Validity and severity thresholds for the depression subscale of the Affective Self Rating Scale: an equipercentile equating study using classical test theory

2021 ◽  
Author(s):  
SJ Sharp ◽  
MA Bond ◽  
KS Chiang ◽  
SJ Collier ◽  
J Farrington ◽  
...  
Keyword(s):  
Rating Scale ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equipercentile Equating ◽  
Classical Test ◽  
Self Rating ◽  
Depression Subscale

Evaluation Properties of the Chinese Version of the Caring Factor Survey-Caring of Manager According to Classical Test Theory and Item Response Theory

2019 ◽  
Vol 23 (4) ◽  
pp. 275-283
Author(s):  
Ling Wang ◽  
John W. Nelson
Keyword(s):  
Item Response Theory ◽  
Psychometric Properties ◽  
Item Response ◽  
Rating Scale ◽  
Item Difficulty ◽  
Classical Test Theory ◽  
Chinese Version ◽  
Test Theory ◽  
Response Theory ◽  
Classical Test

The aim of the study is to evaluate psychometric properties of the Chinese version of Caring Factor Survey-Caring of Manager (CFS-CM), which evaluated by using with classical test theory (CTT) and item response theory (IRT). CTT analyses evaluate include internal consistence reliability, test–retest reliability and construct validity. IRT analyses were conducted to test the unidimensionality, item fit, item difficulty, the reliability, and rating scale analysis. CTT showed good psychometric properties of the CFS-CM. However, IRT revealed some problems of category level. Taking the above issue into consideration, it could be beneficial to perfect the CFS-CM in the future.

scholarly journals Development of the Paranormal and Supernatural Beliefs Scale using classical and modern test theory

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Charlotte E. Dean ◽  
Shazia Akhtar ◽  
Tim M. Gale ◽  
Karen Irvine ◽  
Richard Wiseman ◽  
...  
Keyword(s):  
Rating Scale ◽  
Classical Test Theory ◽  
Test Theory ◽  
Scale Model ◽  
Internal Reliability ◽  
Classical Test ◽  
Classic Test Theory ◽  
Differential Item Functioning Analysis ◽  
Supernatural Beliefs ◽  
Test Retest Reliability

Abstract Background This study describes the construction and validation of a new scale for measuring belief in paranormal phenomena. The work aims to address psychometric and conceptual shortcomings associated with existing measures of paranormal belief. The study also compares the use of classic test theory and modern test theory as methods for scale development. Method We combined novel items and amended items taken from existing scales, to produce an initial corpus of 29 items. Two hundred and thirty-one adult participants rated their level of agreement with each item using a seven-point Likert scale. Results Classical test theory methods (including exploratory factor analysis and principal components analysis) reduced the scale to 14 items and one overarching factor: Supernatural Beliefs. The factor demonstrated high internal reliability, with an excellent test–retest reliability for the total scale. Modern test theory methods (Rasch analysis using a rating scale model) reduced the scale to 13 items with a four-point response format. The Rasch scale was found to be most effective at differentiating between individuals with moderate-high levels of paranormal beliefs, and differential item functioning analysis indicated that the Rasch scale represents a valid measure of belief in paranormal phenomena. Conclusions The scale developed using modern test theory is identified as the final scale as this model allowed for in-depth analyses and refinement of the scale that was not possible using classical test theory. Results support the psychometric reliability of this new scale for assessing belief in paranormal phenomena, particularly when differentiating between individuals with higher levels of belief.

scholarly journals The comparison of the scores obtained by Bayesian nonparametric model and classical test theory methods

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110283
Author(s):  
Meltem Yurtcu ◽  
Hülya Kelecioglu ◽  
Edward L Boone
Keyword(s):  
Classical Test Theory ◽  
Small Sample ◽  
Test Theory ◽  
Nonparametric Model ◽  
Bayesian Nonparametric ◽  
Test Equating ◽  
Classical Test ◽  
A Value ◽  
Item Functioning ◽  
The Individual

Bayesian Nonparametric (BNP) modelling can be used to obtain more detailed information in test equating studies and to increase the accuracy of equating by accounting for covariates. In this study, two covariates are included in the equating under the Bayes nonparametric model, one is continuous, and the other is discrete. Scores equated with this model were obtained for a single group design for a small group in the study. The equated scores obtained with the model were compared with the mean and linear equating methods in the Classical Test Theory. Considering the equated scores obtained from three different methods, it was found that the equated scores obtained with the BNP model produced a distribution closer to the target test. Even the classical methods will give a good result with the smallest error when using a small sample, making equating studies valuable. The inclusion of the covariates in the model in the classical test equating process is based on some assumptions and cannot be achieved especially using small groups. The BNP model will be more beneficial than using frequentist methods, regardless of this limitation. Information about booklets and variables can be obtained from the distributors and equated scores that obtained with the BNP model. In this case, it makes it possible to compare sub-categories. This can be expressed as indicating the presence of differential item functioning (DIF). Therefore, the BNP model can be used actively in test equating studies, and it provides an opportunity to examine the characteristics of the individual participants at the same time. Thus, it allows test equating even in a small sample and offers the opportunity to reach a value closer to the scores in the target test.

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