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Full-Text Articles in Applied Statistics
A Bayesian Beta-Mixture Model For Nonparametric Irt (Bbm-Irt), Ethan A. Arenson, George Karabatsos
A Bayesian Beta-Mixture Model For Nonparametric Irt (Bbm-Irt), Ethan A. Arenson, George Karabatsos
Journal of Modern Applied Statistical Methods
Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. A simple and more flexible Bayesian nonparametric IRT model for dichotomous items is introduced, which constructs monotone item characteristic (step) curves by a finite mixture of beta distributions, which can support the entire space of monotone curves to any desired degree of accuracy. An adaptive random-walk Metropolis-Hastings algorithm is proposed to estimate the posterior distribution of the model parameters. The Bayesian IRT …
Assessing The Ordinality Of Response Bias With Item Response Models: A Case Study Using The Phq-9, Venessa N. Singhroy
Assessing The Ordinality Of Response Bias With Item Response Models: A Case Study Using The Phq-9, Venessa N. Singhroy
Dissertations, Theses, and Capstone Projects
Improper scale usage in psychological and clinical assessment is an important problem. If respondents do not use the scales in a consistent manner, the reliability of a composite is likely to be attenuated. This is particularly problematic when particular items are singled out for special treatment or when subscales are of interest, not just a total score. This study used both non-parametric and parametric item response theory (IRT) methods to gain further insight into the validity of the PHQ-9, a dual purpose instrument that assesses the severity of depressive symptoms using nine Likert-scale items and allows the investigator to establish …
The Use Of Item Response Theory In Survey Methodology: Application In Seat Belt Data, Mark K. Ledbetter, Norou Diawara, Bryan E. Porter
The Use Of Item Response Theory In Survey Methodology: Application In Seat Belt Data, Mark K. Ledbetter, Norou Diawara, Bryan E. Porter
Mathematics & Statistics Faculty Publications
Problem: Several approaches to analyze survey data have been proposed in the literature. One method that is not popular in survey research methodology is the use of item response theory (IRT). Since accurate methods to make prediction behaviors are based upon observed data, the design model must overcome computation challenges, but also consideration towards calibration and proficiency estimation. The IRT model deems to be offered those latter options. We review that model and apply it to an observational survey data. We then compare the findings with the more popular weighted logistic regression. Method: Apply IRT model to the observed data …