Replication data for: Reconsidering the Measurement of Political Knowledge

Political knowledge has emerged as one of the central variables in political behavior research, with numerous scholars devoting considerable effort to explaining variance in citizens' levels of knowledge and to understanding the consequences of this variance for representation. Although such substantive matters continue to receive exhaustive study, questions of measurement also warrant attention. I demonstrate that conventional measures of political knowledge—constructed by summing a respondent's correct answers on a battery of factual items—are of uncertain validity. Rather than collapsing incorrect and "don't know" responses into a single absence-of-knowledge category, I introduce estimation procedures that allow these effects to vary. Grouped-data multinomial logistic regression results demonstrate that incorrect answers and don't knows perform dissimilarly, a finding that suggests deficiencies in the construct validity of conventional knowledge measures. The likely cause of the problem is traced to two sources: knowledge may not be discrete, meaning that a simple count of correct answers provides an imprecise measure; and, as demonstrated by the wealth of research conducted in the field of educational testing and psychology since the 1930s, measurement procedures used in political science potentially result in "knowledge" scales contaminated by systematic personality effects.