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    Bibliometric Analysis of Social Desirability
    (Karabuk Univ, 2020) Yurtcu, Meltem; Kocoglu, Erol
    Several studies conducted to measure and determine the perceptions of the individual and the society on various issues presented and compared numerical sociological and psychological finding data. The perceptions determined about the study subject are influenced by social desirability, one of the personality inventory elements. The study was based on the visualization of the descriptive structure. In the study, CiteSpace software was used to develop and visualize the network structure. Web of Science database was used in CiteSpace software. Web of ScienceTM core collection database was searched for the term Social Desirability with abstract, author keywords, and Keywords Plus forms. In total, 5,489 studies on the subject were accessed. These studies were conducted in a total of 171 different fields including psychology, management, health, and educational research. The findings demonstrated that the concept of social desirability was comprehensively studied in various fields, and a knowledge map was developed based on these various fields.
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    Comparison of Item Response Theory Scaling Methods with ROC Analysis
    (Assoc Measurement & Evaluation Education & Psychology, 2022) Yurtcu, Meltem; Guzeller, Cem Oktay
    In this study, one-dimensional item response theory models were evaluated using different scaling methods. In this context, the equating errors and the area under the curve of four scaling methods (Stocking-Lord, Heabara, Mean-Sigma, Mean-Mean), and one, two, and three parameters logistic models (1PL, 2PL, and 3PL) in nonequivalent groups with anchor test (NEAT) design were examined. Additionally, the equating errors of the scaling methods and the results obtained from ROC analysis were compared. Qatar's and Australia's PISA 2012 mathematical literacy test data were used in the study. The minimum error was obtained from the Mean-Mean method with the 1PL model, and the maximum error was obtained from the Mean-Mean method with the 3PL model. Similar results were observed in all comparisons and supported each other. It is concluded that ROC analysis can be used to compare different conditions, methods and models.
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    The Comparison of the Equated Tests Scores by Various Covariates using Bayesian Nonparametric Model
    (Assoc Measurement & Evaluation Education & Psychology, 2021) Yurtcu, Meltem; Kelecioglu, Hulya; Boone, Edward
    This research is based on obtaining equated scores by using covariates in the Bayesian nonparametric model. As covariates in the study, gender, mathematics self-efficacy scores, and common item scores were used. The distributions were obtained for all score groups. Hellinger Distance was calculated to obtain the distances between the distributions of equated scores by using covariates and the distribution of the target test scores. These distances were compared with the distributions of equated scores obtained from methods based on Item Response Theory. The study was conducted on Canadian and Italian samples of Programme for International Student Assessment (PISA) 2012. PARSCALE and IRTEQ were used for classical methods, and R was used for Bayesian nonparametric model. When gender, mathematics self-efficacy scores, and common item scores were used as covariates in the model, distance values of obtained equated scores to target test scores were close to each other, but their distributions were different. The closest distribution to target test scores was achieved when gender and mathematics self-efficacy scores were used together as covariates in the model, and the farthest distributions were obtained from item response theory methods. As a result of the research, it was determined that the model is more informative than the classical methods.
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    The comparison of the scores obtained by Bayesian nonparametric model and classical test theory methods*
    (Sage Publications Ltd, 2021) Yurtcu, Meltem; Kelecioglu, Hulya; Boone, Edward L.
    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.