Strategy in research design and hypothesis testing
B. L. Myers Ph.D., N. L. Enrick Ph.D., A. J. Melcher Ph.D.
Journal of the Academy of Marketing Science · 1974 · Volume 2 · Issue 1
Abstract
The efficiency of a research design may be measured in terms of the degree to which knowledge is enhanced within given resource constraints. Thus, two different types of research design, even though they contain the same number of expected observations, may differ considerably in the amount of information provided. An example is the number N of 32 observations obtained with an analysis of variance witheither2 factors, 2 levels per factor and a replication of 8or4 factors, 4 levels per factor and a replication of 2. We analyze and compare the relative efficiencies of regression and variance analysis models and their implications to research strategy development. Three major considerations are evaluated: (1) short versus long time horizon (interval until effects of a decision are realized), (2) small versus large cost of erroneous rejection of the Null Hypothesis and (3) gross versus refined stage of development of the research study. A set of general guidelines towards improved designs is developed.
Keywords
Bivariate Normal Distribution, Partial Regression Coefficient, Replication Index, Standardize Partial Regression Coefficient, Administrative Science
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