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Copyright of Turkish Journal of Medical Sciences is the property of Scientific and Technical Research Council of Turkey and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: An important aspect of the ‘description’ of a variable is the shape of its distribution, which tells you the frequency of values from different ranges of the variable. Typically, as most of the statistical tests are based on the normality assumption, a researcher is interested in how well the distribution can be approximated by the normal distribution. Unless there are extreme violations of the normality assumptions, approved statistical tests usually provide accurate results. Although simple descriptive statistics can provide some information relevant to this issue, more precise information can be obtained by performing one of the tests of normality to determine whether the sample comes from a normally distributed population or not. Aim: Lilliefors corrected Kolmogorov-Smirnov, Shapiro-Wilk, D'Agostino Pearson and Jarqua-Bera tests were aimed to be compared in terms of Type I error and power of the tests. Materials and Methods: The simulation was run 1000 times for 23 different sample sizes and for 8 different distributions. Lilliefors corrected Kolmogorov-Smirnov, Shapiro-Wilk, D'Agostino Pearson and Jarqua-Bera tests were compared in terms of Type I error and power of the tests. Results: The most powerful results for normal distributions were given by the Jarqua-Bera and for nonnormal distributions by the Shapiro-Wilk test. Conclusions: As it had the lowest Type I error rate, the Jarqua-Bera test was superior for normal and standard normal distributions. For nonnormal distributions, achieving sufficient power at smaller sample sizes, the Shapiro-Wilk was the most powerful. [ABSTRACT FROM AUTHOR]

Background/aim: The multidimensional evaluation of patients with chronic neck pain is important for planning the treatment program. The aim of this study was to investigate the validity and reliability of the Turkish version of the Neck Bournemouth Questionnaire (NBQ)., Materials and Methods: The internal construct validity of the NBQ was examined by the fit of the data to the Rasch measurement model. External validity of the NBQ was evaluated by testing for expected associations of Rasch transformed NBQ score with the corresponding variables through the process of convergent validity. The reliability of the NBQ in terms of both internal consistency and test-retest reliability was assessed by the person separation index (PSI) and differential item functioning (DIF) by time effect., Results: It was determined that the questionnaire has 2 factors. None of the items of Factor 1 (F1) and Factor 2 (F2) showed DIF. The reliability of F1 (Cronbach’s alpha = 0.89, PSI = 0.87) and F2 (Cronbach’s alpha = 0.77, PSI = 0.87) was good with Cronbach’s alpha and PSI. There was a good correlation between NBQ/F1 and the Neck Disability Index (NDI) (r = 0.673) and Neck Pain and Disability Scale (NPDS) (r = 0.709). Also, there was a correlation between NBQ/F2 and the Beck Depression Inventory (BDI) (r = 0.552) and Beck Anxiety Inventory (BAI) (r = 0.410)., Conclusion: The Turkish version of the Neck Bournemouth Questionnaire is valid and reliable., Competing Interests: none declared, (This work is licensed under a Creative Commons Attribution 4.0 International License.)