SUMMARY, SMOOTHING, AND INFERENCE IN EPIDEMIOLOGIC ANALYSIS

In a recent article (Epidemiology 1990; 1: 421-429) 1 resurrected some historical criticisms of conventional statistics in non-randomized, non-randomly sampled studies, and suggested some improvements to current practice in response to these criticisms. Here, I propose that some resolution can be achieved by separating data analysis into summarization, smoothing, and inferential phases. Methods of statistical inference are in fact smoothing methods, as are many methods of descriptive statistics, and as such can be viewed as pattern-recognition devices. Scientific inference is not a statistical process, but instead concerns derivation of explanations for patterns detected by statistical methods. Improvements could be made to all three phases simply by keeping the phases distinct.