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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Statistical methods and common problems in medical or biomedical science research
Fengxia Yan1, Mayberry Robert1, Yonggang Li2
1Department of Community Health and Preventive Medicine, Morehouse School of MedicineAtlanta, GA, USA.
Abstract:
Statistical thinking is crucial for studies in medical and biomedical areas. There are several pitfalls of using statistics in these areas involving in experimental design, data collection, data analysis and data interpretation. This review paper describes basic statistical design problems in biomedical or medical studies and directs the basic scientists to better use of statistical thinking. The contents of this paper were based on previous literatures and our daily basic support work. It includes the sample size determination and sample allocation in experimental design stage, numerical and graphical data summarization, and statistical test methods as well as the related common errors at design and analytic stages. Literatures and our daily support works show that misunderstanding and misusing of statistical concept and statistical test methods are significant problems. These may include ignoring the sample size and data distribution, incorrect summarization measurement, wrong statistical test methods especially for repeated measures, ignoring the assumption for t-test or ANOVA test, failing to perform the adjustment for multiple comparison. This review intends to help the researchers in basic medical or biomedical areas to enhance statistical thinking and make fewer errors in study design and analysis of their studies.
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