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Castro-Schilo, Laura; Ferrer, Emilio – Multivariate Behavioral Research, 2013
We illustrate the idiographic/nomothetic debate by comparing 3 approaches to using daily self-report data on affect for predicting relationship quality and breakup. The 3 approaches included (a) the first day in the series of daily data; (b) the mean and variability of the daily series; and (c) parameters from dynamic factor analysis, a…
Descriptors: Factor Analysis, Prediction, Group Behavior, Collectivism
Lorenzo-Seva, Urbano; Timmerman, Marieke E.; Kiers, Henk A. L. – Multivariate Behavioral Research, 2011
A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…
Descriptors: Simulation, Research Methodology, Factor Analysis, Item Response Theory
Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong – Multivariate Behavioral Research, 2010
This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…
Descriptors: Intervals, Sample Size, Factor Analysis, Least Squares Statistics
Jamshidian, Mortaza; Mata, Matthew – Multivariate Behavioral Research, 2008
Incomplete or missing data is a common problem in almost all areas of empirical research. It is well known that simple and ad hoc methods such as complete case analysis or mean imputation can lead to biased and/or inefficient estimates. The method of maximum likelihood works well; however, when the missing data mechanism is not one of missing…
Descriptors: Structural Equation Models, Simulation, Factor Analysis, Research Methodology
Davison, Mark L.; Kim, Se-Kang; Close, Catherine – Multivariate Behavioral Research, 2009
A profile is a vector of scores for one examinee. The mean score in the vector can be interpreted as a measure of overall profile height, the variance can be interpreted as a measure of within person variation, and the ipsatized vector of score deviations about the mean can be said to describe the pattern in the score profile. A within person…
Descriptors: Vocational Interests, Interest Inventories, Profiles, Scores
de Winter, J. C. F.; Dodou, D.; Wieringa, P. A. – Multivariate Behavioral Research, 2009
Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…
Descriptors: Sample Size, Factor Analysis, Enrollment, Evaluation Methods

Krzanowski, Wojtek J.; Kline, Paul – Multivariate Behavioral Research, 1995
A cross-validation method is described for selecting the significant components from a principal components analysis, and properties of the method are discussed. Parallels are drawn with other related methods in covariance structure modeling, and some comparisons among methods are illustrated with two data sets previously analyzed. (SLD)
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Selection

Maraun, Michael D.; And Others – Multivariate Behavioral Research, 1996
The issue of indeterminacy in factor analysis and the debate between the proposed alternative solution and posterior moment position are explored in an article and 14 commentaries and rebuttals in two rounds. Implications for applied work involving factor analysis are discussed. (SLD)
Descriptors: Factor Analysis, Factor Structure, Mathematical Models, Metaphors

Trendafilov, Nickolay T. – Multivariate Behavioral Research, 1994
An alternative to the PROMAX exploratory method is presented for constructing a target matrix in Procrustean rotation in factor analysis. A technique is proposed based on vector majorization. The approach is illustrated with several standard numerical examples. (SLD)
Descriptors: Equations (Mathematics), Factor Analysis, Factor Structure, Matrices

Jackson, Douglas N. – Multivariate Behavioral Research, 1975
A method is proposed for the evaluation of the degree to which trait measures show stability across diverse methods of measurement. The technique is illustrated using multitrait-multimethod matrices from personality assessment, which yield trait-specific factors. (Author/BJG)
Descriptors: Factor Analysis, Matrices, Measurement Techniques, Orthogonal Rotation

Marsh, Herbert W. – Multivariate Behavioral Research, 1987
Study examined the factorial invariance of responses by preadolescent males and females to a multidimensional self-concept instrument. Also demonstrated how confirmatory factor analysis is used to test factorial invariance and examined problems with its use and interpretation. (RB)
Descriptors: Factor Analysis, Methods Research, Research Methodology, Self Concept Measures

Roskam, Edward E.; And Others – Multivariate Behavioral Research, 1992
First- and second-round commentaries on an article by L. Guttman are presented. The following authors responded, with two articles each: (1) E. E. Roskam and J. Ellis; (2) P. H. Schonemann; (3) A. R. Jensen; (4) J. C. Loehlin; and (5) J.-E. Gustafsson. (SLD)
Descriptors: Factor Analysis, Groups, Intelligence, Mathematical Models
Component Analysis versus Common Factor Analysis: Some Issues in Selecting an Appropriate Procedure.

Velicer, Wayne F.; Jackson, Douglas N. – Multivariate Behavioral Research, 1990
Situations for which the researcher should use component analysis versus common factor analysis are discussed. Topics addressed include key algebraic similarities and differences, theoretical and practical issues, the factor indeterminacy issue, latent versus manifest variables, and differences between exploratory and confirmatory analysis…
Descriptors: Algebra, Comparative Analysis, Factor Analysis, Literature Reviews

Marsh, Herbert W.; Richards, Gary E. – Multivariate Behavioral Research, 1987
The factorial structure of the Rotter Internal-External (IE) scale was examined. While there was strong evidence against the unidimensionality of the Rotter scale, the findings suggested that the first-order factors do define a single higher-order construct that may represent the generalized IE construct. (Author/LMO)
Descriptors: Construct Validity, Factor Analysis, Factor Structure, Goodness of Fit

Guttman, Louis – Multivariate Behavioral Research, 1992
Argues that Jensen's article contains an inaccurate and misleading account of Spearman's work and distorts the basic concepts of factor analysis. The target article has failed in all its main objectives; its major failing is a result of the irrelevance of factor analysis to the study of group differences. (SLD)
Descriptors: Blacks, Equations (Mathematics), Factor Analysis, Groups
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