No abstract available
Sample Size*

No abstract available.
Sample Size*

No abstract available.
Sample Size*

At first, we review a sample size estimation method for log-rank test in survival analysis. Although it is widely used these days, it has a weakness for practical use. We propose a modification method to avoid the weakness.
Sample Size*

No abstract available.
Analysis of Variance* ; Sample Size*

Repeated measures designs are widely used in the field of anesthesiology because they allow the detection of within-person change over time and provide a higher statistical power for detecting differences than a single measure design while reducing the costs and efforts to conduct a study. However, the complex process of calculating the sample size for repeated measures design requires profound statistical knowledge and also programming skills in some instances. In the present article, the author describes 1) the basic statistics for repeated measures design, 2) the explanation for G Power software, and 3) how to calculate the sample size using an example.
Anesthesiology ; Sample Size*

The purpose of clinical trials is to find evidences for the effects of experimental new drugs or treatments on human. For the successful clinical trials, it is not sufficient to use statistics only for the analyses of collected data, but it is necessary to extend the usage of statistics in various ways. At the beginning of the study, one needs to use statistics for systematically and concretly planning the study. For this, we discussed the usage of statistics in defining the effect, determining the sample size, statistical analyses, and so on.
Humans ; Sample Size

The proper use of statistics in medical studies is very important to draw an objective conclusion. The misuse and misunderstanding of statistics degrade the quality of scientific results. Authors should make an effort to choose proper statistical procedures and report the results appropriately. In this article, we review and summarize aspects of statistical consideration in preparing for publication in medical journals.
Publications ; Sample Size

Sample size computations, which should be done at the planning stage of the study, are necessary for research to estimate a population parameter or test a hypothesis. For causal analysis of observational databases, sample size computations are generally not needed. Post-hoc power analyses, which are typically done with non-significant findings, should not be performed since reporting post-hoc power is nothing more than reporting p values differently. While sample size calculations are typically based on the tradition of significance testing, sample size calculations based on precision are feasible – if not preferred – alternatives. Sample size calculations depend on several factors such as the study objective, scale of measurement of the outcome variable, study design, and sampling design. Computing for sample size is not as straightforward as presented in textbooks but specific strategies may be resorted to in the face of challenges and constraints.
Sample Size ; Power, Psychological

PURPOSE: Use of inappropriate statistical methods may lead to incorrect conclusions and a waste of valuable resources. The goal of this study was to assess the frequency and the types of several common statistical errors in the published articles of the Journal of the Korean Academy of Prosthodontics (JKAP) for a 5-year period. MATERIALS AND METHODS: Of 336 articles in the JKAP published from 2006 to 2010, 255 articles using statistics were reviewed and classified by statistical method and year. The frequency and types of the statistical methods were examined, and the statistical errors were evaluated by the appropriateness of the experimental design, assumption check, independent outcomes, proper sample size and suitable use of statistical method. Statistical guidelines were completed based on the appropriateness. RESULTS: Of the 255 articles using statistics, 193 articles (75.9%) used inferential statistics and 153 articles used SPSS statistical software (60.0%). Of the articles using inferential statistics, the three most frequently used statistical methods were ANOVA (41.5%), t-test (20.0%), and the nonparametric method (16.9%). The average rate of statistical errors was 61.2 percent, similar to the rate reported by several studies completed for the medical journal. CONCLUSION: After the whole analysis of the difference among the groups, post-hoc tests for the pairwise comparisons are required. The optimal sample size calculation is an essential part of this study protocol. To minimize the occurrence of statistical errors, statistical guidelines were developed according to each statistical test procedure and will contribute to the academic improvement in the JKAP.
Prosthodontics ; Research Design ; Sample Size