A multigroup item response theory analysis of the psychopathy checklist--revised

Item response theory was used to investigate the functioning of the Psychopathy Checklist-Revised (PCL-R; R. D. Hare, 1991, 2003) in several offender populations. With male criminal offenders (N=3,847) as a reference group, differential item functioning analyses were performed for 3 comparison groups: female criminal offenders (N=1,219), male forensic psychiatric patients (N=1,246), and male criminal offenders scored from file reviews (N=2,626). Results are discussed in the context of the 2-factor, 4-facet model for the PCL-R (R. D. Hare, 2003; J. Parker, G. Sitarenios, & R. D. Hare, 2003). Application of a multigroup graded response model to all 4 groups suggests scalar equivalence may hold at least approximately for each population, although the PCL-R provided slightly greater information about the latent trait of psychopathy for male criminal offenders scored from the standard procedure.     

解释性项目反应理论模型：理论与应用

解释性项目反应理论模型(Explanatory Item Response Theory Models, EIRTM)是指基于广义线性混合模型和非线性混合模型构建的项目反应理论(Item Response Theory, IRT)模型。EIRTM能在IRT模型的基础上直接加入预测变量, 从而解决各类测量问题。首先介绍EIRTM的相关概念和参数估计方法, 然后展示如何使用EIRTM处理题目位置效应、测验模式效应、题目功能差异、局部被试依赖和局部题目依赖, 接着提供实例对EIRTM的使用进行说明, 最后对EIRTM的不足之处和应用前景进行讨论。     

An application of item response theory to alexithymia assessment among abstinent alcoholics.

An item response theory (IRT) model identified three dimensions assessed by the Toronto Alexithymia Scale (TAS) in a sample of 130 male applicants for inpatient care at a Veterans Administration (VA) medical center alcoholism treatment program. A unidimensional solution did not capture all of alexithymia's theoretical features. Subjects with lower alexithymia scores gave positive responses to items tapping emotional awareness deficits; only those with higher alexithymia scores gave positive responses to items tapping external, operative cognitive style. Thus, a total TAS score may not represent alexithymia accurately in substance-abusing patient populations.     

An introduction to mixture item response theory models

Mixture item response theory (IRT) allows one to address situations that involve a mixture of latent subpopulations that are qualitatively different but within which a measurement model based on a continuous latent variable holds. In this modeling framework, one can characterize students by both their location on a continuous latent variable as well as by their latent class membership. For example, in a study of risky youth behavior this approach would make it possible to estimate an individual's propensity to engage in risky youth behavior (i.e., on a continuous scale) and to use these estimates to identify youth who might be at the greatest risk given their class membership. Mixture IRT can be used with binary response data (e.g., true/false, agree/disagree, endorsement/not endorsement, correct/incorrect, presence/absence of a behavior), Likert response scales, partial correct scoring, nominal scales, or rating scales. In the following, we present mixture IRT modeling and two examples of its use. Data needed to reproduce analyses in this article are available as supplemental online materials at http://dx.doi.org/10.1016/j.jsp.2016.01.002.     

Summed-score linking using item response theory: application to depression measurement

An item response theory (IRT) approach to test linking based on summed scores is presented and demonstrated by calibrating a modified 23-item version of the Center for Epidemiologic Studies Depression Scale (CES-D) to the standard 20-item CES-D. Data are from the Depression Patient Outcomes Research Team, II, which used a modified CES-D to measure risk for depression. Responses (N = 1,120) to items on both the original and modified versions were calibrated simultaneously using F. Samejima's (1969, 1997) graded IRT model. The 2 scales were linked on the basis of derived summed-score-to-IRT-score translation tables. The established cut score of 16 on the standard CES-D corresponded most closely to a summed score of 20 on the modified version. The IRT summed-score approach to test linking is a straightforward, valid, and practical method that can be applied in a variety of situations.     

An application of item response theory to the DSM-III-R criteria for borderline personality disorder

This paper summarizes results from analyses of the DSM criteria for borderline personality disorder (BPD) using models from item response theory (IRT). The study sample consisted of 353 participants, the majority of whom were psychiatric patients. Confirmatory factor analysis showed that a one-factor model provided the best fit to the data. All the DSM BPD criteria had moderate or higher item discrimination parameters, indicating that all items contributed meaningful information in assessing BPD. Item information functions revealed that the BPD criteria as a whole were useful for capturing BPD traits in the moderately severe to severe range, but that they performed less well in the less severe range. The general conclusion is that the criteria do represent a coherent syndrome and that further research on the informational value of the individual criteria would be useful.     

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.     

An application of item response theory analysis to alcohol, cannabis, and cocaine criteria in DSM-IV

Item response theory (IRT) is supplanting classical test theory as the basis for measures development. This study demonstrated the utility of IRT for evaluating DSM-IV diagnostic criteria. Data on alcohol, cannabis, and cocaine symptoms from 372 adult clinical participants interviewed with the Composite International Diagnostic Interview--Expanded Substance Abuse Module (CIDI-SAM) were analyzed with Mplus (B. Muthen & L. Muthen, 1998) and MULTILOG (D. Thissen, 1991) software. Tolerance and legal problems criteria were dropped because of poor fit with a unidimensional model. Item response curves, test information curves, and testing of variously constrained models suggested that DSM-IV criteria in the CIDI-SAM discriminate between only impaired and less impaired cases and may not be useful to scale case severity. IRT can be used to study the construct validity of DSM-IV diagnoses and to identify diagnostic criteria with poor performance.     

An investigation of hierarchical Bayes procedures in item response theory

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item and ability parameters. Simulated data sets were analyzed via two joint and two marginal Bayesian estimation procedures. The marginal Bayesian estimation procedures yielded consistently smaller root mean square differences than the joint Bayesian estimation procedures for item and ability estimates. As the sample size and test length increased, the four Bayes procedures yielded essentially the same result.The authors wish to thank the Editor and anonymous reviewers for their insightful comments and suggestions.     

An item response theory analysis of the narcissistic personality inventory

This research uses item response theory methods to evaluate the Narcissistic Personality Inventory (NPI; Raskin & Terry, 1988). Analyses using the 2-parameter logistic model were conducted on the total score and the Corry, Merritt, Mrug, and Pamp (2008) and Ackerman et?al. (2011) subscales for the NPI. In addition to offering precise information about the psychometric properties of the NPI item pool, these analyses generated insights that can be used to develop new measures of the personality constructs embedded within this frequently used inventory.     

The impact of social desirability bias on the EPQ-R item scores: An item response theory analysis

This study assessed the potential influence of social desirability (SD) response bias on the E, N, and P EPQ-R scores at the level of individual items. The study was based on a bidimensional IRT model which was fitted in a large sample. This allowed a detailed analysis of both the internal validities of the items and the content of the items which were most affected by SD. The E items were least affected by SD, but the direction of the impact depended on the type of item. As expected, in the N and P cases the relations obtained were consistently negative, but the strength of the SD impact also depended considerably on the type of item. The P scale was the most problematic in terms of convergent and discriminant validity.     

Sex-role attitudes across two cultures: United States and India

This study tests whether students from India hold more traditional sex role attitudes compared to students from the US, whether women from either country hold more liberal sex role attitudes than males, and whether socioeconomic and demographic factors are better predictors of sex role attitudes among women of either culture. Data were obtained in 1978 from a sample of 409 undergraduate students from three Mississippi colleges in the US and 419 undergraduate and graduate students from three educational institutions in Andhra Pradesh, India. Sex role attitudes are measured by scaling developed by Scanzoni (1975). Out of a total possible score of 100, the mean values are 69.09 for the US sample and 53.62 for the Indian sample. Differences between the means for all 20 sex role attitudes are statistically significant. Results indicate that US females and Indian females had less traditional sex role attitudes than their respective counterparts. Mother role, wife role, father role, and total sex role attitude were more traditional among males in India compared to males in the US and among females in India compared to females in the US. More traditional attitudes were held by males in India with lower educated fathers and unemployed mothers. Religion was the only variable significantly related to Indian female students. In the US, traditional sex role attitudes of males were significantly related to high maternal income and residence in urban areas. More traditional sex role attitudes among US females were related to increasing age and marital status. Stepwise analysis reveals that the most powerful explanatory factors were sex and mother's occupation among Indian students and sex, father's income, and year in college among US students. What little variance was explained was explained by more variables in the US sample, and the best model predictors explained more variance in the US sample.     

群体水平IRT模型及其应用——兼与IRT的比较

传统上,群体评估都是以个体的评估结果的平均值为基础进行的。而群体水平IRT理论则可以避开对个体的评估,直接实现对群体的评估,它具有许多传统方法难以企及的优点。本文将群体水平IRT模型应用于2007年某省高考英语阅读理解的410所学校的能力评估,评估结果发现：410所学校的英语阅读理解能力几乎都在[-1,1]区间内,没有能力极高或极低的学校。对这些学校而言,测验中所有项目的难度较易,区分度适中。所有的评估结果与IRT模型的评估结果在 的水平上相关显著,表明GIRT模型在实践中是可以选择的一种群体评估方法。     

An item response theory analysis of self-report measures of adult attachment

Self-report measures of adult attachment are typically scored in ways (e.g., averaging or summing items) that can lead to erroneous inferences about important theoretical issues, such as the degree of continuity in attachment security and the differential stability of insecure attachment patterns. To determine whether existing attachment scales suffer from scaling problems, the authors conducted an item response theory (IRT) analysis of 4 commonly used self-report inventories: Experiences in Close Relationships scales (K. A. Brennan, C. L. Clark, & P. R. Shaver, 1998), Adult Attachment Scales (N. L. Collins & S. J. Read, 1990), Relationship Styles Questionnaire (D. W. Griffin & K. Bartholomew, 1994) and J. Simpson's (1990) attachment scales. Data from 1,085 individuals were analyzed using F. Samejima's (1969) graded response model. The authors' findings indicate that commonly used attachment scales can be improved in a number of important ways. Accordingly, the authors show how IRT techniques can be used to develop new attachment scales with desirable psychometric properties.     

An item response theory analysis of the Problem Gambling Severity Index

Increases in the availability of gambling heighten the need for a short screening measure of problem gambling. The Problem Gambling Severity Index (PGSI) is a brief measure that allows for the assessment of characteristics of gambling behavior and severity and its consequences. The authors evaluate the psychometric properties of the PGSI using item response theory methods in a representative sample of the urban adult population in South Africa (N = 3,000). The PGSI items were evaluated for differential item functioning (DIF) due to language translation. DIF was not detected. The PGSI was found to be unidimensional, and use of the nominal categories model provided additional information at higher values of the underlying construct relative to a simpler binary model. This study contributes to the growing literature supporting the PGSI as the screen of choice for assessing gambling problems in the general population.     

General mixture item response models with different item response structures: Exposition with an application to Likert scales

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person’s responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category (“neither agree nor disagree”) is taken to be qualitatively similar to the other categories, and is taken to provide information about the person’s endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person’s willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.