Some characterize public opinion as fickle, volatile,
or subject to abrupt change. Yet, empirical evidence from Page and
Shapiro (1992) reveals the opposite. This study re-examines the
issue of public opinion stability because the six-percentage point
criterion Page and Shapiro used ignored the true sample sizes and
distributions of many surveys. Calculating the precise statistical
test for the difference between two independent proportions shows
how smaller opinion changes are potentially statistically significant
depending on four parameters: the exact magnitude of the change,
the sample size, the distribution of the survey responses, and the
design effect correction used. Evenly split (near 50/50) smaller
samples (near 1,000 respondents) are generally significant at the
six-percentage point level. However, evenly split larger samples
(2,000+) attain significance at levels below the six-percentage
point threshold, typically around differences of five and four percentage
points. In unevenly split distributions (90/10), differences of
as little as two percentage points can be statistically significant.
Analysis of a subset of The Rational Public data as well as Public
Opinion Quarterly Poll Trend data reveals that the metric of opinion
stability matters. Many cases previously classified as instances
of opinion stability become instances of instability when retaining
the sample and distribution characteristics.
Jason Barabas, Graduate Fellow, Department
of Political Science, Northwestern University
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