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大韓小兒齒科學會誌 = Journal of the Korean academy of pediatric dentistry, v.40 no.3, 2013년, pp.223 - 232
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There are many problems in evaluating study results by p value in null hypothesis testing for dental research. It is a logical fallacy to conclude that the null hypothesis is true when the it is not rejected. There are much serious misunderstanding about p value, and researchers should be cautious a...
| 핵심어 | 질문 | 논문에서 추출한 답변 |
|---|---|---|
| 효과 크기란 무엇인가? | 효과 크기는 독립변수와 종속변수 간 연관성의 강도를 나타내는 지표이다. 실험군의 평균과 대조군의 평균 사이의 차이를 효과 크기라고 할 수 있으나, 임의적 척도를 사용한 연구에서처럼 변수의 측정치 자체가 내재적 의미를 가지고 있지 않거나 메타분석 연구에서처럼 상이한 척도를 사용한 여러 연구들의 결과를 종합하여야 할 때에는 표준화된 효과 크기를 사용한다. | |
| 베이지안 통계은 어떤 편리성이 있는가? | 연구가 반복되어 결과가 축적될수록 베이지안 통계는 정확한 진실에 가까워진다. 지금까지 얻은 정보를 하나 하나 다시 계산하는 것이 아니라 최신 정보만 개정하면 결과적으로 같은 수치를 얻을 수 있다는 편리성이 있다. 최근의 미국대통령 선거에서 한 설문조사 사이트는 누적되는 설문조사 결과를 이어지는 설문조사 결과와 통합 분석하는 베이지안 통계 방법을 사용하여 정확한 예측에 성공할 수 있었다38). | |
| 귀무가설이란 무엇인가? | 귀무가설은 연구가설(대립가설, alternative hypothesis)의 반대가 되는 가설로서, 실제로 연구에서 알고자 하는 효과가 없다고 가정하는 가설이다. 유의성 검정에서 연구가설을 검정하지 않고 연구가설의 반대인 귀무가설을 검정을 하는 것은 후건 긍정의 오류를 피하기 위함이다. |
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