Paul R. Yarnold
Optimal Data Analysis, LLC
Prior research used the log-linear model to explain shifts in political party identification (democrat=1; independent=2; republican=3) of 202 Catholic voters who reported party identification in the 1956 and 1960 presidential elections. The results showed: “When the symmetry model is fitted to the six off-diagonal cells…L2=20.99, with df=3, which means we must reject the hypothesis that shifts in each direction tended to cancel each other. …Since 2=15.7 for df=1, we conclude that there is a significant tendency for net change to occur predominantly in one direction. Inspection of the table shows that to be in a Democratic direction. …For the quasi-symmetry hypothesis…L2 =0.12 and df=1. Thus we conclude that the panel data approach symmetry, given unequal marginals in the two years. …The difference in L2 between symmetry and quasi-symmetry models is 20.87 and the difference in df is 2. It is, therefore, reasonable to conclude that the marginal distribution of Catholic voter party identification differs significantly between 1956 and 1960” (pp. 51-54). Exploratory novometric analysis is used to model party identification in 1960 (multicategorical class variable) using party identification in 1956 (multicategorical attribute). Next ODA is used to evaluate temporal stability (confirmatory hypothesis) and to identify statistically reliable instability (exploratory hypothesis) underlying party identification assessed across time.
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