | 16 |
| TOTAL COMO AUTOR | 18 |
| TOTAL COMO EDITOR | 1 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1983 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2013 |
| ÍNDICE H | 2 |
Handbook of Statistical Modeling for the Social and Behavioral Sciences
Regression Analysis of Multivariate Binary Response Variables Using Rasch-Type Models and Finite-Mixture Methods
A model is considered for the regression analysis of multivariate binary data such as repeated-measures data (for example, panel data) or multiple-indicators with measures of some underlying characteristic such as attitude or ability (for example, surveys or tests). The model is related to the usual Rasch model, the usual latent-class model, and other familiar models such as logistic regression. In addition to a regression specification, the mode…
Finite Mixtures of Covariance Structure Models with Regressors
Models of finite mixtures of normal densities conditional on regressor variables are specified and estimated. The authors consider mixtures of multivariate normals where the expected value for each component depends on nonnormal regressor variables. The expected values and covariance matrices of the mixture components are parameterized using conditional mean- and covariance-structures. The authors discuss the construction of the likelihood functi…
On Strategy for Methodological Analysis
Manski (1993) recommends a strategy for methodological analysis built on the notion that the top-down mathematical study of identification, not the more conventional bottom-up study of statistical models and inference, is the fundamental problem in the social sciences. He illustrates with identification analyses of four key methodological issues: (1) extrapolation (or prediction), (2) selection bias (or inference with missing data), (3) modeling …
Observational Residuals in Factor Analysis and Structural Equation Models
In the last decade there has been a surge of interest in the role of outliers and residuals in statistical analyses. However, there is a surprising neglect of these topics in factor analysis and in other structural equation models with latent variables. In this paper we propose ways to calculate unstandardized residuals, derive standardized residuals, suggest tests of statistical significance for residuals, and illustrate the procedures with empi…
Lineare Modelle zur Analyse von Paneldaten
Construction Principles for Latent Trait Models
Linear models in social science, psychlology, economics, and epidemiology are often formullated in latent continuous variables, which can be measured only with error or through two or more observed indicators. Henice, the latent variables are connected with the observed variables by a measurement model. If the observed indicators are metric, the covariance matrix of the observed variables is analyzed by using covariance structure models. Covarian…
Latent Variable Models of Dichotomous Data
This issue of Sociological Methods & Research contains four excellent illustrations of current methods for analyzing dichotomous data: dichotomous factor analysis (Muthén, 1989), latent trait analysis (Eaton et al., 1989), and grade of membership analysis (Woodbury and Manton, 1989). These methods are now sufficiently developed for use by researchers, though a lack of available software for the grade of membership model renders that method mostly…
The German Teaching Profession and Nazi Party Membership
Konrad H. Jarausch, Gerhard Arminger, The German Teaching Profession and Nazi Party Membership: A Demographic Logit Model, The Journal of Interdisciplinary History, Vol. 20, No. 2 (Autumn, 1989), pp. 197-225
Lincs
Miss
MISS is a computer program written in the GAUSS programming language for the microcomputer (with DOS operating system and mathcoprocessor). It provides several options for incomplete data sets. First, it will produce maximum likelihood estimates of the covariance matrix and mean vector via the EM algorithm. It will also generate a new data set with data substituted for the missing observations. This is analogous to computing factors scores in fac…
Making It Count Even More
Gerhard Arminger, George W. Bohrnstedt, Making It Count Even More: A Review and Critique of Stanley Lieberson's Making It Count: The Improvement of Social Theory and Research, Sociological Methodology, Vol. 17 (1987), pp. 363-372
Misspecification, Asymptotic Stability, and Ordinal Variables in the Analysis of Panel Data
When using panel data important problems are often conveniently overlooked. These include model misspecification, asymptotic stability, unequally spaced panel waves, and the use of ordinal rather than metric data. While panel data may be useful to eliminate specification error, if the process generating data is in equilibrium, the problems of misspecification persist if a model with a lagged endogenous variable is formulated. Furthermore, the not…
Quantitative Methoden in der Geschichtswissenschaft
A Farewell to Structural Analysis
Linear Stochastic Differential Equation Models for Panel Data with Unobserved Variables
Since Coleman (1968), sociologists have increasingly used differential equation models to analyze continuous dependent variables over time. Current applications of these models include, for example, Hummon, Doreian, and Teuter's (1975) analysis of control in organizations, Freeman and Hannan's (1975) model of organizational growth and decline, S6rensen's (1977) model of occupational mobility, Nielsen's (1980) analysis of the Flemish movement in B…
Platonic and Operational True Scores in Covariance Structure Analysis
Bielby (1986) argues that conventional practices for normalizing latent variable models can lead the applied researcher astray. He presents two examples to show how this may occur. In the first example, he considers the regression of income on education. In the second, he considers a panel model of attitude stability. He concludes that “explicit calibration of measurements” is as critical in sociological work as it is in the physical sciences. Th…
Multivariate Analyse von qualitativen abhängigen Variablen mit verallgemeinerten linearen Modellen
Die bisher verwendeten Modelle und Programme (ECTA, NONMET) zur Analyse von qualitativen abhängigen Variablen werden auf verallgemeinerte lineare Modelle zurückgefuhrt. Damit werden auch die Probleme der Einbeziehung von quantitativen unabhängigen Variablen sowie der Berechnung von Freiheitsgraden und der Schätzung von Parametern bei fehlenden Zellen auf einfache Weise gelöst
Methode, Statistik und Modell in den Sozialwissenschaften
The relationship between methods, statistics and models in the social sciences is discussed. New models generalizing commonly used linear models to deal with qualitative and ordinal data are introduced; their basic similarity to linear models is pointed out. Rate models and stochastic linear differential equations to model social processes in continuous time are mentioned. The implications of weak substantial theory and the correct use of statist…
Observational Residuals in Factor Analysis and Structural Equation Models
In the last decade there has been a surge of interest in the role of outliers and residuals in statistical analyses. However, there is a surprising neglect of these topics in factor analysis and in other structural equation models with latent variables. In this paper we propose ways to calculate unstandardized residuals, derive standardized residuals, suggest tests of statistical significance for residuals, and illustrate the procedures with empi…
Finite Mixtures of Covariance Structure Models with Regressors
Models of finite mixtures of normal densities conditional on regressor variables are specified and estimated. The authors consider mixtures of multivariate normals where the expected value for each component depends on nonnormal regressor variables. The expected values and covariance matrices of the mixture components are parameterized using conditional mean- and covariance-structures. The authors discuss the construction of the likelihood functi…
The German Teaching Profession and Nazi Party Membership
Konrad H. Jarausch, Gerhard Arminger, The German Teaching Profession and Nazi Party Membership: A Demographic Logit Model, The Journal of Interdisciplinary History, Vol. 20, No. 2 (Autumn, 1989), pp. 197-225
Misspecification, Asymptotic Stability, and Ordinal Variables in the Analysis of Panel Data
When using panel data important problems are often conveniently overlooked. These include model misspecification, asymptotic stability, unequally spaced panel waves, and the use of ordinal rather than metric data. While panel data may be useful to eliminate specification error, if the process generating data is in equilibrium, the problems of misspecification persist if a model with a lagged endogenous variable is formulated. Furthermore, the not…
Multivariate Analyse von qualitativen abhängigen Variablen mit verallgemeinerten linearen Modellen
Die bisher verwendeten Modelle und Programme (ECTA, NONMET) zur Analyse von qualitativen abhängigen Variablen werden auf verallgemeinerte lineare Modelle zurückgefuhrt. Damit werden auch die Probleme der Einbeziehung von quantitativen unabhängigen Variablen sowie der Berechnung von Freiheitsgraden und der Schätzung von Parametern bei fehlenden Zellen auf einfache Weise gelöst
Regression Analysis of Multivariate Binary Response Variables Using Rasch-Type Models and Finite-Mixture Methods
A model is considered for the regression analysis of multivariate binary data such as repeated-measures data (for example, panel data) or multiple-indicators with measures of some underlying characteristic such as attitude or ability (for example, surveys or tests). The model is related to the usual Rasch model, the usual latent-class model, and other familiar models such as logistic regression. In addition to a regression specification, the mode…
Linear Stochastic Differential Equation Models for Panel Data with Unobserved Variables
Since Coleman (1968), sociologists have increasingly used differential equation models to analyze continuous dependent variables over time. Current applications of these models include, for example, Hummon, Doreian, and Teuter's (1975) analysis of control in organizations, Freeman and Hannan's (1975) model of organizational growth and decline, S6rensen's (1977) model of occupational mobility, Nielsen's (1980) analysis of the Flemish movement in B…
Multivariate Analyse von qualitativen abhängigen Variablen mit verallgemeinerten linearen Modellen
Die bisher verwendeten Modelle und Programme (ECTA, NONMET) zur Analyse von qualitativen abhängigen Variablen werden auf verallgemeinerte lineare Modelle zurückgefuhrt. Damit werden auch die Probleme der Einbeziehung von quantitativen unabhängigen Variablen sowie der Berechnung von Freiheitsgraden und der Schätzung von Parametern bei fehlenden Zellen auf einfache Weise gelöst
Methode, Statistik und Modell in den Sozialwissenschaften
The relationship between methods, statistics and models in the social sciences is discussed. New models generalizing commonly used linear models to deal with qualitative and ordinal data are introduced; their basic similarity to linear models is pointed out. Rate models and stochastic linear differential equations to model social processes in continuous time are mentioned. The implications of weak substantial theory and the correct use of statist…
A Farewell to Structural Analysis
Linear Stochastic Differential Equation Models for Panel Data with Unobserved Variables
Since Coleman (1968), sociologists have increasingly used differential equation models to analyze continuous dependent variables over time. Current applications of these models include, for example, Hummon, Doreian, and Teuter's (1975) analysis of control in organizations, Freeman and Hannan's (1975) model of organizational growth and decline, S6rensen's (1977) model of occupational mobility, Nielsen's (1980) analysis of the Flemish movement in B…
Platonic and Operational True Scores in Covariance Structure Analysis
Bielby (1986) argues that conventional practices for normalizing latent variable models can lead the applied researcher astray. He presents two examples to show how this may occur. In the first example, he considers the regression of income on education. In the second, he considers a panel model of attitude stability. He concludes that “explicit calibration of measurements” is as critical in sociological work as it is in the physical sciences. Th…
Making It Count Even More
Gerhard Arminger, George W. Bohrnstedt, Making It Count Even More: A Review and Critique of Stanley Lieberson's Making It Count: The Improvement of Social Theory and Research, Sociological Methodology, Vol. 17 (1987), pp. 363-372
Misspecification, Asymptotic Stability, and Ordinal Variables in the Analysis of Panel Data
When using panel data important problems are often conveniently overlooked. These include model misspecification, asymptotic stability, unequally spaced panel waves, and the use of ordinal rather than metric data. While panel data may be useful to eliminate specification error, if the process generating data is in equilibrium, the problems of misspecification persist if a model with a lagged endogenous variable is formulated. Furthermore, the not…
Quantitative Methoden in der Geschichtswissenschaft
Lincs
Miss
MISS is a computer program written in the GAUSS programming language for the microcomputer (with DOS operating system and mathcoprocessor). It provides several options for incomplete data sets. First, it will produce maximum likelihood estimates of the covariance matrix and mean vector via the EM algorithm. It will also generate a new data set with data substituted for the missing observations. This is analogous to computing factors scores in fac…
Construction Principles for Latent Trait Models
Linear models in social science, psychlology, economics, and epidemiology are often formullated in latent continuous variables, which can be measured only with error or through two or more observed indicators. Henice, the latent variables are connected with the observed variables by a measurement model. If the observed indicators are metric, the covariance matrix of the observed variables is analyzed by using covariance structure models. Covarian…
Latent Variable Models of Dichotomous Data
This issue of Sociological Methods & Research contains four excellent illustrations of current methods for analyzing dichotomous data: dichotomous factor analysis (Muthén, 1989), latent trait analysis (Eaton et al., 1989), and grade of membership analysis (Woodbury and Manton, 1989). These methods are now sufficiently developed for use by researchers, though a lack of available software for the grade of membership model renders that method mostly…
The German Teaching Profession and Nazi Party Membership
Konrad H. Jarausch, Gerhard Arminger, The German Teaching Profession and Nazi Party Membership: A Demographic Logit Model, The Journal of Interdisciplinary History, Vol. 20, No. 2 (Autumn, 1989), pp. 197-225
Lineare Modelle zur Analyse von Paneldaten
Observational Residuals in Factor Analysis and Structural Equation Models
In the last decade there has been a surge of interest in the role of outliers and residuals in statistical analyses. However, there is a surprising neglect of these topics in factor analysis and in other structural equation models with latent variables. In this paper we propose ways to calculate unstandardized residuals, derive standardized residuals, suggest tests of statistical significance for residuals, and illustrate the procedures with empi…
On Strategy for Methodological Analysis
Manski (1993) recommends a strategy for methodological analysis built on the notion that the top-down mathematical study of identification, not the more conventional bottom-up study of statistical models and inference, is the fundamental problem in the social sciences. He illustrates with identification analyses of four key methodological issues: (1) extrapolation (or prediction), (2) selection bias (or inference with missing data), (3) modeling …
Finite Mixtures of Covariance Structure Models with Regressors
Models of finite mixtures of normal densities conditional on regressor variables are specified and estimated. The authors consider mixtures of multivariate normals where the expected value for each component depends on nonnormal regressor variables. The expected values and covariance matrices of the mixture components are parameterized using conditional mean- and covariance-structures. The authors discuss the construction of the likelihood functi…
Regression Analysis of Multivariate Binary Response Variables Using Rasch-Type Models and Finite-Mixture Methods
A model is considered for the regression analysis of multivariate binary data such as repeated-measures data (for example, panel data) or multiple-indicators with measures of some underlying characteristic such as attitude or ability (for example, surveys or tests). The model is related to the usual Rasch model, the usual latent-class model, and other familiar models such as logistic regression. In addition to a regression specification, the mode…
Handbook of Statistical Modeling for the Social and Behavioral Sciences
Mathematics (13 obras) · Computer Science (11 obras) · Econometrics (11 obras) · Statistics (11 obras) · Advanced Statistical Methods and Models (5 obras) · Statistical Methods and Bayesian Inference (5 obras) · Advanced Statistical Modeling Techniques (4 obras) · Data science (4 obras) · Economics (4 obras) · Latent variable (4 obras)