http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
남정모,정수연 대한의사협회 2012 대한의사협회지 Vol.55 No.6
Most textbooks for biostatistics only explain each individual statistical test with its mathematical formula. However, it is crucial to understand the relationships among the statistical methods and to properly integrate the individual methods to effectively apply them to real clinical research settings. The choice for valid statistical tests greatly depends on the dependency of the sample and the number of independent variables in the analyses as well as the measurement scale of dependent variables and independent variables. In this report, many statistical tests such as the two sample t-test, ANOVA, non-parametric tests, chi-square test, log-rank test, multiple linear regression, logistic regression, mixed model, and Cox regression model are addressed through hypothetical examples. The key for a successful analysis of a clinical experiment is to adopt suitable statistical tests. This study presents a guideline to clinical researchers for selecting valid and powerful statistical tests in their study design. The choice of suitable statistical tests increases the reliability of analytical results and therefore the possibility of accepting a researcher's clinical hypothesis. The proposed flowchart of appropriate tests of statistical inference will be of help to many clinical researchers to their study.
지역간 의료이용 변이지표의 통계학적 분포와 검정에 대한 연구
남정모,조우현,이선희,Nam, Jung-Mo,Cho, Woo-Hyun,Lee, Sun-Hee 대한예방의학회 1999 예방의학회지 Vol.32 No.1
Objectives. The Study of Small Area Variation(SAV) is most interesting issue in the health care researches. Most studies of SAV have been concluded the existences of variation on the basis of the magnitude of variation without statistical testing. But it is difficult to explain the existence of variation with this way because variation indicies are easily influenced by several parameters and also their distribution are skewed. So, it needs for the study to investigate the distribution of these indices and develop the statistical testing model. Methods. This study was planned to analyze on the distribution of variation indices such as Extremal Quotient(EQ), Coefficient of Variation(CV), Systematic Component of Variation(SCV) and compare the statistical power among indicies. The simulations was performed on the basis of several assumptions and compared to the empirical data. Results. Main findings can be summarized as follows. 1. If other conditions are constant, the more number of regions, the larger 95 percentile of EQ. But under same situation, 95 percentile of CV and SCV were slightly decreased. 2. If the size of regional population or utilization rate were increased, 95 percentile of all statistics were decreased. Also in the cases of small population size and low utilization rate, 95 percentiles of EQ showed various change contrast to the little change of CV. 3. If the difference at the size of regional population were increased, 95 percentiles of EQ and SCV were increased contrast to the little different of CV. 4. If the utilization rate were increased, 95 percentiles of all indicies were increased. But under the same difference of utilization rate, the power of CV and SCV were increased comparing to no change of the power of EQ. 5. Usually the power of EQ were lower than that of CV or SCV and it is similar between CV and SCV. Conclusions. Therefore, we suggest that in selecting the variation indicies at the SAV, CV or SCV are superior than EQ in terms of significance level and power.