Karl G. Jöreskog

• PhD
• Professor (Full) at Uppsala University

This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regress...

We conducted confirmatory factor analysis (CFA) of responses (N=803) to a self-reported measure of optimism, using full-information estimation via adaptive quadrature (AQ), an alternative estimation method for ordinal data. We evaluated AQ results in terms of the number of iterations required to achieve convergence, model fit, parameter estimates,...

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A pairwise maximum likelihood (PML) estimation method is developed for factor analysis models with ordinal data and fitted both in an exploratory and confirmatory set-up. The performance of the method is studied via simulations and comparisons with full information maximum likelihood (FIML) and three-stage limited information estimation methods, na...

Winning medals at the Olympic Games has become an objective that countries worldwide want to achieve. In line with research devoted to the predictors of success, the present article examines the connection between certain welfare characteristics (political, social, and economic development) and the probability of success in the 1984 and 2004 Olympi...

Various statistical models for simplex structures are formulated in terms of the well-known Wiener and Markov stochastic processes. A distinction is made between a perfect simplex and a quasi-simplex. For each model the problems of identification and estimation of the parameters and that of testing the goodness of fit of the model are considered. A...

Scores on 12 aptitude and achievement tests for 11,743 subjects, subdivided into four groups according to intelligence and socioeconomic status, were used. A technique, developed by Jöreskog, for simultaneously factor analysing data from several populations was used to determine whether there was factorial invariance over the four groups. A model,...

Until recently the main difficulty in the use of maximum-likelihood estimation in factor analysis has been the lack of satisfactory methods of obtaining numerical solutions. This defect has now been remedied, and this paper describes new rapid methods of finding maximum-likelihood estimates.

The Satorra Bentler (SB) and the Browne ADF chi-square statistics are used for testing structural equation models with non-normal data. The relationships between the SB and ADF statistics and kurtosis are developed and it is shown that the weighted deviations of the "population" true second-order moments and the fitted second-order moments for thes...

Ordinal variables are common in many empirical investigations in the social and behavioral sciences. Researchers often apply the maximum likelihood method to fit structural equation models to ordinal data. This assumes that the observed measures have normal distributions, which is not the case when the variables are ordinal. A better approach is to...

Theory and methodology for exploratory factor analysis have been well developed for continuous variables. In practice, observed or measured variables are often ordinal. However, ordinality is most often ignored and numbers such as 1, 2, 3, 4, representing ordered categories, are treated as numbers having metric properties, a procedure which is inco...

Editor's introduction In longitudinal research we need computer programs to handle the complex statistical models necessary for the analysis of the longitudinal data. Based on the central features of the design of a longitudinal project, meaning that the same or similar measurements are obtained from the same people on two or more occasions, and in...

A general theory for parametric inference in contingency tables is outlined. Estimation of polychoric correlations is seen as a special case of this theory. The asymptotic covariance matrix of the estimated polychoric correlations is derived for the case when the thresholds are estimated from the univariate marginals and the polychoric correlations...

This graduate-level text aims to introduce students of the natural sciences to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own. A thoroughly updated and expanded version of the authors' successful textbook on geological factor analysis, this book draws on exam...

Constrained optimization recently has been implemented in the LISREL software package, allowing formulation of parent-offspring transmission models in a simple and efficient manner. A reverse path model of parental transmission is described within the LISREL framework for application to twin and/or adoptive family data. The model incorporates genet...

Two programs will be described: PRELIS and LISREL 7. PRELIS is a program for multivariate data screening and data summarization and a preprocessor for LISREL. LISREL 7 is an extension of LISREL 6. Among the new features of LISREL 7 is its ability to produce correct asymptotic chisquare goodness-of-fit measures and standard errors of parameter estim...

Reviews the book, Structural Modeling by Example: Applications in Educational, Sociological, and Behavioral Research edited by Peter Cuttance and Russell Ecob (see record 1988-98021-000 ). The objective of this book is to provide extensive examples of how a number of contributors worked through an applied problem. If the objective of this book is t...

Political efficacy is considered to be one of the most important attitudes in theories of political participation and democratic politics. It has been assumed that political efficacy is a stable, persistent orientation rather than a transient attitude. Several studies have examined the stability of political efficacy over time. In most of these stu...

reviews most of the important models and techniques for analysis of covariance structures and illustrates them with a few simple examples types of covariance structures / variance and covariance components / measurement models / path analysis models / simplex models general approaches to analysis of covariance structures / general covariance an...

A large-scale simulation design was used to study the sensitivity of maximum likelihood (ML) factor analysis to violations of measurement scale and distributional assumptions in the input data. Product-moment, polychoric, Spearman's rho, and Kendall's tau-b correlations computed from ordinal data were used to estimate a single-factor model. The res...

A large-scale simulation design was used to study the sensitivity of maximum likelihood (ML) factor analysis to violations of measurement scale and distributional assumptions in the input data. Product-moment, polychoric. Spearman's rho, and Kendall's tau-b correlations computed from ordinal data were used to estimate a single-factor model. The res...

A number of different research designs for data collection, analysis, and interpretation has been proposed for the study of developmental change (see e.g., Baltes, 1968; Schaie, 1965, 1977; Schaie and Baltes, 1975). In Schaie’s (1965) general developmental model, the individual’s psychological response under study may be characterized by the cohort...

In our paper we proposed a general methodology for analyzing longitudinal data from several cohorts. This methodology is general and flexible and can accommodate many different models for this kind of data. The main purpose of the proposed methodology is to find a model which takes the intrinsic strueture of the data collection design into account...

Selectivity problems can occur whenever one tries to estimate population parameters from a nonrandom sample. The sample may be nonrandom because only individuals with certain characteristics are selected into the sample (sample selection), or because individuals participate voluntarily in the sample (self-selection). Selective samples can also occu...

The authors describe new developments in structural equation modeling as incorporated in LISREL V. The procedures are illustrated on data from three previous studies.

The characteristic feature of a longitudinal research design is that the same measurements are obtained from the same people at two or more occasions. The purpose of a longitudinal or panel study is to assess the changes that occur between occasions and to attribute these changes to certain background characteristics and events existing or occurrin...

A procedure for estimating the reliability of a factorially complex composite is considered.

Jöreskog's (1970a) procedure for the analysis of simplex models was used to test Humphreys' (1968) assertion that eight semesters of undergraduate grade-point averages have a simplex form. Not only was this assertion confirmed but precise estimates of reliability and of unattenuated correlations were obtained.

A general approach to the analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed. Seve...

The psychometric application of Jöreskog's (Note 1) procedure for simultaneous factor analysis in several populations is illustrated. Using Scholastic Aptitude Test data from two samples, procedures are shown for checking test construction assumptions about units of measurement and error variance, within and between samples.

A simplex model is presented for the analysis of longitudinal academic growth variables in which only one measure is obtained at each time. When this model fits the observed data, then reliabilities and unattenuated correlations can be estimated except for the first and last periods.

A procedure is presented for the analysis of rating data with correlated intrajudge and uncorrelated interjudge measurement errors. Correlations between true scores on different rating dimensions, reliabilities for each judge on each dimension and correlations between intrajudge errors can be estimated given a minimum of three raters and two dimens...

We consider a model in which one observes multiple indicators and multiple causes of a single latent variable. In terms of the multivariate regression of the indicators on the causes, the model implies restrictions of two types: (i) the regression coefficient matrix has rank one, (ii) the residual variance-covariance matrix satisfies a factor analy...

Intraclass correlation reliablity estimates are based on the assumption that the various measures are equivalent. Jöreskog's (1970) general model for the analysis of covariance structures can be used to test the validity of this assumption.

The logical structure of the Campbell and Fiske (1959) multitrait-multimethod approach is applied to the problem of studying growth and its determinants. The resulting model is a special case of Jöreskog's (1970a) general model for the analysis of covariance structures. The relationships of traditional psychometric formulations to this model are de...

Aitken's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are seale free and asymptotically efficient. The estimates are computed by a rapidly convergin...

To resolve a recent controversy between Klein and Cleary and Levy, a model for dichotomous congeneric items is presented which has mean errors of zero, dichotomous true scores that are uncorrelated with errors, and errors that are mutually uncorrelated.

Various models for sets of congeneric tests are considered, including models appropriate for the analysis of multitrait-multimethod data. All models are illustrated with real data. The special cases when two or more tests within a set are tau-equivalent or parallel are also considered. All data analyses are done within the framework of a general mo...

This paper is concerned with the study of similarities and differences in factor structures between different groups. A common situation occurs when a battery of tests has been administered to samples of examinees from several populations. A very general model is presented, in which any parameter in the factor analysis models (factor loadings, fact...

A general method for estimating the unknown coefficients in a set of linear structural equations is described. In its most general form the method allows for both errors in equations (residuals, disturbances) and errors in variables (errors of measurement, observational errors) and yields estimates of the residual variance-covariance matrix and the...

Scores on 12 aptitude and achievement tests for 11, 743 subjects, subdivided into four groups according to intelligence and socioeconomic status, were used. A technique, developed by Jöreskog, for simultaneously factor analyzing data from several populations was used to determine whether there was factorial invariance over the four groups. A model,...

SUMMARY It is assumed that observations on a set of variables have a multivariate normal distribution with a general parametric form of the mean vector and the variance-covariance matrix. Any parameter of the model may be fixed, free or constrained to be equal to other parameters. The free and constrained parameters are estimated by maximum likelih...

It is assumed that observations on a set of variables have a multivariate normal distribution with a general parametric form of the mean vector and the variance-covariance matrix. Any parameter of the model may be fixed, free or constrained to be equal to other parameters. The free and constrained parameters are estimated by maximum likelihood. A w...