Contrasting clinical and statistical significance within the research setting.
When designing a clinical trial or study, the value of the following interrelated parameters should be determined prior to collecting data: clinical significance, statistical significance, power, and sample size. Too often, clinical importance and the other design issues are ignored and only statistical significance dictates the conclusions of the study. In order to evaluate the frequency that each of these design parameters is addressed in the published literature, the topic of pulmonary function tests (specifically forced vital capacity) was chosen, and all relevant articles for one year (1990) were identified using Minnesota MEDLINE. A total of 121 articles met the selection criteria and were reviewed. Of all the articles, 13.2% discussed clinical significance, 21.5% discussed sample size, and only 5.0% addressed statistical power. As expected, the majority of the articles (92.6%) discussed statistical significance (P values). None of the articles mentioned all four factors. When choosing the level of clinical significance several methods may be used. Such might be well established in certain clinical areas or available from previous publications and references or they may be attainable from pilot study data and, in the absence of any prior information, a clinician may use personal experience. To minimize subjectivity, the clinical effect-size can be based on the population distribution of the measurement of interest.
Lindgren
B R
BR
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis 55455.
Wielinski
C L
CL
Finkelstein
S M
SM
Warwick
W J
WJ
D002986:Clinical Trials as Topic; D006801:Humans; D012107:Research Design; D012129:Respiratory Function Tests; D012494:Sampling Studies; D013223:Statistics as Topic