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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
Giordano, Bruno L.; Guastavino, Catherine; Murphy, Emma; Ogg, Mattson; Smith, Bennett K.; McAdams, Stephen – Multivariate Behavioral Research, 2011
Sorting procedures are frequently adopted as an alternative to dissimilarity ratings to measure the dissimilarity of large sets of stimuli in a comparatively short time. However, systematic empirical research on the consequences of this experiment-design choice is lacking. We carried out a behavioral experiment to assess the extent to which…
Descriptors: Auditory Stimuli, Acoustics, Data Collection, Research Methodology
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
Li, Libo; Hser, Yih-Ing – Multivariate Behavioral Research, 2011
In this article, we directly question the common practice in growth mixture model (GMM) applications that exclusively rely on the fitting model without covariates for GMM class enumeration. We provide theoretical and simulation evidence to demonstrate that exclusion of covariates from GMM class enumeration could be problematic in many cases. Based…
Descriptors: Evidence, Risk, Goodness of Fit, Adolescents
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
Van Landeghem, Georges; De Fraine, Bieke; Van Damme, Jan – Multivariate Behavioral Research, 2005
This short contribution is a comment on M. Moerbeek's exploration of consequences of ignoring a level of clustering in a multilevel model, which was published in the first issue of the 2004 volume of Multivariate Behavioral Research. After having recapitulated the framework and extended the results of Moerbeek's study, we formulate two critical…
Descriptors: Multivariate Analysis, Behavioral Science Research, Models, Research Methodology

Wiley, James B.; And Others – Multivariate Behavioral Research, 1984
The advantages and disadvantages of balanced incomplete block designs are clarified and their use is demonstrated with an empirical example. A procedure for reducing data of this type to analyzable form is proposed, and an analytical approach that is appropriate for the resulting data is illustrated. (Author/BW)
Descriptors: Behavioral Science Research, Data Analysis, Data Collection, Research Design

Lambert, Zarrel V.; And Others – Multivariate Behavioral Research, 1991
A method is presented that eliminates some interpretational limitations arising from assumptions implicit in the use of arbitrary rules of thumb to interpret exploratory factor analytic results. The bootstrap method is presented as a way of approximating sampling distributions of estimated factor loadings. Simulated datasets illustrate the…
Descriptors: Behavioral Science Research, Computer Simulation, Estimation (Mathematics), Factor Structure

Huberty, Carl J.; DiStefano, Christine; Kamphaus, Randy W. – Multivariate Behavioral Research, 1997
How a cluster analysis is conducted, validated, and interpreted is illustrated using a 14-scale behavioral assessment instrument and a national sample of 1,228 elementary school students. Method, cluster typology, validity, cluster structure, and prediction of cluster membership are discussed. (Author/SLD)
Descriptors: Behavior Rating Scales, Behavioral Science Research, Cluster Analysis, Elementary Education
Mills, Jamie, D.; Olejnik, Stephen, F.; Marcoulides, George, A. – Multivariate Behavioral Research, 2005
The effectiveness of the Tabu variable selection algorithm, to identify predictor variables related to a criterion variable, is compared with the stepwise variable selection method and the all possible regression approach. Considering results obtained from previous research, Tabu is more successful in identifying relevant variables than the…
Descriptors: Predictor Variables, Multiple Regression Analysis, Behavioral Science Research, Evaluation Criteria

Wiggins, Jerry S. – Multivariate Behavioral Research, 1984
This overview of the field of personality theory evaluates the important features of Raymond Cattell's work. While there are many areas of agreement between Cattell and other personality theorists, his rejection of traditional clinical methods for measurement and experimentation has created controversy as well as an extraordinarily rich…
Descriptors: Behavior Theories, Behavioral Science Research, Clinical Psychology, Experimental Psychology

Loehlin, John C. – Multivariate Behavioral Research, 1984
Raymond Cattell's efforts to sort out the relationships of genetic or environmental patterns to personality factors have contributed to behavior genetics. Early writings on the projected decline of intelligence in Britain, studies using Multivariate Abstract Variance Analysis, and other miscellaneous studies on personality factors and mental…
Descriptors: Behavioral Science Research, Experimenter Characteristics, Genetics, Heredity

Cattell, Raymond B. – Multivariate Behavioral Research, 1984
In this overview of his research in personality theory, Cattell describes the play of people, situations, and, ideas enacted over 30 years in his University of Illinois laboratory. Establishing meaningful empirical measurement methods was the foundation for further research into many aspects of personality development. (BS)
Descriptors: Affective Behavior, Autobiographies, Behavior Theories, Behavioral Science Research