2017
DOI: 10.3346/jkms.2017.32.7.1072
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Statistical Data Editing in Scientific Articles

Abstract: Scientific journals are important scholarly forums for sharing research findings. Editors have important roles in safeguarding standards of scientific publication and should be familiar with correct presentation of results, among other core competencies. Editors do not have access to the raw data and should thus rely on clues in the submitted manuscripts. To identify probable errors, they should look for inconsistencies in presented results. Common statistical problems that can be picked up by a knowledgeable … Show more

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Cited by 67 publications
(49 citation statements)
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“…The Kolmogorov–Smirnow test is significant accepting the hypothesis of non‐normal distribution of all variables; this suggests that applying DEA in these data collection is suitable. Habibzadeh () recommends using mean for normal distribution and median for non‐normal distribution in the descriptive statistics, then we also observe the median value of variables. In general, the central value of all variables has increasing trend except for the fluctuation of scale of investment, long‐term debts, and total long‐term debts.…”
Section: Research Design and Methodologymentioning
confidence: 59%
“…The Kolmogorov–Smirnow test is significant accepting the hypothesis of non‐normal distribution of all variables; this suggests that applying DEA in these data collection is suitable. Habibzadeh () recommends using mean for normal distribution and median for non‐normal distribution in the descriptive statistics, then we also observe the median value of variables. In general, the central value of all variables has increasing trend except for the fluctuation of scale of investment, long‐term debts, and total long‐term debts.…”
Section: Research Design and Methodologymentioning
confidence: 59%
“…Non-normally distributed data were analyzed using Kruskal-Wallis H test Conover with post hoc test (multigroup comparisons) and Mann-Whitney U test (two-group comparisons). Data are presented as arithmetic means (normally distributed data), geometric means (log-transformed data), or medians (nonnormally distributed data) and accompanied with 95% confidence interval ( CI ) [ 21 ]. Analysis of covariance (ANCOVA) was used to account for potential variation in cell number (expressed as variation in protein concentration between cell lysates) and to discern variables independently associated with examined mediators of apoptosis.…”
Section: Methodsmentioning
confidence: 99%
“…Continuous variables were expressed as median (interquartile range) since they were not normally distributed. Categorical variables were expressed as a number (percentage) [13].…”
Section: Discussionmentioning
confidence: 99%