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Deciding to Agree: Explaining Consensual Behavior on the United States Supreme Court
Unformatted Document Text:  27 APPENDIX A -- Explanation and Coding of Independent Variables Dependent Variables. Unanimous Decision. Our first dependent variable captures whether the vote on the merits in each case was unanimous. Unanimous cases are coded 1, all others are coded 0. A unanimous decision includes any decision in which no justice dissented, regardless of how many justices participated in the case. Consensual Decisions. Our second dependent variable measures the degree of consensus in the vote on the merits for each case. We calculated the level of consensus by dividing the number of justices who voted in the majority by the number of justices who participated in each case. This dependent variable allows us to assess what factors are more likely to lead to consensus, even if the vote in the case is not unanimous. Independent Variables. We coded most of the independent variables such that a positive increase in the independent variable leads to a positive increase in the likelihood that the decision will be unanimous. See Table 2 for the hypothesized direction of each coefficient and summary statistics. Ideological Dispersion Among the Justices. This variable measures the absolute value of the distance between the median justice’s Martin-Quinn ideology score and the most ideologically distant justice’s Martin-Quinn ideology score. We computed this variable based upon which justices participated in each case. Chief Justice Dummies. In order to test whether whom the Chief Justice is matters when predicting whether a particular Court will achieve consensus or unanimity on a case, we created dummy variables for each of the four Chief Justices who served during the time frame under analysis. We then use Roberts as the baseline for comparison.

Authors: Corley, Pamela., Steigerwalt, Amy. and Ward, Artemus.
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27
APPENDIX A -- Explanation and Coding of Independent Variables
Dependent Variables.
Unanimous Decision. Our first dependent variable captures whether the vote on the merits in
each case was unanimous. Unanimous cases are coded 1, all others are coded 0. A unanimous
decision includes any decision in which no justice dissented, regardless of how many justices
participated in the case.
Consensual Decisions. Our second dependent variable measures the degree of consensus in the
vote on the merits for each case. We calculated the level of consensus by dividing the number of
justices who voted in the majority by the number of justices who participated in each case. This
dependent variable allows us to assess what factors are more likely to lead to consensus, even if
the vote in the case is not unanimous.
Independent Variables.
We coded most of the independent variables such that a positive increase in the independent
variable leads to a positive increase in the likelihood that the decision will be unanimous. See
Table 2 for the hypothesized direction of each coefficient and summary statistics.
Ideological Dispersion Among the Justices. This variable measures the absolute value of the
distance between the median justice’s Martin-Quinn ideology score and the most ideologically
distant justice’s Martin-Quinn ideology score. We computed this variable based upon which
justices participated in each case.
Chief Justice Dummies. In order to test whether whom the Chief Justice is matters when
predicting whether a particular Court will achieve consensus or unanimity on a case, we created
dummy variables for each of the four Chief Justices who served during the time frame under
analysis. We then use Roberts as the baseline for comparison.


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