Carol M. Woods

More information from fewer questions: The factor structure and item properties of the original and Brief Fear of Negative Evaluation scale

Statistical methods designed for categorical data were used to perform confirmatory factor analyses and item response theory (IRT) analyses of the Fear of Negative Evaluation scale (FNE; D. Watson & R. Friend, 1969) and the Brief FNE (BFNE; M. R. Leary, 1983). Results suggested that a 2-factor model fit the data better for both the FNE and the BFNE, although the evidence was less strong for the FNE. The IRT analyses indicated that although both measures had items with good discrimination, the FNE items discriminated only at lower levels of the underlying construct, whereas the BFNE items discriminated across a wider range. Convergent validity analyses indicated that the straightforwardly-worded items on each scale had significantly stronger relationships with theoretically related measures than did the reverse-worded items. On the basis of all analyses, usage of the straightforwardly-worded BFNE factor is recommended for the assessment of fear of negative evaluation.

Relationship Between Obsessive Beliefs and Obsessive–Compulsive Symptoms

The aim of this study was to examine the relationship between symptom presentation in obsessive–compulsive disorder (OCD) and dysfunctional beliefs hypothesized to relate to OCD. Five-hundred sixty two undergraduates completed self-report measures of OCD symptoms and OCD-related beliefs, as well as measures of social anxiety and depression. The tendency to overestimate threat significantly predicted the OCD symptom domains of washing, checking/doubting, obsessing, mental neutralizing, and hoarding. Perceived need to control ones thoughts predicted obsessing. Perceived importance of thoughts predicted neutralizing. Perfectionism beliefs predicted ordering. Although the relationship between dysfunctional beliefs and OCD remained significant when controlling for social anxiety and depression, Threat Estimation and Perfectionism showed a moderate relationship with these variables as well. Thus, although some dysfunctional beliefs show a specific relationship to OCD, others may reflect broader forms of psychopathology.

The factor structure and screening utility of the social interaction anxiety scale

The widely used Social Interaction Anxiety Scale (SIAS; R. P. Mattick & J. C. Clarke, 1998) possesses favorable psychometric properties, but questions remain concerning its factor structure and item properties. Analyses included 445 people with social anxiety disorder and 1,689 undergraduates. Simple unifactorial models fit poorly, and models that accounted for differences due to item wording (i.e., reverse scoring) provided superior fit. It was further found that clients and undergraduates approached some items differently, and the SIAS may be somewhat overly conservative in selecting analogue participants from an undergraduate sample. Overall, this study provides support for the excellent properties of the SIASs straightforwardly worded items, although questions remain regarding its reverse-scored items.

The Anxiety Sensitivity Index - Revised: psychometric properties and factor structure in two nonclinical samples

Anxiety sensitivity (AS) is the fear of anxiety-related sensations based on beliefs about their harmful consequences. Despite its status as the most popular measure of AS, the anxiety sensitivity index is too abbreviated to adequately measure the somatic, cognitive, and social facets of the construct. The Anxiety Sensitivity Index - Revised (ASI-R) is a revised and expanded version of the ASI that was developed to improve the assessment of AS and its dimensions. The present study was conducted to examine the psychometric properties and factor structure of the ASI-R. Two large undergraduate samples completed a psychometric assessment package that included the ASI-R and measures of anxiety, depression, and related constructs. Exploratory factor analysis revealed four lower-order ASI-R factors: (1) beliefs about the harmful consequences of somatic sensations; (2) fear of publicly observable anxiety reactions; (3) fear of cognitive dyscontrol; and (4) fear of somatic sensations without explicit consequences. These factors loaded on a single, higher-order factor. Correlations between the ASI-R factors and related variables were consistent with AS theory. Results across both samples in the present study were highly similar. The strengths and limitations of the ASI-R are discussed, and the implications of our findings for the nature and measurement of AS are considered.

Evaluation of MIMIC-Model Methods for DIF Testing With Comparison to Two-Group Analysis

Differential item functioning (DIF) occurs when an item on a test or questionnaire has different measurement properties for 1 group of people versus another, irrespective of mean differences on the construct. This study focuses on the use of multiple-indicator multiple-cause (MIMIC) structural equation models for DIF testing, parameterized as item response models. The accuracy of these methods, and the sample size requirements, are not well established. This study examines the accuracy of MIMIC methods for DIF testing when the focal group is small and compares results with those obtained using 2-group item response theory (IRT). Results support the utility of the MIMIC approach. With small focal-group samples, tests of uniform DIF with binary or 5-category ordinal responses were more accurate with MIMIC models than 2-group IRT. Recommendations are offered for the application of MIMIC methods for DIF testing.

An item response theory analysis of DSM-IV personality disorder criteria across younger and older age groups.

Many of the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV; American Psychiatric Association, 1994) personality disorder (PD) diagnostic criteria focus on a younger social and occupational context. The absence of age-appropriate criteria for older adults forces researchers and clinicians to draw conclusions based on existing criteria, which are likely inadequate. To explore which DSM-IV PD criteria contain age group measurement bias, the authors report 2 analyses of data on nearly 37,000 participants, ages 18-98 years, taken from a public data set that includes 7 of the 10 PDs (antisocial, avoidant, dependent, histrionic, obsessive-compulsive, paranoid, and schizoid). The 1st analysis revealed that older age groups tend to endorse fewer PD criteria than younger age groups. The 2nd analysis revealed that 29% of the criteria contain measurement bias. Although the latent variable structure for each PD was quite similar across younger and older age groups, some individual criteria were differentially endorsed by younger and older adults with equivalent PD pathology. The presence of measurement bias for these criteria raises questions concerning the assessment of PDs in older adults and the interpretation of existing data.

Empirical Selection of Anchors for Tests of Differential Item Functioning

Differential item functioning (DIF) occurs when items on a test or questionnaire have different measurement properties for one group of people versus another, irrespective of group-mean differences on the construct. Methods for testing DIF require matching members of different groups on an estimate of the construct. Preferably, the estimate is based on a subset of group-invariant items called designated anchors. In this research, a quick and easy strategy for empirically selecting designated anchors is proposed and evaluated in simulations. Although the proposed rank-based approach is applicable to any method for DIF testing, this article focuses on likelihood-ratio (LR) comparisons between nested two-group item response models. The rank-based strategy frequently identified a group-invariant designated anchor set that produced more accurate LR test results than those using all other items as anchors. Group-invariant anchors were more difficult to identify as the percentage of differentially functioning items increased. Advice for practitioners is offered.

Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities.

The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the population distribution. A simulation study shows that the new procedure is feasible in practice, and that when the latent distribution is not well approximated as normal, two-parameter logistic (2PL) item parameter estimates and expected a posteriori scores (EAPs) can be improved over what they would be with the normal model. An example with real data compares the new method and the extant empirical histogram approach.

Factor Analysis of Scales Composed of Binary Items: Illustration with the Maudsley Obsessional Compulsive Inventory

It is well known that traditional factor analytic methods are designed for use with continuous data, and suboptimal for items with 2 response options (i.e., binary items). Nevertheless, traditional methods have been employed in all previous assessment of the dimensionality of the Maudsley Obsessional Compulsive Inventory (MOCI), a true/false measure of obsessive–compulsive symptoms ( R. J. Hodgson &; S. Rachman, 1977). The aim of this paper is to illustrate 2 techniques that are more suitable for factor-analyzing binary items than traditional methods, through application to the MOCI (n = 1,080). Computer files for use with the TESTFACT (D. Wilson, R. L. Wood, &; R. Gibbons, 1991 ) and Mplus (Muthén &; Muthén, 1998) computer programs are provided. Results from an inappropriately applied principal axis factor analysis are presented for comparison, and factor structures, loadings, and interfactor correlations are compared across methods.

The Langer-Improved Wald Test for DIF Testing With Multiple Groups Evaluation and Comparison to Two-Group IRT

Differential item functioning (DIF) occurs when the probability of responding in a particular category to an item differs for members of different groups who are matched on the construct being measured. The identification of DIF is important for valid measurement. This research evaluates an improved version of Lord’s χ2 Wald test for comparing item response model parameter estimates between two groups. The improved version uses better approaches for computation of the covariance matrix and equating the item parameters across groups. There are two equating algorithms implemented in IRTPro and flexMIRT software: Wald-1 (one-stage) and Wald-2 (two-stage), only one of which has been studied in simulations before. The present study evaluates for the first time the Wald-1 algorithm and Wald-1 and Wald-2 for three groups simultaneously. A comparison to two-group IRT-LR-DIF is included. Results indicate that Wald-1 performs very well and is recommended, whereas Type I error is extremely inflated for Wald-2. Performance of IRT-LR-DIF and Wald-1 was similar, even for three groups.