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Establishing Roots Before Branching Out: Parameter Recovery In Item Response Tree Models, Tyler Ryan
Establishing Roots Before Branching Out: Parameter Recovery In Item Response Tree Models, Tyler Ryan
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Item Response Trees are a type of item response model that incorporates information about conditional responding to items using a rooted tree graph structure. Researchers have used item response trees for common measurement tasks and for testing novel hypotheses. Previous simulation studies investigating item response trees either lack generalizability to the broad domain of their use or lack thorough investigation and reporting of the results. I conducted a simulation study to explore how sample size, test length, item characteristics, and tree structure affect both item and person parameter recovery for 1PL and 2PL models. The results suggested that, as with …
Comparing Dichotomous And Polytomous Items Using Item Response Trees, Daniel Jenkins
Comparing Dichotomous And Polytomous Items Using Item Response Trees, Daniel Jenkins
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Research on the optimal number of response options on graphic rating scales has yielded mixed results such as that more scale points are better; there is an optimal range; or that it does not matter. The present study compared the psychometric properties of dichotomous and polytomous personality items using several methods of scoring including summed scores, item response theory (IRT), and item response trees. It was found that regression models based on dichotomous items explained similar amounts of variance in careless responding as models based on polytomous items. In addition, scores from dichotomous models were more closely related to the …
Detecting Insufficient Effort Responding: An Item Response Theory Approach, Tyler Douglas Barnes
Detecting Insufficient Effort Responding: An Item Response Theory Approach, Tyler Douglas Barnes
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Insufficient Effort Responding (IER) is prevalent enough in self-report data to cause issues with construct validity. There are many ways to detect IER, but they are less than ideal as they each detect different forms of IER. I compared an Item Response Theory (IRT) approach consisting of the lz person-fit statistic and the Person Fluctuation Parameter (PFP) to longstring, non-consecutive longstring, even-odd split, and psychological synonyms indices. I simulated 3200 samples with one of four types of random responding: consecutive responding, non-consecutive patterned responding, random responding following a normal distribution, and random responding following a uniform distribution. Also, I generated …
Using Differential Functioning Of Items And Tests (Dfit) To Examine Targeted Differential Item Functioning, Erin L. O'Brien
Using Differential Functioning Of Items And Tests (Dfit) To Examine Targeted Differential Item Functioning, Erin L. O'Brien
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Current studies of differential item functioning (DIF) look at look at how groups differ in responding to items across an entire trait continuum. This is important for detecting the presence of consistent patterns of responses across items between groups of people. Current tests of DIF are limited in that they only detect differences between groups across all levels of the trait. However, selection decisions are usually made within specific ranges of trait levels. The purpose of this research was to determine if restricting theta values in an existing framework would be better at detecting DIF as current methods for restricted …
Do Applicants And Incumbents Respond To Personality Items Similarly? A Comparison Using An Ideal Point Response Model, Erin L. O'Brien
Do Applicants And Incumbents Respond To Personality Items Similarly? A Comparison Using An Ideal Point Response Model, Erin L. O'Brien
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This study examined the extent to which applicants and incumbents use different response processes when responding to personality items. It was hypothesized that applicants' responses to personality items will be more similar to a dominance response model and that incumbents' responses will be more similar to an ideal point response model. I used item response theory to estimate sample data from applicants (N = 1509) and incumbents (N = 1568) who completed the Sixteen Personality Questionnaire Select. Differential item (DIF) and test functioning (DTF) analyses were conducted using the generalized graded unfolding model (GGUM), which is based on ideal point …
The Development Of The Wright Work Engagement Scale, Gene Michael Alarcon
The Development Of The Wright Work Engagement Scale, Gene Michael Alarcon
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Recent developments in organizational attitude research have focused on the concept of engagement. Despite the growing literature on engagement there is little agreement on the conceptualization of engagement. The current study sought to conceptualize and measure work engagement using Item Response Theory. The Wright Work Engagement Scale was created using two samples, a student sample for exploratory analyses and a working sample for item analyses. Results indicate engagement is a unidimensional construct. The 12 item Work Engagement Scale was created and demonstrated sufficient convergent and discriminant validity.
Type I Error Rates And Power Estimates For Several Item Response Theory Fit Indices, Bradley R. Schlessman
Type I Error Rates And Power Estimates For Several Item Response Theory Fit Indices, Bradley R. Schlessman
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Despite frequent use of the adjusted chi-square to degrees of freedom ratio (χ2/df) test for Item Response Theory fit (Drasgow, Levine, Tsien, Williams. and Mead, 1995), there remains a lack of empirical testing of the statistic's Type I error rates and power. The present study compared the adjusted χ2/df test to two other commonly used IRT fit statistics. The other fit indices examined were S-χ2 (Orlando and Thissen, 2000) and χ2* (Stone's, 2000). This study also addressed misfit based on the possibility that the item responses analyzed were created based on a different response process than that assumed by the …
Item And Person Characteristics As Predictors Of Faking, Nicholas Tyler Day
Item And Person Characteristics As Predictors Of Faking, Nicholas Tyler Day
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Applicants may be more motivated to fake than incumbents and may fake more on some items than others. The present study investigated both item and person characteristics as predictors of faking. At the item level, both item transparency and job-relevance were hypothesized to be associated with higher levels of faking. In contrast, item verifiability was hypothesized to be associated with lower levels of faking. At the person level, applicants were expected to have a higher prevalence of faking than incumbents. Data was taken from an existing pool of applicants (n = 507) and incumbents (n = 302) at a customer …