Abstract
A flexible and general method of creating linear statistical models that incorporate assumptions implied by hypotheses is described and demonstrated. The demonstration involves testing analysis of covariance type hypotheses in the presence of nonparallel regression lines. Computation requires only an ordinary least squares regression program. The logical justification and statistical rationale for the demonstration problem are based on Rogosa (1980).

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