Results 11 to 20 of about 69 (67)
A Mixture Rasch Model Analysis of Data from a Survey of Novice Teacher Core Competencies
International Journal of Contemporary Educational Research, 2023 Although the Rasch model is used to measure latent traits like attitude or ability where there are multiple latent structures within the dataset it is best to use a technique called the Mixture Rasch Model (MRM) which is a combination of a Rasch model and a latent class analysis (LCA). This study used data from a survey for teachers, teacher candidates,
Turker Toker, Kent Seıdel
openaire +2 more sources
Mixture Rasch Model with Main and Interaction Effects of Covariates on Latent Class Membership
International Journal of Assessment Tools in Education, 2019 Covariates have been used in mixture IRT models to help explain why examinees are classed into different latent classes. Previous research has considered manifest variables as covariates in a mixture Rasch analysis for prediction of group membership. Latent covariates, however, are more likely to have higher correlations with the latent class variable.
Tugba KARADAVUT +2 more
openaire +5 more sources
INSAN Jurnal Psikologi dan Kesehatan MentalThis study aimed to test the reliability and validity of the Indonesian-translated Body Regulation Exercise Questionnaire (BREQ-3), originally developed by Wilson et al. (2006), using Rasch analysis. A total of 408 Indonesian participants aged 18–25 years completed the survey. The results supported the unidimensionality of each BREQ-3 subscale.
Bryan Andika +2 more
openaire +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
A mixture Rasch facets model for rater’s illusory halo effects
Behavior Research Methods, 2022A rater's overall impression of a ratee's essay (or other assessment) can influence ratings on multiple criteria to yield excessively similar ratings (halo effect). However, existing analytic methods fail to identify whether similar ratings stem from homogeneous criteria (true halo) or rater bias (illusory halo).
Kuan-Yu Jin, Ming Ming Chiu
openaire +2 more sources
Applying a Mixture Rasch Model‐Based Approach to Standard Setting
Educational Measurement: Issues and Practice, 2023AbstractThe subjective aspect of standard‐setting is often criticized, yet data‐driven standard‐setting methods are rarely applied. Therefore, we applied a mixture Rasch model approach to setting performance standards across several testing programs of various sizes and compared the results to existing passing standards derived from traditional ...
Michael R. Peabody +2 more
openaire +1 more source
Mixture Distribution Rasch Models
1995This chapter deals with the generalization of the Rasch model to a discrete mixture distribution model. Its basic assumption is that the Rasch model holds within subpopulations of individuals, but with different parameter values in each subgroup. These subpopulations are not defined by manifest indicators, rather they have to be identified by applying ...
Jürgen Rost, Matthias von Davier
openaire +1 more source
Mixture Rasch model for guessing group identification
AIP Conference Proceedings, 2013Several alternative dichotomous Item Response Theory (IRT) models have been introduced to account for guessing effect in multiple-choice assessment. The guessing effect in these models has been considered to be itemrelated. In the most classic case, pseudo-guessing in the three-parameter logistic IRT model is modeled to be the same for all the subjects
Hoo Leong Siow +2 more
openaire +1 more source
Estimation of Mixture Rasch Models from Skewed Latent Ability Distributions
Measurement: Interdisciplinary Research and Perspectives, 2020Mixture Rasch (MixRasch) models conventionally assume normal distributions for latent ability. Previous research has shown that the assumption of normality is often unmet in educational and psychol...
Tugba Karadavut +2 more
openaire +1 more source
Mixture-Distribution and HYBRID Rasch Models
2007This chapter provides an overview of mixture-distribution Rasch models (RMs) and HYBRID RMs and their extensions. Discrete mixture-distribution IRT models assume that the observed data were drawn from an unobservable mixture of populations. Within each of these populations, a different item response model may hold (HYBRID models), or models with ...
Matthias von Davier, Kentaro Yamamoto
openaire +1 more source
A Mixture Rasch Model With a Covariate
Applied Psychological Measurement, 2013Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying ...
openaire +1 more source