Exploratory and confirmatory factor analyses of the pervasive developmental disorders rating scale for young children with autistic disorder

In this study, the authors examined the construct validity of the Pervasive Developmental Disorder Rating Scale (PDDRS; R. C. Eaves, 1993), which is a screening instrument used to identify individuals with autistic disorder and other pervasive developmental disorders. The PDDRS is purported to measure 3 factors--arousal, affect, and cognition-that collectively make up the construct of autism. Using scores from 199 children (aged 1-6 years) diagnosed with autistic disorder, the authors submitted data to exploratory and confirmatory factor analyses. In the 1st series of analyses, the authors analyzed a user-specified 3-factor solution using principal axis factor analysis with a promax rotation to evaluate the assertion of a correlated 3-factor structure. Next, the authors analyzed 1-factor and 2-factor solutions to determine if they provided a better factor structure for the data. In the 2nd series, the authors conducted confirmatory factor analyses, which compared the theorized hierarchical 2nd-order factor model with 5 plausible competing models. The results of the exploratory analyses supported the 3-factor solution. With the confirmatory analyses, the 2nd-order factor model provided the best fit for the data. The exploratory and confirmatory analyses supported the theoretical assumptions undergirding the development of the PDDRS. The authors discuss theoretical implications, practical implications, and areas for further research.     

Exploratory and confirmatory factor analyses of the Asian American Racism-Related Stress Inventory

The authors conducted exploratory and confirmatory factor analyses of the Asian American Racism-Related Stress Inventory (AARRSI) to further examine the underlying factor structure in a total sample of 1,273 Asian American participants. In the first step of analysis, an exploratory factor analysis with 651 participants yielded a 13-item two-factor solution to the data. In the second step, a confirmatory factor analysis with 622 participants supported both the 13-item two-factor model and the original 29-item three-factor model in the cross-validation sample and generational and ethnicity analyses. The two-factor and three-factor models produced internal consistency estimates ranging from .81 to .95. In addition, the authors examined convergent and criterion related evidence for 13-item and 29-item versions of the AARRSI. Given its brief nature and generally good fit across generational status and ethnicity, the authors suggest that the 13-item AARRSI might be advantageous for research and assessment endeavors.     

Cultural considerations using the structured clinical interview for DSM-III for mood and anxiety disorders assessment

This paper focuses on the impact that culture has upon standardized or structured interviews. It briefly reviews how these interviews evolved from a primary research function, what they can teach us about clinical work, and the multiple ways that culture influences these supposedly objective instruments and the diagnoses which follow from their use. Although the use of structured interviews and standardized diagnostic criteria has been a major advance for the field in terms of reliability, care needs to be exercised when evaluating individuals from disparate cultural backgrounds.     

Exploratory and confirmatory factor analysis of a short-form of the EMBU among Chinese adolescents

The present study used a sample of Chinese adolescents and validated a short-form of the Egna Minnen Betr?ffande Uppfostran: One's Memories of Upbringing (s-EMBU) assessing perceived parental rearing styles. A Chinese revision of the s-EMBU by the authors was administered to a total of 779 high school students, ages 11 to 19 years. Exploratory factor analysis with half of the sample yielded a three-factor solution of Rejection, Emotional Warmth, and Overprotection, accounting for 47.1% of the total variance onthe father form and 48.8% of the total variance on the mother form. Then, confirmatory factor analysis indicated a good fit of the three-factor model to the data in the other half of the sample. The three subscales consisted of 6, 6, and 7 items, respectively. Scores on these subscales had Cronbach alphas ranging from .71 to .81, indicating adequate internal consistency. These psychometric properties suggest its applicability for research with Chinese adolescents.     

The exploratory and confirmatory factor analyses of two subjective career success instruments

This study investigated the psychometric properties of two subjective career success instruments within the South African context: Perceived Career Success (PCSS: Gattiker &; Larwood, 1986 Gattiker, U. E., &; Larwood, L. (1986). Subjective career success: A study of managers and support personnel. Journal of Business and Psychology, 1(2), 78–94. http://dx.doi.org/10.1007/BF01018805[Crossref] , [Google Scholar]) and Life Success Measures Scale (LSMS: Parker &; Chusmir, 1992 Parker, B., &; Chusmir, L. H. (1992). Development and validation of a life-success measures scale. Psychological Reports, 70(2), 627–637. http://dx.doi.org/10.2466/pr0.1992.70.2.627[Crossref], [Web of Science ®] , [Google Scholar]). Data were collected via a convenient sample of 708 South African Police Services (SAPS) personnel (females = 36.8%; Sotho language = 62.50%). Exploratory factor analysis (EFA) was conducted on both instruments, followed by confirmatory factor analyses (CFA). Both instruments showed acceptable construct validity and reliability of scores.     

Comparison of several shortened versions of the EMBU: exploratory and confirmatory factor analyses

The aim of the present study was to analyze the psychometric properties of different versions of the EMBU (Egna Minnen av Barndoms Uppfostran – My memories of upbringing) in a non-clinical sample of adolescents. The factor structure of the questionnaire was studied by means of more adequate exploratory and confirmatory factor procedures in order to ascertain which version achieves a better fit to data. The 64-item version of the EMBU was administered to a non-clinical sample of 832 adolescents. Exploratory and Confirmatory factor analyses were carried out for successive versions of 64, 37, 24 and 23 items. The theoretical four-factor structure of the 64-item version is not replicated in a factor analysis through principal axis extraction with direct oblimin rotation. The "Favoring Subject" factor was not found. 37 items present loadings equal to or larger than 0.30 for the "Rejection", "Emotional Warmth" and "Overprotection" factors. A re-analysis of these items shows a clear three-factor structure. When Arrindell et al .'s (1999 ) 23-item version was analysed, the three expected factors were also found. Confirmatory factor analyses allow us to reduce the 36-item version to a shorter one of 24 items. This last version achieves the best fit to data, including the 23-item version. The new 24-item version improves the construct validity of the EMBU and presents similar reliability coefficients.     

Dimensionality of posttraumatic stress disorder symptoms in children exposed to disaster: results from confirmatory factor analyses.

Factor analytic studies of trauma victims' posttraumatic stress disorder (PTSD) have offered conflicting hypotheses about how to conceptualize PTSD into symptom categories. The present study used confirmatory factor analyses of self-reported PTSD symptomatology from 5,664 child and adolescent victims of Hurricane Hugo to compare 10 models of PTSD dimensionality. PTSD was best represented by a 2nd-order PTSD factor that manifests in 3 symptom clusters (Intrusion/Active Avoidance, Numbing/Passive Avoidance, and Arousal). This model was cross-validated on 3 age groups (late childhood, early adolescence, and late adolescence), and results indicated factorial invariance across groups. PTSD symptoms varied in relative centrality to the underlying dimensions of PTSD, which differed in their relations with anxiety and degree of traumatic exposure. Implications for classification criteria and an empirically supported theory of PTSD are discussed.     

Exploratory and confirmatory factor analytic investigations of the Illness Attitudes Scale in a nonclinical sample.

The Illness Attitudes Scale (IAS) assesses fears, beliefs and attitudes associated with hypochondriasis [Kellner, R. (1986). Somatization and hypochondriasis. New York: Praeger Publishers.]. Recent factor analytic investigations of the IAS in non-clinical samples have suggested a number of different factor solutions. In study 1, we used principal components analysis with both orthogonal and oblique rotation to better explore the structure of this measure. Using a random selection of 390 participants from a larger pool of 780, a five-factor solution was identified: (1) fear of illness, death, disease and pain, (2) effects of symptoms, (3) treatment experiences, (4) disease conviction and (5) health habits. In study 2, confirmatory factor analysis (CFA) of responses from the remaining 390 students evaluated: (a) a single-factor model, (b) Kellner's original nine-factor model, (c) a four-factor model proposed by Ferguson and Daniel [Ferguson, E. & Daniel, E. (1995). The Illness Attitudes Scale (IAS): a psychometric evaluation on a nonclinical population. Personality and Individual Differences, 18, 463-469.], (d) a different four-factor model proposed by Stewart and Watt [Stewart, S. H. & Watt, M. C. (1998). A psychometric investigation of the Illness Attitudes Scale (IAS) in a nonclinical young adult sample. Submitted for publication.] and (e) the five-factor model derived in study 1. Of these models, greatest support was obtained for our five-factor model. However, it was also clear that this model could be improved. Based on the results of the CFA, as well as previous research and theoretical considerations, we tested a revised model in which the health habits factor was deleted. Analysis of the revised model showed that it received the greatest support and could be conceptualized as either four distinct factors or as hierarchical in nature, with four lower-order factors loading on a single higher-order factor. Future directions for research as well as suggestions for scoring and using the IAS with nonclinical samples are discussed.     

Cognitive-affective stress propensity: A confirmatory factor analysis of stress propensity measures

A cognitive-affective stress propensity (CASP) construct is used to integrate previous findings regarding individual differences in experienced stress and resultant strain. A confirmatory factor analysis determined the structure of the CASP construct using a one factor model. This model and alternative models of factor structure contain two additional new constructs, psychological magnification and cognitive-affective connectivity. These two variables, and five trait variables previously identified as moderators in stress propensity research, were used in the analysis. Results show the one factor model to fit the data better than alternative models, thus supporting the notion of a latent construct (CASP).     

Examining the factor structure of the Psychological Mindedness Scale in the Japanese population through exploratory and confirmatory factor analyses

Psychological mindedness (PM) is a psychological construct that represents the tendency and ability to understand the relationships between thoughts, feelings, and behavior. This study examined the statistical properties, particularly the factor structure, of the Psychological Mindedness Scale (PMS) in a non‐clinical Japanese sample through exploratory and confirmatory factor analysis. The relationship between PMS and depression was also examined for predictive validity. The results suggested that the PMS tested on a Japanese sample contains the following four factors: (a) belief in the benefits of discussing one's problems; (b) access to feelings; (c) openness to new ideas and capacity to change; and (d) interest in the meaning and motivation of own and others' behavior. Whereas the total PM score and Factors 2 and 3 had negative correlations with depression, there was a positive correlation between Factor 4 and depression. The 4‐factor structure of the scale is deemed to be applicable to the Japanese population.     

Comparison of alternative estimation methods in confirmatory factor analyses of the General Health Questionnaire

This paper examines the implications of violating assumptions concerning the continuity and distributional properties of data in establishing measurement models in social science research. The General Health Questionnaire-12 uses an ordinal response scale. Responses to the GHQ-12 from 201 Hong Kong immigrants on arrival in Australia showed that the data were not normally distributed. A series of confirmatory factor analyses using either a Pearson product-moment or a polychoric correlation input matrix and employing either maximum likelihood, weighted least squares or diagonally weighted least squares estimation methods were conducted on the data. The parameter estimates and goodness-of-fit statistics provided support for using polychoric correlations and diagonally weighted least squares estimation when analyzing ordinal, nonnormal data.     

Exploratory second-order analyses for components and factors

Abstract: Exploratory methods using second‐order components and second‐order common factors were proposed. The second‐order components were obtained from the resolution of the correlation matrix of obliquely rotated first‐order principal components. The standard errors of the estimates of the second‐order component loadings were derived from an augmented information matrix with restrictions for the loadings and associated parameters. The second‐order factor analysis proposed was similar to the classical method in that the factor correlations among the first‐order factors were further resolved by the exploratory method of factor analysis. However, in this paper the second‐order factor loadings were estimated by the generalized least squares using the asymptotic variance‐covariance matrix for the first‐order factor correlations. The asymptotic standard errors for the estimates of the second‐order factor loadings were also derived. A numerical example was presented with simulated results.     

Invariance of the “NEO-PI-R” factor structure across exploratory and confirmatory factor analyses

Confirmatory factor analyses (CFA) carried out in the last decades to test the Five-factor simple structure have generally obtained negative results. McCrae, Zonderman, Costa, Bond, and Paunonen (1996) suggested that CFA limitations were the main cause of such negative results. They also claim that Procrustes Orthogonal rotation method is an adequate procedure to test the replicability of the Five-factor structure. The aim of the present paper is twofold: (A) comparing several Exploratory factor procedures (including the Procrustes rotation) to test what is the most appropriate one to analyse the replicability of the Five-factor structure, and (B) replicating the CFA results of the McCrae et al.’s study with a larger number of subjects. The normative American (N = 1000), and Spanish (2000) standardization samples of the NEO-PI-R, together with an independent university sample (N = 948) were analysed. Results were replicated in the three samples, and suggest that: (1) structural properties of the Five-factor model, as measured by the NEO-PI-R, are invariant irrespective of the Exploratory factor procedure used, and (2) when CFA limitations are surpassed, the Five-factor structure is supported.     

A structured interview for the assessment of the Five-Factor Model of personality: facet-level relations to the axis II personality disorders

The Structured Interview for the Five-Factor Model (SIFFM; Trull & Widiger, 1997) is an 120-item semistructured interview that assesses both adaptive and maladaptive features of the personality traits included in the five-factor model of personality, or "Big Five." In this article, we evaluate the ability of SIFFM scores to predict personality disorder symptomatology in a sample of 232 adults (46 outpatients and 186 nonclinical college students). Personality disorder symptoms were assessed using the Personality Diagnostic Questionnaire-Revised (PDQ-R; Hyler & Rider, 1987). Results indicated that many of the predicted associations between lower-order personality traits and personality disorders were supported. Further, many of these associations held even after controlling for comorbid personality disorder symptoms. These findings may help inform conceptualizations of the personality disorders, as well as etiological theories and treatment.     

Assessing personality disorders using a systematic clinical interview: evaluation of an alternative to structured interviews

The aim of this study was to assess interrater reliability and provide initial data bearing on the validity of a method of assessing personality disorders (PDs) that does not presume that patients can accurately self-report personality pathology. In a sample of 24 outpatients, two clinician-judges independently applied the Shedler-Westen Assessment Procedure-200 (SWAP-200; Westen & Shedler, 1999a, 2000), a 200-item Q-sort procedure for assessing personality pathology, to data from the Clinical Diagnostic Interview (Westen, 2002), a systematic clinical interview that mirrors and standardizes methods used by experienced clinicians to diagnose personality. In 16 of the 24 cases, the treating clinician also independently described the patient using the SWAP-200 Q-sort, based on longitudinal knowledge of the patient over the course of treatment, blind to the interview data. Interrater reliability was uniformly high, with median correlations between interviewers at r > .80. Interviewer-treating clinician correlations were also high, with median convergent validity coefficients at r > .80. Diagnostic overlap (discriminant validity) was moderate for dimensional DSM-IV diagnoses, reflecting extensive comorbidity among disorders, but minimal for empirically derived diagnoses identified in prior research. Treating clinicians' dimensional PD diagnoses using this method also strongly predicted interviewer-rated measures of adaptive functioning. The findings provide preliminary support for the reliability and validity of an alternative to structured interviews for diagnosing personality pathology, and suggest that the way to improve validity of personality diagnosis may not be to minimize clinical inference but to quantify it using psychometric instruments.     

A psychometric investigation of the content of the structured interview

The responses of 92 British males to the questions of the Structured Interview (SI) were content analysed. The consistency of the content in measuring a single concept was investigated by means of item and factor analyses. A simple, unweighted sum of the content ratings was then compared with the scores achieved on the three prospectively validated Type A measures—the Jenkins Activity Survey, the Framingham Scale and the SI. The results from the analyses suggest that the content of the SI has many similarities with the questionnaire assessments of Type A behaviour and is a poor predictor of SI assessment. It is argued that the added dimension of style of response that is considered in the SI is the reason for different assessments being made by the SI and the questionnaire measures of Type A behaviour. The implications for the measurement of Type A behaviour are discussed.     

Model‐related factor score predictors for confirmatory factor analysis

The present paper introduces model‐related (MR) factor score predictors, which reflect specific aspects of confirmatory factor models. The development is mainly based on Schönemann and Steiger's regression score components, but it can also be applied to the factor score coefficients. It is shown that the rotation of factor score predictors has no impact on the covariance matrix reproduced from the corresponding regression component patterns. Thus, regression score components or factor score coefficients can be rotated in order to obtain the required properties. This idea is the basis for MR factor score predictors, which are computed by means of a partial Procrustes rotation towards a target pattern representing the interesting properties of a confirmatory factor model. Two examples demonstrate the construction of MR factor score predictors reflecting specific constraints of a factor model.     

A confirmatory analysis of the factor stability hypothesis

The procedures recently developed by Jöreskog for studying similarities and differences in factor structures between different groups were applied to data from a study designed by Thurstone to investigate the sampling stability of a hypothesized isolated configuration. The hypothesis of an isolated configuration was rejected but not by much. The results represent a restricted and unique simple structure solution with the factor loadings and uniqueness values invariant over the two samples.     

Exploratory factor analysis for small samples

Traditionally, two distinct approaches have been employed for exploratory factor analysis: maximum likelihood factor analysis and principal component analysis. A third alternative, called regularized exploratory factor analysis, was introduced recently in the psychometric literature. Small sample size is an important issue that has received considerable discussion in the factor analysis literature. However, little is known about the differential performance of these three approaches to exploratory factor analysis in a small sample size scenario. A simulation study and an empirical example demonstrate that regularized exploratory factor analysis may be recommended over the two traditional approaches, particularly when sample sizes are small (below 50) and the sample covariance matrix is near singular.