By David K. Hildebrand, James D. Laing, Howard Rosenthal
Ordinal information should be rank ordered yet no longer assumed to have equivalent distances among different types. utilizing help by means of judges for civil rights measures and bussing because the fundamental instance, this paper exhibits how such facts can top be analyzed.
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Extra resources for Analysis of ordinal data
If the prediction is wrong, we add one to our error total. Thus, for the 13 Democrats, we predict left or left-center and consequently make no errors (see Table 1). The proposition predicts center for each of the nine Independents so the six non-center cases are errors. Finally, the prediction for Republicans identifies left and left-center as error events, contributing three errors for the nine Republican bureaucrats. Therefore, we observe nine (0+6+3) prediction errors, the number of bureaucrats who lie in the set of cells that are shaded in Table 1.
Page a Analysis of Ordinal Data Page b SAGE UNIVERSITY PAPERS Series: Quantitative Applications in the Social Sciences Series Editor: Michael S. Lewis-Beck, University of Iowa Editorial Consultants Richard A. Berk, Sociology, University of California, Los Angeles William D. Berry, Political Science, Florida State University Kenneth A. Bollen, Sociology, University of North Carolina, Chapel Hill Linda B. Bourque, Public Health, University of California, Los Angeles Jacques A. Hagenaars, Social Sciences, Tilburg University Sally Jackson, Communications, University of Arizona Richard M.
Many other types of propositions can be evaluated with the general framework. After dealing extensively with bivariate propositions, we briefly consider the AUTHORS' NOTE: We thank our research assistant, Richard Gunsaulus, for a careful and critical reading of the manuscript. We have also benefitted from comments by the series editor and a referee. Page 8 evaluation of multivariate predictions. The general framework not only provides a common perspective for interpreting standard measures of association.