By George A. Milliken, Dallas E. Johnson
Researchers frequently don't research nonreplicated experiments statistically simply because they're strange with present statistical tools that could be acceptable. research of Messy facts, quantity II information the statistical equipment applicable for nonreplicated experiments and explores how you can use statistical software program to make the necessary computations possible
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Additional info for Analysis of Messy Data, Volume II: Nonreplicated Experiments
4 of Milliken and Johnson (1984). That is, contrasts of the a's are examined only if the characteristic root test has previously shown that there is significant interaction in the data. 1. 1 Data from Davies (1954, p. 305). 6 of two-way factorial experiments. Davies used an additive model to analyze the data. 97 with 12 degrees as an estimate of o2. Davies did not test for interaction. 317. 882), //0: A = 0 is rejected. Thus, the characteristic root test shows that significant interaction is present in these data.
While the ability to determine whether a particular data set is additive is useful to the data analyst in many ways, it is also important, if not more important, to be able to obtain a reliable estimator of the experimental error variance. Tests of significance and confidence interval construction when a set of data is determined to be nonadditive require accurate estimation of the experimental error variance. 2). 3).
Ti=yi. -y.. j-y.. i = 1,2, . , r J = 1,2, . . , i A r 2 =/ r r = 1,2, . . , fc. k > ^k+i characteristic roots of Z'Z (or ZZ'), > ' ' ' > ^P are the nonzero Z = (Zy)_ Zij=ytj-yi. j + ?.. p^min (fc - 1, f - 1) a r = normalized characteristic vector of ZZ' corresponding to the characteristic root,
Analysis of Messy Data, Volume II: Nonreplicated Experiments by George A. Milliken, Dallas E. Johnson