Lies, damned lies — or statistics?


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Abstract

Purpose:The Journal of Hypertension has now produced statistical guidelines for authors. This review highlights some of the important issues in the guidelines.Type I and II errors:The Type I error is essentially the chance of a false positive result and is conventionally set to 5%. Equally important, but sometimes neglected, is the Type II error — the chance of a false negative result.Normality of data:Many statistical tests are only valid if the data are normally distributed. If the data are not normally distributed, non-parametric tests should be used.Multiple comparisons:Type I error rates must be corrected if multiple comparisons are made.Correlation coefficients:In general, regression coefficients are more useful than correlation coefficients. The latter may often be statistically significant but not convey any useful information.Confidence intervals:A confidence interval is a measure of the range which is likely to contain the true value of the parameter of interest; it conveys more information than a P value about the result of a study. Confidence intervals are also very useful for comparing studies.

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