Major Concerns Regarding Study Design and Clinical Biomarker Interpretation (original) (raw)

Statistical Tests in Medical Research

Acta Oncologica, 1992

Various propositions have been made to improve the statistical quality of medical journals: using statistical referees, promoting better collaboration between statisticians and researchers, and teaching of basic statistics to clinicians. The most frequent errors found in medical articles are misinterpretation of p-values or non-significant results and confusion between statistical and clinical significance, inappropriate use of tests requiring precise assumptions, inappropriate or not controlled multiple testing and particularly testing of post hoc hypotheses, and overemphasis on pvalues. Many errors arising from the misinterpretation of results of statistical hypothesis tests, the basic principles of this methodology are emphasized, and the usual fallacies found in the medical literature are reviewed.

The Use of Statistics in Medical Research

The American …, 2007

There is widespread evidence of the extensive use of statistical methods in medical research. Just the same, standards are generally low and a growing body of literature points to statistical errors in most medical journals. However, there is no comprehensive study contrasting the top medical journals of basic and clinical science for recent practice in their use of statistics. were screened for their statistical content. Types, frequencies, and complexity of applied statistical methods were systematically recorded. A 46-item checklist was used to evaluate statistical quality for a subgroup of papers.

Statistics IV: Interpreting the results of statistical tests

Continuing Education in Anaesthesia, Critical Care & Pain, 2007

This is the fourth in a series of articles in this journal on the use of statistics in medicine. In the previous issue, we described how to choose an appropriate statistical test. In this article, we consider this further and discuss how to interpret the results. More on choosing an appropriate statistical test Deciding which statistical test to use to analyse a set of data depends on the type of data (interval or categorical, paired vs unpaired) being analysed and whether or not the data are normally distributed. Interpretation of the results of statistical analysis relies on an appreciation and consideration of the null hypothesis, P-values, the concept of statistical vs clinical significance, study power, types I and II statistical errors, the pitfalls of multiple comparisons, and one vs two-tailed tests before conducting the study.

Statistical Aspect in Medical and Paramedical Research Articles

Background: The purpose of this study was to introduce the appropriate application of statistical concept and methodology in medical and paramedical science articles. Author represented statistical methods that have been utilized in the literature. Materials and Methods: The concepts of descriptive, inferential, basic and advance statistics, p-values, clinical and statistical significance are discussed with examples to project their application to the interpretation of various medical and paramedical researches. In addition, descriptions of Student's t test, Chi-square test, Fisher's exact test, Logistic regression and Cox regression are presented. These techniques are described with adequate detail to allow a reader who has access to the original data to verify the reported results. Results: Statistical literacy required for scientific evolution of the research. Statistical methods are increasingly a necessary and an inseparable part of medical and paramedical research. Due...

The null hypothesis significance test in health sciences research (1995-2006): statistical analysis and interpretation

BMC Medical Research Methodology, 2010

The null hypothesis significance test (NHST) is the most frequently used statistical method, although its inferential validity has been widely criticized since its introduction. In 1988, the International Committee of Medical Journal Editors (ICMJE) warned against sole reliance on NHST to substantiate study conclusions and suggested supplementary use of confidence intervals (CI). Our objective was to evaluate the extent and quality in the use of NHST and CI, both in English and Spanish language biomedical publications between 1995 and 2006, taking into account the International Committee of Medical Journal Editors recommendations, with particular focus on the accuracy of the interpretation of statistical significance and the validity of conclusions. were selected through a systematic sampling method. After excluding the purely descriptive and theoretical articles, analytic studies were evaluated for their use of NHST with P-values and/or CI for interpretation of statistical "significance" and "relevance" in study conclusions.