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    A Comparison of Propensity Score Weighting Methods for Evaluating the Effects of Programs With Multiple Versions
    (Routledge Journals, Taylor & Francis Ltd, 2019) Leite, Walter L.; Aydin, Burak; Gurel, Sungur
    This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove selection bias. The results indicate that inverse probability of treatment weighting (IPTW) removes the most bias, followed by optimal full matching (OFM), and marginal mean weighting through stratification (MMWTS). The study also compared standard error estimation with Taylor series linearization, bootstrapping and the jackknife across propensity score methods. With IPTW, these standard error estimation methods performed adequately, but standard errors estimates were biased in most conditions with OFM and MMWTS.
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    A Preliminary Study to Evaluate the Reproducibility of Factor Analysis Results: The Case of Educational Research Journals in Turkey
    (Assoc Measurement & Evaluation Education & Psychology, 2019) Aydin, Burak; Kaplan, Mehmet; Atilgan, Hakan; Gurel, Sungur
    In quantitative research, an attempt to reproduce previously reported results requires at least a transparent definition of the population, sampling method, and the analyses procedures used in the prior studies. Focusing on the articles published between 2010 and 2017 by the four prestigious educational research journals in Turkey, this study aimed to investigate the reproducibility of the factor analysis results from a theoretical perspective. A total of 275 articles were subject to descriptive content analysis. Results showed that 77.8% of the studies did not include an explicit definition of the population under interest, and in 50.9% of the studies, the sampling method was either not clear or reported to be convenience sampling. Moreover, information about the missing data or a missing data dealing technique was absent in the 76% of the articles. Approximately, half of the studies were found to have inadequate model fit. Furthermore, in almost all studies, it could not be determined whether the item types (i.e., levels of measurement scales) were taken into consideration during the analyses. In conclusion, the majority of the investigated factor analysis results were evaluated to be non-reproducible in practice.