Pere J. Ferrando

FACTOR: A computer program to fit the exploratory factor analysis model

Exploratory factor analysis (EFA) is one of the most widely used statistical procedures in psychological research. It is a classic technique, but statistical research into EFA is still quite active, and various new developments and methods have been presented in recent years. The authors of the most popular statistical packages, however, do not seem very interested in incorporating these new advances. We present the program FACTOR, which was designed as a general, user-friendly program for computing EFA. It implements traditional procedures and indices and incorporates the benefits of some more recent developments. Two of the traditional procedures implemented are polychoric correlations and parallel analysis, the latter of which is considered to be one of the best methods for determining the number of factors or components to be retained. Good examples of the most recent developments implemented in our program are (1) minimum rank factor analysis, which is the only factor method that allows one to compute the proportion of variance explained by each factor, and (2) the simplimax rotation method, which has proved to be the most powerful rotation method available. Of these methods, only polychoric correlations are available in some commercial programs. A copy of the software, a demo, and a short manual can be obtained free of charge from the first author.

The construct of sensation seeking as measured by Zuckerman's SSS-V and Arnett's AISS: a structural equation model

The degree of equivalence between the dimension of sensation seeking as measured by Zuckermans SSS form V and Arnetts AISS is assessed using a structural equation model. The structure of the Spanish translation of both instruments is first assessed at the item level using factor analytic procedures. In both cases the structures agree reasonably with those proposed from the theory and, furthermore, the psychometric properties of the Spanish translations are similar to those of the original instruments. Results of the structural equation model suggest that both instruments are essentially measuring the same dimension.

Two SPSS programs for interpreting multiple regression results.

When multiple regression is used in explanation-oriented designs, it is very important to determine both the usefulness of the predictor variables and their relative importance. Standardized regression coefficients are routinely provided by commercial programs. However, they generally function rather poorly as indicators of relative importance, especially in the presence of substantially correlated predictors. We provide two user-friendly SPSS programs that implement currently recommended techniques and recent developments for assessing the relevance of the predictors. The programs also allow the user to take into account the effects of measurement error. The first program, MIMR-Corr.sps, uses a correlation matrix as input, whereas the second program, MIMR-Raw.sps, uses the raw data and computes bootstrap confidence intervals of different statistics. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from http:// brm.psychonomic-journals.org/content/supplemental.

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

IRT-related factor analytic procedures for testing the equivalence of paper-and-pencil and Internet-administered questionnaires.

This article describes a general item response theory-based factor analytic procedure that allows assessment of the equivalence between 2 administrative modes of a questionnaire: paper and pencil, and Internet based. The theoretical relations between the present procedure and other methods used in previous empirical research are shown, and the advantages of the procedure are discussed. An empirical application based on 2 personality questionnaires is given, and the results are compared with the results of using traditional procedures for assessing equivalence. The substantive implications of the results, as well as suggestions for further research and methodology, are discussed.

An Item Response Theory Model for Incorporating Response Time Data in Binary Personality Items

This article describes a general item response theory model for personality items that allows the information provided by the item response times to be used to estimate the individual trait levels. The submodel describing the item response times is a modification of Thissens log-linear model and is based on the distance-difficulty hypothesis in personality measurement. First, the procedures for fitting the model and assessing the goodness of fit are described. Second, the gain in the precision of estimating the individual trait levels when the information provided by the response times is used is assessed. Finally, all the developments in this article are illustrated by means of an empirical example.

Detecting Dissimulation in Personality Test Scores: A Comparison between Person-Fit Indices and Detection Scales

The present study examined whether an internal procedure for assessing the scalability of the response patterns, based on item response theory (IRT), can detect deliberate dissimulation (faking good) in the Extraversion, Neuroticism, and Psychoticism scale scores of the Eysenck Personality Questionnaire Revised. The procedure is compared to the traditional approaches, which use the Lie and the Social Desirability (SD) scales. A data set was analyzed in which participants were either administered the measures in standard conditions or given special instructions to fake good. The results showed that the IRT-based measures were not powerful enough to detect dissimulation, whereas the Lie and SD scales performed much better.

Person Reliability in Personality Measurement: An Item Response Theory Analysis

This article discusses the rationale of an item response theory (IRT) model, based on Thurstone scaling, for personality measurement and suggests procedures for (a) estimating the location and slope parameters of the person response curve (PRC), (b) assessing the precision of the estimates, and (c) assessing the model-data fit. The relations between the PRC parameters and the l0 and lz person-fit measures are also discussed. The procedures described and the relations discussed are illustrated using empirical data.

Acquiescence as a source of bias and model and person misfit: A theoretical and empirical analysis

In personality and attitude measurement, the presence of acquiescent responding can have an impact on the whole process of item calibration and test scoring, and this can occur even when sensible procedures for controlling acquiescence are used. This paper considers a bidimensional (content acquiescence) factor-analytic model to be the correct model, and assesses the effects of fitting unidimensional models to theoretically unidimensional scales when acquiescence is in fact operating. The analysis considers two types of scales: non-balanced and fully balanced. The effects are analysed at both the calibration and the scoring stages, and are of two types: bias in the item/respondent parameter estimates and model/person misfit. The results obtained theoretically are checked and assessed by means of simulation. The results and predictions are then assessed in an empirical study based on two personality scales. The implications of the results for applied personality research are discussed.

Factorial structure of the revised children manifest anxiety scale in a Spanish sample: Relations with Eysenck personality dimensions

Abstract A Spanish translation of the Revised Children Manifest Anxiety Scale (RCMAS) was administered to 1576 students, with an age range of 9–12 years, from a Spanish elementary school. The factor analysis under a 5-factor model gave a structure similar to that obtained in the U.S. version. Relations between the RCMAS and the Extraversion and Neuroticism Junior Eysenck Personality Questionnaire scales were investigated by means of a canonical correlation analysis. As expected, the three anxiety subscales correlated highly and significantly with the Neuroticism scale and lower and negatively with Extraversion.