Abstract
Regression analysis of repeated‐measures data from plots in large experiments is both labor intensive and time consuming. When duration estimates characterizing each individual repeated‐measures series are of interest, numerical integrations are possible alternatives. This note evaluates a trapezoidal rule for estimating a wetness duration index that is derived from repeated tensiometer readings of matric potential associated with plots in a recent soybean [Glycine max (L.) Merr.] study. Tensiometer repeated‐measures series were randomly selected from four of the treatments with their replications for a total of 15 plots (of 420 total) associated with a 2‐yr experiment. Regression‐based duration estimates were developed and compared with those derived using an unequally spaced trapezoidal rule. Equivalence between the two estimators was assessed based on multiple statistical analyses. The estimators were virtually identical by all criteria. The numerical method is faster and easier to employ. Furthermore, the concept can be applied to other repeated measurements, and the results may be useful as covariates in other analyses.
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