Statistical analysis of the goodness of classical factor analysis regression (CFAR) /

Cover title.

An investigation of the goodness of fit of the maximum likelihood estimation procedure in factor analysis /

Thesis--Illinois.

The structure of labor market segmentation of occupations : some evidence from factor analysis /

Includes bibliographies (p. 31).

An application of factor analysis to water quality data /

Cover title.

Gray's model of personality and aggregate level factor analysis

Previous research shows that correlations tend to increase in magnitude when individuals are aggregated across groups. This suggests that uncorrelated constellations of personality variables (such as the primary scales of Extraversion and Neuroticism) may display much higher correlations in aggregate factor analysis. We hypothesize and report that individual level factor analysis can be explained in terms of Giant Three (or Big Five) descriptions of personality, whereas aggregate level factor analysis can be explained in terms of Gray's physiological based model. Although alternative interpretations exist, aggregate level factor analysis may correctly identify the basis of an individual's personality as a result of better reliability of measures due to aggregation. We discuss the implications of this form of analysis in terms of construct validity, personality theory, and its applicability in general. Copyright (C) 2003 John Wiley Sons, Ltd.

The gambling related cognitions scale (GRCS): development, confirmatory factor validation and psychometric properties

Aims The aims of this study are to develop and validate a measure to screen for a range of gambling-related cognitions (GRC) in gamblers. Design and participants A total of 968 volunteers were recruited from a community-based population. They were divided randomly into two groups. Principal axis factoring with varimax rotation was performed on group one and confirmatory factor analysis (CFA) was used on group two to confirm the best-fitted solution. Measurements The Gambling Related Cognition Scale (GRCS) was developed for this study and the South Oaks Gambling Screen (SOGS), the Motivation Towards Gambling Scale (MTGS) and the Depression Anxiety Stress Scale (DASS-2 1) were used for validation. Findings Exploratory factor analysis performed using half the sample indicated five factors, which included interpretative control/bias (GRCS-IB), illusion of control (GRCS-IC), predictive control (GRCS-PC), gambling-related expectancies (GRCS-GE) and a perceived inability to stop gambling (GRCS-IS). These accounted for 70% of the total variance. Using the other half of the sample, CFA confirmed that the five-factor solution fitted the data most effectively. Cronbach's alpha coefficients for the factors ranged from 0.77 to 0.91, and 0.93 for the overall scale. Conclusions This paper demonstrated that the 23-item GRCS has good psychometric properties and thus is a useful instrument for identifying GRC among non-clinical gamblers. It provides the first step towards devising/adapting similar tools for problem gamblers as well as developing more specialized instruments to assess particular domains of GRC.

The gambling urge scale: Development, confirmatory factor validation, and psychometric properties

The urge to gamble is a physiological, psychological, or emotional motivational state, often associated with continued gambling. The authors developed and validated the 6-item Gambling Urge Questionnaire (GUS), which was based on the 8-item Alcohol Urge Questionnaire (M. J. Bohn, D. D. Krahn, & B. A. Staehler, 1995), using 968 community-based participants. Exploratory factor analysis using half of the sample indicated a 1-factor solution that accounted for 55.18% of the total variance. This was confirmed using confirmatory factor analysis with the other half of the sample. The GUS had a Cronbach's alpha coefficient of .81. Concurrent, predictive, and criterion-related validity of the GUS were good, suggesting that the GUS is a valid and reliable instrument for assessing gambling urges among nonclinical gamblers.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

Factor analysis of the self-report Dysexecutive (DEX-S) Questionnaire

The self-rating Dysexecutive Questionnaire (DEX-S) is a recently developed standardized self-report measure of behavioral difficulties associated with executive functioning such as impulsivity, inhibition, control, monitoring, and planning. Few studies have examined its construct validity, particularly for its potential wider use across a variety of clinical and nonclinical populations. This study examines the factor structure of the DEX-S questionnaire using a sample of nonclinical (N = 293) and clinical (N = 49) participants. A series of factor analyses were evaluated to determine the best factor solution for this scale. This was found to be a 4-factor solution with factors best described as inhibition, intention, social regulation, and abstract problem solving. The first 2 factors replicate factors from the 5-factor solutions found in previous studies that examined specific subpopulations. Although further research is needed to evaluate the factor structure within a range of subpopulations, this study supports the view that the DEX has the factor structure sufficient for its use in a wider context than only with neurological or head-injured patients. Overall, a 4-factor solution is recommended as the most stable and parsimonious solution in the wider context.

Factor structure and internal consistency of the Young Schema Questionnaire (Short Form) in Korean and Australian samples

We investigated cross-cultural differences in the factor structure and psychometric properties of the 75-item Young Schema Questionnaire-Short Form (YSQ-SF). Participants were 833 South Korean and 271 Australian undergraduate students. The South Korean sample was randomly divided into two sub-samples. Sample A was used for Exploratory Factor Analysis (EFA) and sample B was used for Confirmatory Factor Analysis (CFA). EFA for the South Korean sample revealed a 13-factor solution to be the best fit for the data, and CFA on the data from sample B confirmed this result. CFA on the data from the Australian sample also revealed a 13-factor solution. The overall scale of the YSQ-SF demonstrated a high level of internal consistency in the South Korean and Australian groups. Furthermore, adequate internal consistencies for all subscales in the South Korean and Australian samples were demonstrated. In conclusion, the results showed that YSQ-SF with 13 factors has good psychometric properties and reliability for South Korean and Australian University students. Korean samples had significantly higher YSD scores on most of the 13 subscales than the Australian sample. However, limitations of the current study preclude the generalisability of the findings to beyond undergraduate student populations. (c) 2006 Elsevier B.V. All rights reserved.

Evaluating the properties of a stage-specific self-efficacy scale for physical activity using classical test theory, confirmatory factor analysis and item response modeling

The purpose of this paper was to evaluate the psychometric properties of a stage-specific selfefficacy scale for physical activity with classical test theory (CTT), confirmatory factor analysis (CFA) and item response modeling (IRM). Women who enrolled in the Women On The Move study completed a 20-item stage-specific self-efficacy scale developed for this study [n = 226, 51.1% African-American and 48.9% Hispanic women, mean age = 49.2 (67.0) years, mean body mass index = 29.7 (66.4)]. Three analyses were conducted: (i) a CTT item analysis, (ii) a CFA to validate the factor structure and (iii) an IRM analysis. The CTT item analysis and the CFA results showed that the scale had high internal consistency (ranging from 0.76 to 0.93) and a strong factor structure. Results also showed that the scale could be improved by modifying or eliminating some of the existing items without significantly altering the content of the scale. The IRM results also showed that the scale had few items that targeted high self-efficacy and the stage-specific assumption underlying the scale was rejected. In addition, the IRM analyses found that the five-point response format functioned more like a four-point response format. Overall, employing multiple methods to assess the psychometric properties of the stage-specific self-efficacy scale demonstrated the complimentary nature of these methods and it highlighted the strengths and weaknesses of this scale.

A novel neural network technique for exploratory data analysis

This paper surveys the context of feature extraction by neural network approaches, and compares and contrasts their behaviour as prospective data visualisation tools in a real world problem. We also introduce and discuss a hybrid approach which allows us to control the degree of discriminatory and topographic information in the extracted feature space.

Factor analysis and discriminant validity:a brief review of some practical issues

Growth in availability and ability of modern statistical software has resulted in greater numbers of research techniques being applied across the marketing discipline. However, with such advances come concerns that techniques may be misinterpreted by researchers. This issue is critical since misinterpretation could cause erroneous findings. This paper investigates some assumptions regarding: 1) the assessment of discriminant validity; and 2) what confirmatory factor analysis accomplishes. Examples that address these points are presented, and some procedural remedies are suggested based upon the literature. This paper is, therefore, primarily concerned with the development of measurement theory and practice. If advances in theory development are not based upon sound methodological practice, we as researchers could be basing our work upon shaky foundations.