Christine E. DeMars
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View article: From Item Estimates to Test Operations: The Cascading Effect of Rapid Guessing
From Item Estimates to Test Operations: The Cascading Effect of Rapid Guessing Open
Inadequate test‐taking effort poses a significant challenge, particularly when low‐stakes test results inform high‐stakes policy and psychometric decisions. We examined how rapid guessing (RG), a common form of low test‐taking effort, bias…
View article: Another Look at Yen's Q3: Is .2 an Appropriate Cut‐Off?
Another Look at Yen's Q3: Is .2 an Appropriate Cut‐Off? Open
This study examined the widely used threshold of .2 for Yen's Q3, an index for violations of local independence. Specifically, a simulation was conducted to investigate whether Q3 values were related to the magnitude of bias in estimates o…
View article: Treating Noneffortful Responses as Missing
Treating Noneffortful Responses as Missing Open
This study investigates the treatment of rapid-guess (RG) responses as missing data within the context of the effort-moderated model. Through a series of illustrations, this study demonstrates that the effort-moderated model assumes missin…
View article: Item Parameter Recovery: Sensitivity to Prior Distribution
Item Parameter Recovery: Sensitivity to Prior Distribution Open
Marginal maximum likelihood, a common estimation method for item response theory models, is not inherently a Bayesian procedure. However, due to estimation difficulties, Bayesian priors are often applied to the likelihood when estimating 3…
View article: A Note on the Relation Between the Angle of the Reference Composite and Liu, Li, and Liu’s Method 4 for Domain Scores
A Note on the Relation Between the Angle of the Reference Composite and Liu, Li, and Liu’s Method 4 for Domain Scores Open
In this note, I show how Liu, Li, and Liu's Method 4 for estimating domain scores yields results very similar to Wang's derivation of the reference composite. Liu, Li, and Liu's method is a simple way to obtain the composite.
View article: A Note on the Odds Ratio DIF Index
A Note on the Odds Ratio DIF Index Open
Jin, Chen, and Wang (2018) proposed using the log of the odds ratio (OR) as a DIF index for item responses that follow the Rasch model. The OR is relatively simple to calculate and does not require grouping examinees by ability. This index…
View article: An Updated Recommendation for Multiple Comparisons
An Updated Recommendation for Multiple Comparisons Open
Instructors of introductory and intermediate statistics courses often teach the use of analysis of variance (ANOVA) for the purpose of comparing more than two group means and pairwise comparison procedures (PCPs) to determine which group m…
View article: Revised Parallel Analysis With Nonnormal Ability and a Guessing Parameter
Revised Parallel Analysis With Nonnormal Ability and a Guessing Parameter Open
Previous work showing that revised parallel analysis can be effective with dichotomous items has used a two-parameter model and normally distributed abilities. In this study, both two- and three-parameter models were used with normally dis…
View article: Examining the Performance of the Metropolis–Hastings Robbins–Monro Algorithm in the Estimation of Multilevel Multidimensional IRT Models
Examining the Performance of the Metropolis–Hastings Robbins–Monro Algorithm in the Estimation of Multilevel Multidimensional IRT Models Open
The purpose of this study was to examine the performance of the Metropolis–Hastings Robbins–Monro (MH-RM) algorithm in the estimation of multilevel multidimensional item response theory (ML-MIRT) models. The accuracy and efficiency of MH-R…
View article: Multilevel IRT: When is local independence violated?
Multilevel IRT: When is local independence violated? Open
Calibration data often is often collected within schools. This illustration shows that random school effects for ability do not bias IRT parameter estimates or their standard errors. However, random school effects for item difficulty lead …