A sensible formulation of the significance test.

The conventional procedure for null hypothesis significance testing has long been the target of appropriate criticism. A more reasonable alternative is proposed, one that not only avoids the unrealistic postulation of a null hypothesis but also, for a given parametric difference and a given error probability, is more likely to report the detection of that difference.

Efficacy estimates from parasite count data that include zero counts.

Because of the positive skewness of parasite distributions and the greater constancy of percentage of response of therapy in animal populations, parasite count data are conventionally transformed logarithmically before combining results from different animals, either all controls or all treated. Observations of zero counts raise difficulties, since the logarithm of zero is not useful. In this study, several types of zero count adjustments are compared.

Urbanicity-related trends in lung cancer mortality in US counties: white females and white males, 1970-1987.

Background: The effect of urbanization on age-adjusted lung cancer mortality rates in US counties is investigated. The data come from National Cancer Institute, and urban trends are estimated in time periods 1970-1979 and 1980-1987, for both white males and white females. To account for possibly different gradients in different parts of the country, the 48 contiguous states are divided into seven regions.

Tightening the clinical trial.

Randomized clinical trials adhere more closely to pre-agreed-on protocols than almost any other type of experiment, yet we can tighten up their analysis if we desire. If we convert the analysis into a randomization analysis--where the one set of data is analyzed many times--once as though each acceptable assignment has been employed, we can eliminate any dependence of the analysis on statistical or probabilistic assumptions. To do this effectively when many assignments could be acceptable, we can go to double randomization, in which a subset, usefully kept balanced, of acceptable assignments is selected (perhaps randomly) before data acquisition.

Evaluation of multicentre clinical trial data using adaptations of the Mosteller-Tukey procedure.

Two procedures, based on proposals discussed by Mosteller and Tukey, are described for obtaining a combined estimate of the difference between two treatment means and its confidence interval from multicentre clinical trial data. Both procedures provide estimates in the possible presence of heteroscedasticity. The first procedure is designated the primary analysis for efficacy assessment.