Continuously distributed random variables in factorial designs

Abstract

Age as a variable in lifespan research usually is sampled as several age blocks which, in turn, are combined with additional variables in a factorial design. Sampling a continuous variable in discrete blocks increases the difficulty in obtaining adequate sampling, reduces power, and prevents a fine grain analysis of age × treatment interactions. Age can be sampled as a continuously distributed variable, factorially combined with treatment groups, and analyzed as an analysis of variance by the use of regression analysis and comparison of multiple R ² coefficients. The advantages of such a sampling strategy include both practical sampling advantages as well as statistical advantages when compared with the usual sampling approach.