Interim analyses of data as they accumulate in laboratory experimentation

Laboratory researchers, from ignorance or by design, often analyse their results before the final number of experimental units (humans, animals, tissues or cells) has been reached. If this is done in an uncontrolled fashion, the pejorative term 'peeking' has been applied. A statistical penalty must be exacted. This is because if enough interim analyses are conducted, and if the outcome of the trial is on the borderline between 'significant' and 'not significant', ultimately one of the analyses will result in the magical P = 0.05. I suggest that Armitage's technique of matched-pairs sequential analysis should be considered. The conditions for using this technique are ideal: almost unlimited opportunity for matched pairing, and a short time between commencement of a study and its completion. Both the Type I and Type II error-rates are controlled. And the maximum number of pairs necessary to achieve an outcome, whether P = 0.05 or P > 0.05, can be estimated in advance.Laboratory investigators, if they are to be honest, must adjust the critical value of P if they analyse their data repeatedly. I suggest they should consider employing matched-pairs sequential analysis in designing their experiments.What does the term 'interim analysis' mean? A short definition is that it refers to the repeated analyses of data as they accumulate. This is not a bad definition, since it can be applied not only to clinical trials but also to laboratory experiments.Why does it matter? It matters in a statistical sense that is not very different from that of making multiple comparisons within the same experiment. In either case, the risk of Type I error (false-positive inference) increases progressively as the number of tests of significance increases. I have reviewed elsewhere the problem of making multiple comparisons and ways of solving it [1,2]. Here I review the topic of making serial comparisons on data as they accumulate. To state this problem in a very crude, but nonetheless broadly a