Examination of the structural, convergent, and incremental validity of the Reynolds Intellectual Assessment Scales (RIAS) with a clinical sample

Empirical examination of the Reynolds Intellectual Assessment Scales (RIAS; C. R. Reynolds & R. W. Kamphaus, 2003a) has produced mixed results regarding its internal structure and convergent validity. Various aspects of validity of RIAS scores with a sample (N = 521) of adolescents and adults seeking psychological evaluations at a university-based clinic were examined. Results from exploratory factor analysis indicated only 1 factor, and confirmatory factor analysis (CFA) indicated that the 1-factor model was a good fit and a better fit than the 2-factor model. Hierarchical factor analysis indicated the higher order, general intelligence factor accounted for the largest amount of variance. Correlations with other measures of verbal/crystallized and nonverbal/fluid intelligence were supportive of the convergent validity of the Verbal Intelligence Index but not the Nonverbal Intelligence Index. Joint CFA with these additional measures resulted in a superior fit of the 2-factor model compared with the 1-factor model, although the Odd-Item-Out subtest was found to be a poor measure of nonverbal/fluid intelligence. Incremental validity analyses indicated that the Composite Intelligence Index explained a medium to large portion of academic achievement variance; the NIX and VIX explained a small amount of remaining variance. Implications regarding interpretation of the RIAS when assessing similar individuals are discussed.     

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.     

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III)

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.     

The structure of childhood disruptive behaviors

Attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) frequently co-occur. Comorbidity of these 2 childhood disruptive behavior domains has not been satisfactorily explained at either a structural or etiological level. The current study evaluated a bifactor model, which allows for a "g" factor in addition to distinct component factors, in relation to other models to improve understanding of the structural relationship between ADHD and ODD. Participants were 548 children (321 boys, 227 girls) between the ages of 6 years and 18 years who participated in a comprehensive diagnostic assessment incorporating parent and teacher ratings of symptoms. Of these 548 children, 153 children were diagnosed with ADHD (without ODD), 114 children were diagnosed with ADHD + ODD, 26 children were diagnosed with ODD (without ADHD), and 239 children were classified as non-ADHD/ODD comparison children (including subthreshold cases). ADHD symptoms were assessed via parent report on a diagnostic interview and via parent and teacher report on the ADHD Rating Scale. ODD symptoms were assessed via teacher report. A bifactor model of disruptive behavior, comprising a "g" factor and the specific factors of ADHD and ODD, exhibited best fit, compared to 1-factor, 2-factor, 3-factor, and 2nd-order factor models of disruptive behaviors. It is concluded that a bifactor model of childhood disruptive behaviors is superior to existing models and may help explain common patterns of comorbidity between ADHD and ODD.     

Orthogonal higher order structure of the Wechsler Intelligence Scale For Children--fourth edition

According to J. B. Carroll's (1993) 3-stratum theory, performance on any subtest reflects a mixture of both 2nd-order and 1st-order factors. To disentangle these influences, variance explained by the general factor should be extracted first. The 1st-order factors are then residualized, leaving them orthogonal to the general factor and each other. When these methods were applied to the WISC-IV standardization sample, the general factor accounted for the greatest amount of common (71.3%) and total (38.3%) variance. The largest contribution by a first-order factor was 6.5% of total variance. It was recommended that interpretation of the WISC-IV not discount the strong general factor.     

Confirmatory factor analysis of the psychopathy checklist: screening version in offenders with axis I disorders

One hundred forty-nine inpatients within a maximum security psychiatric facility were assessed with the Psychopathy Checklist: Screening Version (PCL:SV; S. D. Hart, D. N. Cox, & R. D. Hare, 1995). Within the total sample, 68% had a psychotic disorder and 30% met criteria for psychopathy. Using confirmatory factor analysis, the authors tested the 2-factor PCL:SV model of psychopathy and recent 3- and 4-factor models. Results indicated good fit for each model, with the 4-factor model showing best overall fit. Structural equation modeling was used to determine which psychopathy factors predicted 6-month follow-up of inpatient aggression. The 2-, 3-, and 4-factor models, respectively, accounted for 16%.27%. and 3l% of the variance in aggression.     

Psychometric evaluation of the Greek version of the Aggression Questionnaire

The study assesses the psychometric properties of the Greek version of the Aggression Questionnaire by Buss and Perry in a sample of 760 Greek high school students. This questionnaire has been widely used to study Physical Aggression, Verbal Aggression, Anger, and Hostility. A confirmatory factor analysis of responses showed adequate fit for the original 4-factor model (total variance explained: 68.2%). The analysis also showed satisfactory internal consistency and temporal stability over 6 to 8 weeks. Also, the construct validity, extreme groups' validity, and predictive validity indices were adequate. Greek female students adopted more indirect forms of aggression (Hostility) than males, who applied more direct forms such as Physical Aggression. Findings supported the use of the Greek version of the questionnaire for assessment in high school students.     

Factor structure of the Child Behavior Checklist/6-18 in a sample of girls adopted from China

Confirmatory factor analysis with robust weighted least squares estimation of the 103 dichotomously scored items of the Child Behavior Checklist/6-18 (T. M. Achenbach & L. A. Rescorla, 2001) in a sample of 516 girls adopted from China (ages 6.0-15.7 years; M = 8.2, SD = 1.9) indicated that the fit of the 8-factor model was good (root-mean-square error of approximation = .047) and was slightly better than what T. M. Achenbach and L. A. Rescorla (2001) reported for the same model (.06). Support for the 2nd-order factor structure of Internalizing and Externalizing Problems also was provided. Comparisons of the mean scores for the syndromes and Internalizing, Externalizing, and Total Problems revealed mostly small differences between the sample of adopted Chinese girls and T. M. Achenbach and L. A. Rescorla's normative samples.     

Revisiting the factor structure of the questionnaire on smoking urges

This study assessed the factor structure of the Questionnaire on Smoking Urges (QSU), a commonly used assessment of cravings for cigarettes, with a sample of smokers presenting for treatment in a smoking cessation trial. On the basis of previous research, three confirmatory factor analytic models were tested. Model 1 hypothesized a 26-item, 2-factor model using the items reported in the original QSU analysis by S. T. Tiffany and D. J. Drobes (1991). Model 2 hypothesized a 12-item, 2-factor model comprised of the 6 most robust items found in each of the 2 factors of the original factor analysis. Using the 12 items from Model 2, Model 3 hypothesized a 12-item, 1-factor model. The 2nd model was found to fit the data best. Reliability was also tested using values obtained in this 2nd model, and these estimates were found to be reasonably good. Future research directions for the QSU are discussed.     

Decomposing person and occasion-specific effects: an extension of latent state-trait (LSI) theory to hierarchical LST models

An extension of latent state-trait (LST) theory to hierarchical LST models is presented. In hierarchical LST models, the covariances between 2 or more latent traits are explained by a general 3rd-order factor, and the covariances between latent state residuals pertaining to different traits measured on the same measurement occasion are explained by 2nd-order latent occasion-specific factors. Analogous to recent developments in multitrait-multimethod methodology, all factors are interpreted in relation to factors taken as comparison standards. An empirical example from test anxiety research illustrates how estimates of additive variance components due to general trait, specific trait, occasion, state residual, method, and measurement error can be obtained using confirmatory factor analysis. Advantages and limitations of these models are discussed.     

Testing factor models of the Psychopathy Checklist: Youth Version and their association with instrumental aggression

Although there is a documented link between psychopathy and instrumental violence in adult offenders, the association between these constructs has not garnered significant attention in adolescent offenders. In this study, we evaluated the relationship between psychopathy and instrumental aggression in a sample of 122 male adolescents incarcerated in a state facility for serious and chronic offenders. We evaluated the primary (2-, 3-, and 4-factor) models of the Psychopathy Checklist: Youth Version (PCL:YV; Forth, Kosson, & Hare, 2003) and assessed their relationship to a separate 5-item measure of instrumental violence. CFA revealed good model fit for the 3- and 4-factor latent variable models of adolescent psychopathy and a single-factor model reflecting a 5-item measure of instrumental violence. Structural equation modeling results indicate that the 4-factor model accounted for 20% of the variance for instrumental violence. In contrast, the 3-factor model of the PCL:YV accounted for 8%, and the 2-factor model accounted for 5% of the variance associated with instrumental violence.     

The Factor Structure of Anxiety and Depressive Disorders in a Sample of Clinic-Referred Adolescents

The current study used confirmatory factor analysis (CFA) to examine the factor structure of anxiety and depressive disorders in a sample of clinic-referred adolescents, aged between 12 and 18 years, for diagnoses based on parent (N?=?655; male?=?441) and adolescent (N?=?626; male?=?417) interviews. Three models were examined: a 1-factor model, with all anxiety and depressive disorders in a single factor; a DSM-based 2-factor model, with anxiety disorders in one factor, and depressive disorders in another factor; and an alternate 2-factor model, with fear related anxiety disorders in one factor, and other anxiety and depressive disorders in another factor. The findings indicated support for all three models. Also, ADHD and ODD/CD were associated with only the shared variances between the latent factors in the 2-factor models, and not their unique variance. The implications of the findings for taxonomy, comorbidity, and clinical practice are discussed.     

Measurement of smoking outcome expectancies in children: the Smoking Consequences Questionnaire-Child.

A measure of smoking outcome expectancies was developed for children ages 7-12 years. Confirmatory factor analysis (CFA) was used to determine whether a 1-, 2-, 3-, or 4-factor solution was most appropriate for the data set. CFA revealed that the 3-factor model produced the most adequate fit (Positive Reinforcement, Negative Consequences, and Weight Control). The resulting 15-item measure was named the Smoking Consequences Questionnaire-Child (SCQ-C). The fit of the 3-dimensional structure was then examined separately for 3 age groups representing young (7- to 8-year-old), middle (9- to 10-year-old), and old (11- to 13-year-old) children. Overall, the 3-factor structure fit the data well for the 3 groups. As such, we examined the relations of the 3 scales with antecedent variables for the entire sample. The Positive Reinforcement scale was associated with children's smoking behavior and having a family member or peers who smoked. The Negative Consequences scale was inversely related to having a family member or peer who smoked.     

Confirmatory factor analysis of the NEPSY for younger and older school-age children

Using the standardization sample from the NEPSY, confirmatory factor analysis was conducted to examine the factor structure for ages 5 through 12 of the NEPSY sample, as well as for the younger (5 to 8 years, n=400) and older (9 to 12 years, n=400) age bands, to explore possible differences in test structure at different developmental epochs. Using four standard fit indices, results indicated that a 5-factor model was less than adequate for the entire sample and produced negative error variance for the younger and older age groups, making any solutions for the two subgroups inadmissible. A 4-factor model without the Attention/Executive Function subtests produced satisfactory fit statistics for the entire sample and the younger group, but did not fit the data as well for the older group. A 1-factor model did not fit well for the full sample. These results indicated that the structure for the NEPSY is not invariant across development, with the 4-factor model best fitting the data for the younger age group and for the entire school-age sample.     

Examining the Factor Structure of the Self-Compassion Scale in Four Distinct Populations: Is the Use of a Total Scale Score Justified?

This study examined the factor structure of the Self-Compassion Scale (SCS) using a bifactor model, a higher order model, a 6-factor correlated model, a 2-factor correlated model, and a 1-factor model in 4 distinct populations: college undergraduates (N = 222), community adults (N = 1,394), individuals practicing Buddhist meditation (N = 215), and a clinical sample of individuals with a history of recurrent depression (N = 390). The 6-factor correlated model demonstrated the best fit across samples, whereas the 1- and 2-factor models had poor fit. The higher order model also showed relatively poor fit across samples, suggesting it is not representative of the relationship between subscale factors and a general self-compassion factor. The bifactor model, however, had acceptable fit in the student, community, and meditator samples. Although fit was suboptimal in the clinical sample, results suggested an overall self-compassion factor could still be interpreted with some confidence. Moreover, estimates suggested a general self-compassion factor accounted for at least 90% of the reliable variance in SCS scores across samples, and item factor loadings and intercepts were equivalent across samples. Results suggest that a total SCS score can be used as an overall mesure of self-compassion.     

Motor Creativity and Self-Concept

Creative children often have difficulty in forming their self-concept because parents may suppress their creative ideas. The purpose of this study was to investigate the relationship between motor creativity and self-concept. Wyrick's Motor Creativity Test and the Pictorial Scale of Perceived Competence and Social Acceptance for Young Children were administered to a sample of 414 children aged from 6 ± 0.3 years to 7 ± 0.3 years. Factor analysis for the self-concept measures revealed a 4-factor solution. The amount of variance explained by all 4 factors was 30.28% with the first factor explaining most of the variance (18.2%). Correlation analysis related motor creativity with the self-concept factors, and specifically with the first factor. It seems that perceived maternal acceptance has a significant role in explaining children's motor creativity.     

Examining the Latent Structure of Posttraumatic Growth Between Male and Female Survivors in the Immediate Aftermath of a Flash Flood Disaster

The study examined and compared the latent structure of posttraumatic growth (PTG) based on three proposed models: 1-factor, 3-factor and 5-factor models in order to (1) find out the factor structure that has the best fit for the Filipino sample; (2) find out the factor structure that best represents PTG in the immediate aftermath of a flash flood disaster; and (3) examine the generalizability of the best-fitted model across gender. A sample of 895 survivor-respondents answered the Posttraumatic Growth Inventory (PTGI) within a month after a deadly flash flood. Based on the best-fitted model, a multi-group comparison between male and female was conducted to determine gender generalizability. Results showed that the 3-factor model comprising of Changes in Self/Positive Life Attitudes, Philosophy of Life, and Relating to Others fitted best in contrast to the other two models. The data also demonstrated the generalizability of the 3-factor model across gender, with invariance in factor loadings, item intercepts, factor variance and covariance, and factor means.     

Measurement invariance tests of the Impression Management sub-scale of the Balanced Inventory of Desirable Responding

The Impression Management (IM) subscale of the Balanced Inventory of Desirable Responding (Paulhus, 1988) has been used as a proxy for common method variance in anonymous settings and as a cause of faking on personality testing in confidential settings. This study uses confirmatory factor analysis to conduct measurement invariance/equivalence tests (also known as multiple group analysis) on the IM subscale in a quasi-experiment in anonymous and confidential data collection settings. Using Brown’s (2006) bottom-up approach to Cheung and Rensvold’s (1999) model testing steps and Cheung and Rensvold’s (2002) statistical tests, the IM sub-scale was determined to have equal form, equal factor loadings, equal indicator error variances, equal factor variance, and an equal factor covariance in both 1-factor and 2-factor models in both data collection settings. Mean scale scores were significantly higher in the confidential group than in the anonymous group. These results suggest that using the IM sub-scale as a cause of faking and as a proxy for common method variance (CMV) is likely to be acceptable because the psychometric properties of the instrument are invariant across testing conditions.     

Measuring motivations for intercollegiate athlete alcohol use: a confirmatory factor analysis of the drinking motives measure

This study examined the psychometric properties of the Drinking Motives Measure (DMM) on a sample of 227 collegiate athletes. Confirmatory factor analyses indicated that the 4-factor structure of the DMM provided a better fit than either 2- or 1-factor models, but the overall fit of the 4-factor model was moderate at best. A revised 3-factor model consistent with prior research (M. L. Cooper, M. Russell, J. B. Skinner, & M. Windle, 1992) provided the best fit. Hierarchical multiple regression analyses indicated that the 3 DMM factors included in the revised model accounted for 17%-21% of the unique variance on alcohol consumption variables. Results provide preliminary evidence supporting the internal consistency, construct validity, and convergent validity of the revised 3-factor DMM with collegiate athletes.     

Development and Initial Validation of the Multicultural Personality Inventory (MPI)

Two studies summarize the development and initial validation of the Multicultural Personality Inventory (MPI). In Study 1, the 115-item prototype MPI was administered to 415 university students where exploratory factor analysis resulted in a 70-item, 7-factor model. In Study 2, the 70-item MPI and theoretically related companion instruments were administered to a multisite sample of 576 university students. Confirmatory factory analysis found the 7-factor structure to be a relatively good fit to the data (Comparative Fit Index =.954; root mean square error of approximation =.057), and MPI factors predicted variance in criterion variables above and beyond the variance accounted for by broad personality traits (i.e., Big Five). Study limitations and directions for further validation research are specified.