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261
Investigating population heterogeneity with factor mixture models
- Psychological Methods
, 2005
"... Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data analyzed with methods for multiple groups. If the sources of population heterogeneity are unobserved, the data can be analyzed ..."
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Cited by 73 (4 self)
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Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data analyzed with methods for multiple groups. If the sources of population heterogeneity are unobserved, the data can be analyzed with latent class models. Factor mixture models are a combination of latent class and common factor models and can be used to explore unobserved population heterogeneity. Observed sources of heterogeneity can be included as covariates. The different ways to incorporate covariates correspond to different conceptual interpretations. These are discussed in detail. Characteristics of factor mixture modeling are described in comparison to other methods designed for data stemming from heterogeneous populations. A step-by-step analysis of a subset of data from the Longitudinal Survey of American Youth illustrates how factor mixture models can be applied in an exploratory fashion to data collected at a single time point. The populations investigated in the behavioral sciences and related fields of research are often heterogeneous. A sample may consist of explicitly defined groups such as experimental and control groups, and the aim is to compare these groups. On the other hand, the sources of population heterogeneity may not be known beforehand. Test scores on a cognitive test may reflect two types of children in the sample: those who master the knowledge required to solve the items (masters) and those who lack this critical knowledge (nonmasters). The interest may be to decide to which of the subpopulations a given child most likely belongs. In addition, it may be of interest to characterize masters and nonmasters using background variables to develop specific
Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling
- Journal of Cross-Cultural Psychology
, 2000
"... Extreme response styles (ERS) and acquiescence response styles (ARS) may constitute important sources of cross-cultural differences on survey-type instruments. Differences in ERS and ARS, if undetected, may give rise to spurious results that do not reflect genu-ine differences in attitudes or percep ..."
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Cited by 67 (0 self)
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Extreme response styles (ERS) and acquiescence response styles (ARS) may constitute important sources of cross-cultural differences on survey-type instruments. Differences in ERS and ARS, if undetected, may give rise to spurious results that do not reflect genu-ine differences in attitudes or perceptions. Multiple-group confirmatory factor analysis is recommended as the most effective method of testing for ERS and ARS and determin-ing whether cultural groups can be meaningfully compared on the basis of factor (latent) means. A detailed numerical example is provided.
Factor analysis and scale revision
- Psychological Assessment
, 2000
"... This article reviews methodological issues that arise in the application of exploratory factor analysis (EFA) to scale revision and refinement. The authors begin by discussing how the appropriate use of EFA in scale revision is influenced by both the hierarchical nature of psychological constructs a ..."
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Cited by 58 (0 self)
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This article reviews methodological issues that arise in the application of exploratory factor analysis (EFA) to scale revision and refinement. The authors begin by discussing how the appropriate use of EFA in scale revision is influenced by both the hierarchical nature of psychological constructs and the motivations underlying the revision. Then they specifically address (a) important issues that arise prior to data collection (e.g., selecting an appropriate sample), (b) technical aspects of factor analysis (e.g., determining the number of factors to retain), and (c) procedures used to evaluate the outcome of the scale revision (e.g., determining whether the new measure functions equivalently for different populations). Personality measurement by self-report questionnaire is a thriv-ing enterprise of critical importance to theory development and testing in many psychological disciplines such as clinical psychol-ogy. At least three journals focus on statistical analyses of ques-tionnaire data: Psychological Assessment, Journal of Personality Assessment, and Assessment. Many of the articles in these journals use exploratory factor analysis (EFA) and, oftentimes, the factor analytic findings are used to guide scale revision. In this article, we
Exploratory and confirmatory factor analysis: guidelines, issues, and alternatives
- Journal of Organizational Behavior
, 1997
"... ‘Most uses of ‘‘confirmatory’ ’ factor analyses are, in actuality, partly exploratory and partly confirmatory in that the resultant model is derived in part from theory and in part from a respecification based on the analysis of model fit.’ ..."
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Cited by 53 (0 self)
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‘Most uses of ‘‘confirmatory’ ’ factor analyses are, in actuality, partly exploratory and partly confirmatory in that the resultant model is derived in part from theory and in part from a respecification based on the analysis of model fit.’
Measurement Equivalence: A Comparison of Methods Based on Confirmatory Factor Analysis and Item Response Theory
- Journal of Applied Psychology
, 2002
"... Current interest in the assessment of measurement equivalence emphasizes 2 major methods of analysis. The authors offer a comparison of a linear method (confirmatory factor analysis) and a nonlinear method (differential item and test functioning using item response theory) with an emphasis on their ..."
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Cited by 38 (0 self)
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Current interest in the assessment of measurement equivalence emphasizes 2 major methods of analysis. The authors offer a comparison of a linear method (confirmatory factor analysis) and a nonlinear method (differential item and test functioning using item response theory) with an emphasis on their method-ological similarities and differences. The 2 approaches test for the equality of true scores (or expected raw scores) across 2 populations when the latent (or factor) score is held constant. Both approaches can provide information about when measurement nonequivalence exists and the extent to which it is a problem. An empirical example is used to illustrate the 2 approaches. There is currently a great deal of interest in the assessment of measurement equivalence. According to Drasgow and Kanfer (1985), a test or a subscale is said to have measurement equiva-lence across groups or populations if persons with identical scores on the underlying/latent construct have the same expected raw score or true score at the item level, the subscale total score level, or both. Without measurement equivalence, it is difficult to inter-pret observed mean score differences meaningfully. That is, ob-
Radical Innovation Across Nations: The Preeminence of Corporate Culture
"... Radical innovation is an important driver of the growth, success, and wealth of firms and nations. Because of its importance, authors across various disciplines have proposed many theories about the drivers of such innovation, including government policy and labor, capital, and culture at the nation ..."
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Cited by 29 (0 self)
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Radical innovation is an important driver of the growth, success, and wealth of firms and nations. Because of its importance, authors across various disciplines have proposed many theories about the drivers of such innovation, including government policy and labor, capital, and culture at the national level. The authors contrast these theories with one based on the corporate culture of the firm. They test their theory using survey and archival data from 759 firms across 17 major economies of the world. The results suggest the following: First, among the factors studied, corporate culture is the strongest driver of radical innovation across nations; culture consists of three attitudes and three practices. Second, the commercialization of radical innovations translates into a firm’s financial performance; it is a stronger predictor of financial performance than other popular measures, such as patents. The authors discuss the implications of these findings for research and practice.
Self-construal scales lack validity
- Human Communication Research
, 2003
"... Self-construal is thought to mediate and explain the effects of culture on a wide variety of outcome variables. A meta-analysis of published cross-cultural self-construal research is re-ported in this article, and the results across studies suggests that the evidence for the pre-dicted cultural diff ..."
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Cited by 27 (2 self)
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Self-construal is thought to mediate and explain the effects of culture on a wide variety of outcome variables. A meta-analysis of published cross-cultural self-construal research is re-ported in this article, and the results across studies suggests that the evidence for the pre-dicted cultural differences is weak, inconsistent, or nonexistent. The results of 3 priming experiments (N = 121, N = 99, and N = 361) suggest that (a) priming does not account for the inconsistent results observed in the meta-analysis, (b) that scores on a self-construal scale appear to be measuring trait-like constructs that are not sensitive to priming, and (c) that measures of self-construals lack convergent validity. The results of several measurement studies
Investigating Spearman’s hypothesis by means of multi-group confirmatory factor analysis
- Multivariate Behavioral Research
, 2000
"... Differences between blacks and whites on cognitive ability tests have been attributed to a fundamental difference between these groups in general intelligence (or g, as it is denoted). The hypothesized difference in g gives rise to Spearman’s hypothesis, which states that the differences in the mean ..."
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Cited by 23 (8 self)
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Differences between blacks and whites on cognitive ability tests have been attributed to a fundamental difference between these groups in general intelligence (or g, as it is denoted). The hypothesized difference in g gives rise to Spearman’s hypothesis, which states that the differences in the means of the tests are related to the tests ’ factor loadings on g. Jensen has investigated this hypothesis by correlating differences in means and tests ’ g loadings. The aim of the present article is to investigate B-W differences using multi-group confirmatory factor analysis. The advantages of multi-group confirmatory factor analysis over Jensen’s test of Spearman’s hypothesis are discussed. A published data set is analyzed. Strict factorial invariance is tested and judged to be tenable. Various models are tested, which do and do not incorporate g. It is observed that it is difficult to distinguish between several hypotheses, including and excluding g, concerning group differences. The inability to distinguish between competing models using multi-group confirmatory factor analysis makes it difficult to draw clear conclusions about the exact nature of black-white differences in cognitive abilities. The implications of the results for Jensen’s test of Spearman’s hypothesis are discussed.
Confirmatory factor analysis of the Penn State Worry Questionnaire: Multiple factors or method effects?
, 2003
"... The latent structure of the Penn State Worry Questionnaire (PSWQ) was evaluated with confirmatory factor analyses (CFAs) in 1200 outpatients with DSM-IV anxiety and mood disorders. Of particular interest was the comparative fit and interpretability of a two-factor solution (cf. Behaviour Research an ..."
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Cited by 20 (1 self)
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The latent structure of the Penn State Worry Questionnaire (PSWQ) was evaluated with confirmatory factor analyses (CFAs) in 1200 outpatients with DSM-IV anxiety and mood disorders. Of particular interest was the comparative fit and interpretability of a two-factor solution (cf. Behaviour Research and Therapy 40 (2002) 313) vs. a one-factor model that specified method effects arising from five reverse-worded items. Consistent with prediction, the superiority of the one-factor model was demonstrated in split-sample CFA replications (ns = 600). Multiple-group CFAs indicated that the measurement properties of the PSWQ were invariant in male and female patients. In addition to their direct relevance to the psychometrics of the PSWQ, the results are discussed in regard to methodological considerations for using factor analytic methods in the evaluation of psychological tests.
A new look at the Big Five factor structure through exploratory structural equation modeling. Psychological Assessment
- Substance and artifact in the higher-order factors of the Big Five. Journal of Personality and Social Psychology, 95, 442–455. doi:10.1037/0022-3514.95.2.442 McGrew, K. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulder
, 2010
"... NEO instruments are widely used to assess Big Five personality factors, but confirmatory factor analyses (CFAs) conducted at the item level do not support their a priori structure due, in part, to the overly restrictive CFA assumptions. We demonstrate that exploratory structural equation modeling (E ..."
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Cited by 18 (0 self)
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NEO instruments are widely used to assess Big Five personality factors, but confirmatory factor analyses (CFAs) conducted at the item level do not support their a priori structure due, in part, to the overly restrictive CFA assumptions. We demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory factor analysis (EFA), overcomes these problems with responses (N � 3,390) to the 60-item NEO–Five-Factor Inventory: (a) ESEM fits the data better and results in substantially more differentiated (less correlated) factors than does CFA; (b) tests of gender invariance with the 13-model ESEM taxonomy of full measurement invariance of factor loadings, factor variances– covariances, item uniquenesses, correlated uniquenesses, item intercepts, differential item functioning, and latent means show that women score higher on all NEO Big Five factors; (c) longitudinal analyses support measurement invariance over time and the maturity principle (decreases in Neuroticism and increases in Agreeableness, Openness, and Conscientiousness). Using ESEM, we addressed substantively important questions with broad applicability to personality research that could not be appropriately addressed with the traditional approaches of either EFA or CFA.
