Are Only p-Values Less Than 0.05 Significant? A p-Value Greater Than 0.05 Is Also Significant!

곽상규 한국지질동맥경화학회 2023 지질·동맥경화학회지 Vol.12 No.2

Statistical hypothesis testing compares the significance probability value and the significance level value to determine whether or not to reject the null hypothesis. This concludes “significant or not significant.” However, since this process is a process of statistical hypothesis testing, the conclusion of “statistically significant or not statistically significant” is more appropriate than the conclusion of “significant or not significant.” Also, in many studies, the significance level is set to 0.05 to compare with the significance probability value, p-value. If the p-value is less than 0.05, it is judged as “significant,” and if the p-value is greater than 0.05, it is judged as “not significant.” However, since the significance probability is a value set by the researcher according to the circumstances of each study, it does not necessarily have to be 0.05. In a statistical hypothesis test, the conclusion depends on the setting of the significance level value, so the researcher must carefully set the significance level value. In this study, the stages of statistical hypothesis testing were examined in detail, and the exact conclusions accordingly and the contents that should be considered carefully when interpreting them were mentioned with emphasis on statistical hypothesis testing and significance level. In 11 original articles published in the Journal of Lipid and Atherosclerosis in 2022, the interpretation of hypothesis testing and the contents of the described conclusions were reviewed from the perspective of statistical hypothesis testing and significance level, and the content that I would like to be supplemented was mentioned.

What Should We Consider Carefully When Performing Survival Analysis?

곽상규,최은진 대한소아혈액종양학회 2019 Clinical Pediatric Hematology-Oncology Vol.26 No.1

The survival data and the survival analysis are the data and analysis methods used to study the probability of survival. The survival data consist of a period from the juncture of a start event to the juncture of the end event (occurrence event). The period is called the survival period or survival time. In this way, the method of analysing the survival time of subjects and appropriately summarizing the degree of survival is called survival analysis. To understand and analyse survival analysis methods, researchers must be aware of some concepts. Concepts to be aware of in the survival analysis include events, censored data, survival period, survival function, survival curve and so on. This review focuses on the terms and concepts used in the survival analysis. It will also cover the types of survival data that should be collected and prepared when using actual survival analysis method and how to prepare them.

논문 리뷰를 통한 암성통증에 대한 침을 이용한 양한방 통합치료 효과 연구

곽상규,손기철,신임희,김상경,정현정,이아진,조윤정,김달호,Kwak, Sang Gyu,Sohn, Ki Cheul,Shin, Im Hee,Kim, Sang Gyung,Jung, Hyun-Jung,Lee, A-Jin,Cho, Yoon-Jeong,Kim, Dal Ho 한국데이터정보과학회 2015 한국데이터정보과학회지 Vol.26 No.6

난치성 암환자의 암성통증은 암환자의 삶의 질을 지극히 떨어뜨리는 중요한 요인이다. 전 세계적으로 암성 통증을 줄이기 위한 노력으로 양방과 한방의 통합적 치료방법이 증가하는 추세이다. 국내외 적으로도 통합적 접근을 통한 암성통증과 관련된 연구가 지속적으로 이루어지고 있으며 암 치료에 있어서는 화학요법으로 인한 오심이나 구토를 조절하기 위해 표준화된 항구토제와 병용한 침 치료가 효과적임을 보고한 무작위대조군 임상연구가 있다. 여러 연구에서 암으로 인한 피로, 방사선 치료로 인한 구강 건조증, 그리고 불면, 불안, 삶의 질 등에 침치료가 효과적이라고 보고한 바 있다. 그러나 침치료의 실제적인 임상적 효과와 다양한 증례 보고 에도 불구하고, 침을 이용한 통합치료의 진통 감소효과의 유의성에 대해서는 아직 이견이 많다. 이에 따라 본 연구에서는 전 세계 출판된 논문검색을 통하여 침을 이용한 양 한방 통합치료로 인해 암성통증의 감소효과를 파악하고 각 논문에서 제시하는 값을 종합하여 침을 이용한 통합치료의 효과가 어느 정도인지를 평가하기 보았다. Cancer pain is a very important factor in cancer patients refractory to drop the quality of life of cancer patients. The worldwide trend is an integrated effort by both the western medicine and korean traditional medicine of treatment increases to reduce cancer pain. There are many studies related to cancer pain through an integrated medicine approach. Many study was reported that acupuncture treatment is effective for fatigue, xerostomia, insomnia, anxiety and quality of life. However, despite the practical clinical effects and various case reports of acupuncture, many still disagree about the significance of an integrated treatment of pain reduction with acupuncture. Therefore, we has identified that reduce effect of comprehensive and integrative treatment using acupuncture for cancer pain through publication review. And we evaluated effect of comprehensive and integrative treatment using acupuncture through summary of values in each publication.

The principles of presenting statistical results: Table

곽상규,Kang Hyun,김종해,김태균,안은진,Lee Dong-Kyu,Lee Sangseok,박재홍,Nahm Francis Sahngun,인준용 대한마취통증의학회 2021 Korean Journal of Anesthesiology Vol.74 No.2

General medical journals such as the Korean Journal of Anesthesiology (KJA) receive numerous manuscripts every year. However, reviewers have noticed that the tables presented in various manuscripts have great diversity in their appearance, resulting in difficulties in the review and publication process. It might be due to the lack of clear written instructions regarding reporting of statistical results for authors. Therefore, the present article aims to briefly outline reporting methods for several table types, which are commonly used to present statistical results. We hope this article will serve as a guideline for reviewers as well as for authors, who wish to submit a manuscript to the KJA.

Transparency considerations for describing statistical analyses in research

곽상규,김종해 대한마취통증의학회 2021 Korean Journal of Anesthesiology Vol.74 No.6

Background: Researchers who use the results of statistical analyses to draw conclusions about collected data must write a statistical analysis section in their manuscript. Describing statistical analyses in precise detail is as important as presenting the dosages of drugs and methodology of interventions. It is also essential for scientific accuracy and transparency in scientific research.Methods: We evaluated the quality of the statistical analysis sections of clinical research articles published in the Korean Journal of Anesthesiology between February 2020 and February 2021. Using a Likert scale where 1, 2, and 3 represented “not described at all,” “partially described,” and “fully described,” respectively, the following 6 items were assessed: 1) stating of the statistical analysis methods used, 2) rationale for and detailed description of the statistical analysis methods used, 3) parameters derived from the statistical analyses, 4) type and version of the statistical software package used, 5) significance level, and 6) sidedness of the test (one-sided vs. two-sided). The first 3 items evaluate issues directly related to the statistical analysis methods used and last 3 are indirectly related items.Results: In all the included articles, the statistical analysis methods used were stated (score of 3). However, only 4 articles (12.9%) fully described the sidedness of the test (score of 3).Conclusions: Authors tend not to describe the sidedness of statistical analysis tests in the methodology section of clinical research articles. It is essential that the sidedness be described in research studies.

후향적연구의 집단 간 동등성확보를 통한 임상자료분석

곽상규,신임희,Kwak, Sang Gyu,Shin, Im Hee 한국데이터정보과학회 2015 한국데이터정보과학회지 Vol.26 No.6

두 집단간을 비교하는 다양한 임상연구에서 수집된 데이터를 분석할 때 질환에 미치는 영향을 알아보는 방법으로는 현 시점에서 어떤 특정 질환을 일으킬 수 있는 위험요인포함 우, 무에 띠라 연구대상자를 나누어, 추적 관찰하는 전향적 임상연구에서의 분석과 현 시점에서 질환 유, 무에 따라 위험요인을 과거의 연구대상자의 관찰기록을 바탕으로 확인하는 후향적 임상연구에서의 분석이 있다. 접근 방법과 연구 설계는 다르지만 두 가지 연구의 목적은 두 집단 간 명확한 차이를 확인하는데 있으며, 나아가 두집단의 분류에 영향을 주는 변수가 무엇인지를 알아보는 방법이다. 특히 임상연구에서 두 집단을 비교할 때 성별과 나이와 같은 기본적 특성변수의 영향을 통제한 상태에서 임상적 변수들의 집단 간 차이와 영향을 살펴보아야 한다. 하지만 후향적 연구에서는 과거의 관찰기록을 바탕으로 분석이 진행되는 연구이므로 연구대상자를 두 집단으로 무작위 할당하지 못했기 때문에 기본적인 특성변수들이 차이가 나는 경우가 빈번하게 발생할 수 있다. 이를 해결하기 위하여 임상자료를 분석하는 방법으로 공변량을 사용한다. 대표적으로 공변량을 사용하는 분석방법으로는 공분산분석, 수정회귀모형, propensity score matching 방법 등이 있다. 본 연구는 후향적 임상연구에서 공변량을 이용한 자료 분석 방법 및 propensity score matching 방법을 소개하고, 실제 위암 환자들의 재발관련 자료에 적용하여, 그 필요성을 확인한다. There are two types of clinical research to figure out risk factor for disease using collected data. One is prospective study to approach the subjects from the present time and the other is retrospective study to find the risk factor using the subject's information in the past. Both approached and study design are different but the purpose of the two studies is to identify a significant difference between two groups and to find out what the variables to influence groups. Especially when comparing the two groups in clinical research, we have to look at the difference between the impact clinical variables by group while controlling the influence of the baseline characteristics variables such as age and sex. However, in the retrospective study, the difference of baseline characteristic variables can occur more frequently because the past records did not randomly assign subjects into two groups. In clinical data analysis use covariates to solve this problem. Typically, the analysis method using the analysis of covariance of variance, adjusted model, and propensity score matching method. This study is introduce the way of equality adjustment between groups data analysis using covariates in retrospective clinical studies and apply it to the recurrence of gastric cancer data.

지식경영활동 참여에 대한 영향요인에 관한 연구

곽상규 한국경영학회 2009 한국경영학회 통합학술발표논문집 Vol.2009 No.08

Central limit theorem: the cornerstone of modern statistics

곽상규,김종해 대한마취통증의학회 2017 Korean Journal of Anesthesiology Vol.70 No.2

According to the central limit theorem, the means of a random sample of size, n, from a population with mean, μ, and variance, σ2, distribute normally with mean, μ, and variance, σ2 n . Using the central limit theorem, a variety of parametric tests have been developed under assumptions about the parameters that determine the population probability distribution. Compared to non-parametric tests, which do not require any assumptions about the population probability distribution, parametric tests produce more accurate and precise estimates with higher statistical powers. However, many medical researchers use parametric tests to present their data without knowledge of the contribution of the central limit theorem to the development of such tests. Thus, this review presents the basic concepts of the central limit theorem and its role in binomial distributions and the Student’s t-test, and provides an example of the sampling distributions of small populations. A proof of the central limit theorem is also described with the mathematical concepts required for its nearcomplete understanding.

Noninformative Priors for the Variance Ratio in Analysis of Covariance Model

곽상규,강상길,김달호 장전수학회 2016 Proceedings of the Jangjeon mathematical society Vol.19 No.1

In this paper, we develop the noninformative priors for the variance ratio in the analysis of covariance model. We use the criterion of the asymptotic matching of coverage probabilities of Bayesian credible intervals with the corresponding frequentist coverage probabilities. We develop the first and the second order matching priors. We reveal that the second order matching prior does not exist in the unbalanced case. However, the second order matching prior can be obtained in the balanced case. It turns out that the reference priors satisfy the first order matching criterion, but Jeffreys' prior does not satisfy even the first order matching criterion. Some simulation study is performed.

행사보고 : 2015 분리기술부문위원회 동계 심포지엄 후기

곽상규 한국화학공학회 2015 NICE Vol.33 No.2