Many published papers include large numbers of significance tests. These may be difficult to
interpret because if we go on testing long enough we will inevitably find something which is …

Conclusion The statistic that 1 in 12 women will develop breast cancer is thus correct only for
women who have escaped a number of equally serious but more likely threats to life at an …

Ed Iain Chalmers, Douglas G Altman BMJ Publishing Group,£ 14.95, pp 1 19 ISBN 0 7279
0904 5 sr T_he function of the expert reviewer is not to be more right than other people, but to …

We often want to compare two estimates of the same quantity derived from separate analyses.
Thus we might want to compare the treatment effect in subgroups in a randomised trial, …

In medical research, continuous variables are often converted into categorical variables by
grouping values into two or more categories. We consider in detail issues pertaining to …

Measurements of continuous variables are made in all branches of medicine, aiding in the
diagnosis and treatment of patients. In clinical practice it is helpful to label individuals as …

The relationship between a response variable and one or more continuous covariates is
often curved. Attempts to represent curvature in single- or multiple-regression models are …

The non-equivalence of statistical significance and clinical importance has long been recognised,
but this error of interpretation remains common. Although a significant result in a large …

Prognostic models are used in medicine for investigating patient outcome in relation to
patient and disease characteristics. Such models do not always work well in practice, so it is …

Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the
effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s …