Continuously distributed random variables in factorial designs

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 x 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 R2 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.