Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-19T09:31:38.293Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  24 November 2009

Keith T. Poole
Affiliation:
University of California, San Diego
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abramowitz, Alan I. and Segal, Jeffrey A.. 1992. Senate Elections. Ann Arbor, MI: University of Michigan PressGoogle Scholar
Albert, A. and Anderson, J. A.. 1984. “On the Existence of Maximum Likelihood Estimates in Logistic Regression Models.” Biometrika, 71:1–10CrossRefGoogle Scholar
Albert, James H. and Chib, Siddhartha. 1993. “Bayesian Analysis of Binary and Polychotomous Response Data.” Journal of the American Statistical Association, 88:669–679CrossRefGoogle Scholar
Aldrich, John H. and McGinnis, Michael D.. 1989. “A Model of Party Constraints on Optimal Candidate Positions.” Mathematical and Computer Modeling, 12:437–450CrossRefGoogle Scholar
Amacher, Ryan C. and Boyes, William J.. 1978. “Cycles in Senatorial Voting Behavior: Implications for the Optimal Frequency of Elections.” Public Choice, 33(3): 5–13CrossRefGoogle Scholar
Andrich, David. 1988. Rasch Models for Measurement. Newbury Park, CA: SageCrossRefGoogle Scholar
Andrich, David. 1995. “Hyperbolic Cosine Latent Trait Models for Unfolding Direct Responses and Pairwise Preferences.” Applied Psychological Measurement, 19:269–290CrossRefGoogle Scholar
Ansolabehere, Stephen, Snyder, James M. Jr., and Stewart, Charles III., 2001. “Candidate Positioning in U.S. House Elections.” American Journal of Political Science, 45:136–159CrossRefGoogle Scholar
Austen-Smith, David. 1987. “Interest Groups, Campaign Contributions, and Probabilistic Voting.” Public Choice, 54:123–139CrossRefGoogle Scholar
Austen-Smith, David and Banks, Jeffrey S.. 2000. Positive Political Theory I: Collective Preference. Ann Arbor, MI: University of Michigan PressGoogle Scholar
Austen-Smith, David and Banks, Jeffrey S.. 2004. Positive Political Theory II: Strategy and Structure. Ann Arbor, MI: University of Michigan PressGoogle Scholar
Bailey, Michael. 2002. “Comparing Presidents, Senators, and Justices, 1946–2002.” Working Paper, Georgetown University
Bailey, Michael and Chang, Kelly. 2001. “Comparing Presidents, Senators, and Justices: Inter-institutional Preference Estimation.” Journal of Law, Economics and Organization, 17:477–506CrossRefGoogle Scholar
Bennett, Joseph F. and Hays, William L.. 1960. “Multidimensional Unfolding: Determining the Dimensionality of Ranked Preference Data.” Psychometrika, 25:27–43CrossRefGoogle Scholar
Berndt, E. K., Hall, Bronwyn H., Hall, Robert E., and Hausman, Jerry. 1974. “Estimation and Inference in Nonlinear Structural Models.” Annals of Economic and Social Measurement, 3/4:653–666Google Scholar
Bernhard, William and Brian R. Sala. 2004. “The Dynamics of Senate Voting: “Ideological Shirking” and the 17th Amendment.” Paper Presented at the Annual Meetings of the Southern Political Science Association, New Orleans, LA
Bernhardt, M. Daniel and Ingberman, Daniel E.. 1985. “Candidate Reputations and the ‘Incumbency Effect’.” Journal of Public Economics, 27:47–67CrossRefGoogle Scholar
Best, Alvin M., Young, Forrest W., and Hall, Robert G.. 1979On the Precision of a Euclidean Structure.” Psychometrika, 44:395–408CrossRefGoogle Scholar
Black, Duncan. 1948On the Rationale of Group Decision Making.” Journal of Political Economy, 56:23–34CrossRefGoogle Scholar
Black, Duncan. 1958. The Theory of Committees and Elections. Cambridge, England: Cambridge University PressGoogle Scholar
Blokland-Vogelesang, Rian. 1991. Unfolding and Group Consensus Ranking for Individual Preferences. Leiden: DWSO PressGoogle Scholar
Borg, Ingwer and Groenen, Patrick. 1997. Modern Multidimensional Scaling: Theory and Applications. New York: SpringerCrossRefGoogle Scholar
Brady, Henry. 1990Traits Versus Issues: Factor Versus Ideal-Point Analysis of Candidate Thermometer Ratings.” Political Analysis, 2:97–129CrossRefGoogle Scholar
Brady, David W. and Volden, Craig. 1998. Revolving Gridlock Politics and Policy from Carter to Clinton. Boulder, CO: Westview PressGoogle Scholar
Cahoon, Lawrence S. 1975. Locating a Set of Points Using Range Information Only. Ph.D. Dissertation, Department of Statistics, Carnegie-Mellon University
Cahoon, Lawrence S., Melvin J. Hinich, and Peter C. Ordeshook. 1976. “A Multidimensional Statistical Procedure for Spatial Analysis.” Manuscript, Carnegie-Mellon University
Cahoon, Lawrence S., Hinich, Melvin J., and Ordeshook, Peter C.. 1978. “A Statistical Multidimensional Scaling Method Based on the Spatial Theory of Voting.” In Graphical Representation of Multivariate Data, edited by Wang, P. C.. New York: Academic PressGoogle Scholar
Calvert, Randall. 1985Robustness of the Multidimensional Voting Model: Candidates' Motivations, Uncertainty, and Convergence.” American Journal of Political Science, 29:69–95CrossRefGoogle Scholar
Campbell, Angus, Converse, Philip E., Miller, Warren E., and Stokes, Donald E.. 1960. The American Voter. New York: WileyGoogle Scholar
Carmines, Edward G. and Stimson, James A.. 1989. Issue Evolution: Race and the Transformation of American Politics. Princeton, NJ: Princeton University PressGoogle Scholar
Carroll, J. Douglas. 1972. “Individual Differences and Multidimensional Scaling.” In Multidimensional Scaling: Theory and Applications in the Behavioral Sciences, edited by Romney, A. Kimball, Shepard, Roger N., and Nerlove, Sara Beth. New York: Seminar PressGoogle Scholar
Carroll, J. Douglas. 1980. “Models and Methods for Multidimensional Analysis of Preferential Choice (or Other Dominance) Data.” In Similarity and Choice, edited by Lantermann, E. D. and Feger, H.. Bern, Switzerland: HuberGoogle Scholar
Carroll, J. Douglas and Chang, Jih-Jie. 1970. “Analysis of Individual Differences in Multidimensional Scaling via an N-Way Generalization of ‘Eckart–Young’ decomposition.” Psychometrika, 35:283–320CrossRefGoogle Scholar
Chang, Jih-Jie and J. Douglas Carroll. 1969. “How to Use MDPREF, a Computer Program for Multidimensional Analysis of Preference Data.” Multidimensional Scaling Program Package of Bell Laboratories, Bell Laboratories, Murray Hill, NJ
Chater, Nick. 1999. “The Search for Simplicity: A Fundamental Cognitive Principle?” Quarterly Journal of Experimental Psychology, 52A:273–302CrossRefGoogle Scholar
Cheng, Ken. 2000Shepard's Universal Law Supported by Honeybees in Spatial Generalization.” Psychological Science, 5:403–408CrossRefGoogle Scholar
Clinton, Joshua D. 2003. “Same Principals, Same Agents, Different Institutions: Roll Call Voting in the Continental Congress, Congresses of Confederation and the U.S. Senate, 1774–1786.” Working Paper, Princeton University
Clinton, Joshua D. and Meirowitz, Adam H.. 2003Integrating Voting Theory and Roll-Call Analysis: A Framework.” Political Analysis, 11:381–396CrossRefGoogle Scholar
Clinton, Joshua D. and Meirowitz, Adam H.. 2004Testing Accounts of Legislative Strategic Voting: The Compromise of 1790.” American Journal of Political Science, 48:675–689CrossRefGoogle Scholar
Clinton, Joshua D., Jackman, Simon D., and Rivers, Douglas. 2004The Statistical Analysis of Roll Call Data: A Unified Approach.” American Political Science Review, 98:355–370CrossRefGoogle Scholar
Converse, Philip E. 1964. “The Nature of Belief Systems in Mass Publics.” In Ideology and Discontent, edited by Apter, David E.. New York: Free PressGoogle Scholar
Coombs, Clyde. 1950Psychological Scaling Without a Unit of Measurement.” Psychological Review, 57:148–158CrossRefGoogle Scholar
Coombs, Clyde. 1964. A Theory of Data. New York: WileyGoogle Scholar
Courant, Richard and Hilbert, David. 1937. Methods of Mathematical Physics: Volume I. Berlin: Julius SpringerGoogle Scholar
Cox, Gary W. 1999The Empirical Content of Rational Choice Theory: A Reply to Green and Shapiro.” Journal of Theoretical Politics, 11:147–169CrossRefGoogle Scholar
Cox, Gary W. 2004. “Lies, Damned Lies and Rational Choice Analysis.” In Problems and Methods in the Study of Politics, edited by Shapiro, Ian, Smith, Rogers M., and Masoud, Tarek E.. Cambridge: Cambridge University PressGoogle Scholar
Cox, Gary W. and Katz, Jonathan N.. 2002. Elbridge Gerry's Salamander: The Electoral Consequences of the Reapportionment Revolution. New York: Cambridge University PressCrossRefGoogle Scholar
Cox, Gary W. and McCubbins, Mathew D.. 1993. Legislative Leviathan. Berkeley, CA: University of California PressGoogle Scholar
Cox, Gary W. and Mathew D. McCubbins. 2004. “Setting the Agenda: Responsible Party Government in the US House of Representatives.” Manuscript, University of California, San Diego
Cox, Gary W. and Poole, Keith T.. 2002a. “On Measuring Partisanship in Roll Call Voting: The U.S. House of Representatives, 1877–1999.” American Journal of Political Science, 46:477–489CrossRefGoogle Scholar
Cox, Gary W. and Keith T. Poole. 2002b. “Measuring Group Differences in Roll Call Voting.” Manuscript, University of Houston
Cox, Trevor F. and Michael, A. A. Cox. 2001. Multidimensional Scaling. New York: Chapman and Hall/CRCGoogle Scholar
Cragg, John G. and Donald, Stephen G.. 1997Inferring the Rank of a Matrix.” Journal of Econometrics, 76:223–250CrossRefGoogle Scholar
D'Andrade, Roy G., Quinn, Naomi R., Nerlove, Sara Beth, and Romney, A. Kimball. 1972. “Categories of Disease in American-English and Mexican-Spanish.” In Multidimensional Scaling: Theory and Applications in the Behavioral Sciences, edited by Romney, A. Kimball, Shepard, Roger N., and Nerlove, Sara Beth. New York: Seminar PressGoogle Scholar
Davis, Otto A. and Hinich, Melvin J.. 1966. “A Mathematical Model of Policy Formation in a Democratic Society.” In Mathematical Applications in Political Science, II, edited by Bernd, J. L.. Dallas: SMU Press, pp. 175–208Google Scholar
Davis, Otto A. and Hinich, Melvin J.. 1967. “Some Results Related to a Mathematical Model of Policy Formation in a Democratic Society.” In Mathematical Applications in Political Science III, edited by Bernd, J.. Charlottesville, VA: University of Virginia Press, pp. 14–38Google Scholar
Davis, Otto A., Hinich, Melvin J., and Ordeshook, Peter C.. 1970An Expository Development of a Mathematical Model of the Electoral Process.” American Political Science Review, 64:426–448CrossRefGoogle Scholar
DeSarbo, Wayne S. and Cho, Jaewun 1989A Stochastic Multidimensional Scaling Vector Threshold Model for the Spatial Representation of ‘Pick Any/N’ Data.” Psychometrika, 54:105–129CrossRefGoogle Scholar
DeSarbo, Wayne S. and Hoffman, Donna L.. 1987Constructing MDS Joint Spaces from Binary Choice Data: A Multidimensional Unfolding Threshold Model for Marketing Research.” Journal of Marketing Research, 24:40–54CrossRefGoogle Scholar
Dhrymes, Phoebus J. 1978. Introductory Econometrics. New York: Springer-VerlagCrossRefGoogle Scholar
Diermeier, Daniel. 1996. “Rational Choice and the Role of Theory in Political Science.” In The Rational Choice Controversy, edited by Friedman, Jeffrey. New Haven: Yale University PressGoogle Scholar
Downs, Anthony. 1957. An Economic Theory of Democracy. New York: Harper & RowGoogle Scholar
Eckart, Carl and Young, Gale. 1936The Approximation of One Matrix by Another of Lower Rank.” Psychometrika, 1: 211–218CrossRefGoogle Scholar
Efron, Bradley. 1979Bootstrap Methods: Another Look at the Jackknife.” Annals of Statistics, 7:1–26CrossRefGoogle Scholar
Efron, Bradley and Tibshirani, Robert J.. 1993. An Introduction to the Bootstrap. New York: Chapman & HallCrossRefGoogle Scholar
Ekman, Gosta. 1954Dimensions of Color Vision.” Journal of Psychology, 38:467–474CrossRefGoogle Scholar
Ellenberg, Jordan. 2001. “Growing Apart: The Mathematical Evidence for Congress' Growing Polarization.” Slate, 26 December 2001
Elling, Richard C. 1982. “Ideological Change in the U.S. Senate: Time and Electoral Responsiveness.” Legislative Studies Quarterly, 7(1):75–92CrossRefGoogle Scholar
Embretson, Susan and Reise, Steven P.. 2000. Item Response Theory for Psychologists. Mahwah, NJ: Lawrence ErlbaumGoogle Scholar
Enelow, James M. and Hinich, Melvin. 1984. The Spatial Theory of Voting. New York: Cambridge University PressGoogle Scholar
Ennis, Daniel M. 1988a. “Confusable and Discriminable Stimuli: Comment on Nosofsky (1986) and Shepard (1986).” Journal of Experimental Psychology: General, 117:408–411CrossRefGoogle Scholar
Ennis, Daniel M. 1988b. “Technical Comments: Toward a Universal Law of Generalization.” Science, 242:944CrossRefGoogle Scholar
Ennis, Daniel M., Palen, Joseph J., and Mullen, Kenneth. 1988A Multidimensional Stochastic Theory of Similarity.” Journal of Mathematical Psychology, 32:449–465CrossRefGoogle Scholar
Feldman, Stanley and Zaller, John. 1992Political Culture of Ambivalence: Ideological Responses to the Welfare State.” American Journal of Political Science, 36:268–307CrossRefGoogle Scholar
Ferejohn, John and Satz, Debra. 1996. “Unification, Universalism, and Rational Choice Theory.” In The Rational Choice Controversy, edited by Friedman, Jeffrey. New Haven: Yale University PressGoogle Scholar
Ferejohn, John and Debra Satz. 2000. “Rational Choice Theory and Mental Models.” Working Paper, Stanford University
Feyerabend, Paul K. 1975. Against Method. London: New Left PressGoogle Scholar
Fiorina, Morris P. 1996. “Rational Choice, Empirical Contributions, and the Scientific Enterprise.” In The Rational Choice Controversy, edited by Friedman, Jeffrey. New Haven: Yale University PressGoogle Scholar
Firth, David and Arthur Spirling. 2003. “Divisions of the United Kingdom House of Commons, from 1992 to 2003 and Beyond.” Working Paper, Nuffield College, Oxford
Fischer, Gerhard H. and Molenaar, Ivo W.. 1995. Rasch Models: Foundations, Recent Developments, and Applications. New York: Springer-VerlagCrossRefGoogle Scholar
Garner, Wendell R. 1974. The Processing of Information and Structure. New York: WileyGoogle Scholar
Gelfand, Alan E. and Smith, Adrian F. M.. 1990Sampling-Based Approaches to Calculating Marginal Densities.” Journal of the American Statistical Association, 85:398–409CrossRefGoogle Scholar
Gelman, Andrew. 1992Iterative and Non-iterative Simulation Algorithms.” Computing Science and Statistics, 24:433–438Google Scholar
Gelman, Andrew, Carlin, John B., Stern, Hal S., and Rubin, Donald B.. 2000. Bayesian Data Analysis. New York: Chapman and Hall/CRCGoogle Scholar
Geman, Donald and Geman, Stuart. 1984Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 6:721–741CrossRefGoogle ScholarPubMed
Gerber, Elizabeth R. and Jeffrey B. Lewis. 2002. “Beyond the Median: Voter Preferences, District Heterogeneity, and Representation.” Working Paper, UCLA
Gifi, Albert. 1990. Nonlinear Multivariate Analysis. Chicester, England: WileyGoogle Scholar
Gill, Jeff. 2002. Bayesian Methods: A Social and Behavioral Sciences Approach. Boca Raton, FL: Chapman & Hall/CRCGoogle Scholar
Gleason, Terry C. and Staelin, Richard. 1975A Proposal for Handling Missing Data.” Psychometrika, 40:229–252CrossRefGoogle Scholar
Gluck, Mark A. 1991Stimulus Generalization and Representation in Adaptive Network Models of Category Learning.” Psychological Science, 2:50–55CrossRefGoogle Scholar
Gombrich, Ernst Hans. 1978. The Story of Art (13th edition). New York: Phaidon PressGoogle Scholar
Goodman, Craig. 2004. “Ideological Constraint in Congress: Experiments in Roll Call Voting.” Ph.D. Dissertation, University of Houston
Green, Donald P. and Shapiro, Ian. 1994. Pathologies of Rational Choice Theory: A Critique of Applications in Political Science. New Haven: Yale University PressGoogle Scholar
Greene, William H. 1993. Econometric Analysis. Englewood Cliffs, NJ: Prentice HallGoogle Scholar
Guttman, Louis L. 1944A Basis for Scaling Qualitative Data.” American Sociological Review, 9:139–150CrossRefGoogle Scholar
Guttman, Louis L. 1954. “A New Approach to Factor Analysis.” In Mathematical Thinking in the Social Sciences, edited by Lazarsfeld, P. F.. Glencoe, IL: Free PressGoogle Scholar
Haberman, Shelby J. 1977Maximum Likelihood Estimation in Exponential Response Models.” Annals of Statistics, 5:815–841CrossRefGoogle Scholar
Hammond, Thomas H. and Fraser, Jane M.. 1983Baselines for Evaluating Explanations of Coalition Behavior in Congress.” Journal of Politics, 45:635–656CrossRefGoogle Scholar
Harrington, Joseph. 1992The Role of Party Reputation in the Formation of Policy.” Journal of Public Economics, 49:107–121CrossRefGoogle Scholar
Hastings, W. Keith. 1970Monte Carlo Sampling Methods Using Markov Chains and Their Applications.” Biometrika, 54:97–109CrossRefGoogle Scholar
Heckman, James J. and Snyder, James M.. 1997Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators.” Rand Journal of Economics, 28:142–189CrossRefGoogle Scholar
Heiser, Willem J. 1981. Unfolding Analysis of Proximity Data. Leiden: University of LeidenGoogle Scholar
Hinich, Melvin J. and Munger, Michael. 1994. Ideology and the Theory of Political Choice. Ann Arbor, MI: University of Michigan PressCrossRefGoogle Scholar
Hinich, Melvin J. and Munger, Michael. 1997. Analytical Politics. New York: Cambridge University PressCrossRefGoogle Scholar
Hinich, Melvin J. and Pollard, Walker. 1981A New Approach to the Spatial Theory of Electoral Competition.” American Journal of Political Science, 25:323–341CrossRefGoogle Scholar
Hinich, Melvin J. and Roll, Richard. 1981Measuring Nonstationarity in the Parameters of the Market Model.” Research in Finance, 3:1–51Google Scholar
Hitchcock, David B. 2003A History of the Metropolis–Hastings Algorithm.” The American Statistician, 57:254–257CrossRefGoogle Scholar
Hoadley, John F. 1980The Emergence of Political Parties in Congress, 1789–1803.” American Political Science Review, 74:757–779CrossRefGoogle Scholar
Hoffer, Eric. 1951. The True Believer: Thoughts on the Nature of Mass Movements. New York: Harper & Row (Perennial Library Edition, 1966, 1989)Google Scholar
Hojo, Hiroshi. 1994A New Method for Multidimensional Unfolding.” Behaviormetrika, 21:131–147CrossRefGoogle Scholar
Horst, Paul. 1963. Matrix Algebra for Social Scientists. New York: Holt, Rinehart and WinstonGoogle Scholar
Hotelling, Harold. 1929Stability in Competition.” The Economic Journal, 39:41–57CrossRefGoogle Scholar
Jackman, Simon D. 2000a. “Estimation and Inference via Bayesian Simulation: An Introduction to Markov Chain Monte Carlo.” American Journal of Political Science, 44:375–404CrossRefGoogle Scholar
Jackman, Simon D. 2000b. “Estimation and Inference are ‘Missing Data’ Problems: Unifying Social Science Statistics via Bayesian Simulation.” Political Analysis, 8:307–332CrossRefGoogle Scholar
Jackman, Simon D. 2001Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference and Model Checking.” Political Analysis, 9:227–241CrossRefGoogle Scholar
Jenkins, Jeffery A. and Munger, Michael C.. 2003. “Investigating the Incidence of Killer Amendments in Congress.” Journal of Politics, 65:498–517CrossRefGoogle Scholar
Jenkins, Jeffery A. and Sala, Brian R.. 1998. “The Spatial Theory of Voting and the Presidential Election of 1824.” American Journal of Political Science, 42:1157–1179CrossRefGoogle Scholar
Johnson, Richard M. 1963On a Theorem Stated by Eckart and Young.” Psychometrika, 28:259–263CrossRefGoogle Scholar
Keller, Joseph B. 1962Factorization of Matrices by Least-Squares.” Biometrika, 49:239–242CrossRefGoogle Scholar
Kiewiet, D. Roderick and McCubbins, Mathew D.. 1991. The Logic of Delegation: Congressional Parties and the Appropriation Process. Chicago: University of Chicago PressGoogle Scholar
King, Gary, Honaker, James, Joseph, Anne, and Scheve, Kenneth. 2001Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation.” American Political Science Review, 95:49–69Google Scholar
King, David. 1998. “Party Competition and Polarization in American Politics.” Paper Prepared for the 1998 Annual Meeting of the Midwest Political Science Association
Krehbiel, Keith. 1993. “Where's the Party?” British Journal of Political Science, 23(1):235–266CrossRefGoogle Scholar
Krehbiel, Keith. 1998. Pivotal Politics: A Theory of U.S. Lawmaking. Chicago: University of Chicago PressCrossRefGoogle Scholar
Kruskal, Joseph B. 1964a. “Multidimensional Scaling by Optimizing a Goodness of Fit to a Nonmetric Hypothesis.” Psychometrika, 29:1–27CrossRefGoogle Scholar
Kruskal, Joseph B. 1964b. “Nonmetric Multidimensional Scaling: A Numerical Method.” Psychometrika, 29:115–129CrossRefGoogle Scholar
Kruskal, Joseph B. and Wish, Myron. 1978. Multidimensional Scaling. Beverly Hills, CA: SageCrossRefGoogle Scholar
Kruskal, Joseph B., Forrest W. Young, and Judith B. Seery. 1973. “How to Use KYST: A Very Flexible Program to Do Multidimensional Scaling and Unfolding.” Multidimensional Scaling Program Package of Bell Laboratories, Bell Laboratories, Murray Hill, NJ
Kuhn, Thomas S. 1962/1996. The Structure of Scientific Revolutions (3rd edition). Chicago: University of Chicago PressGoogle Scholar
Ladha, Krishna K. 1991A Spatial Model of Legislative Voting with Perceptual Error.” Public Choice, 68:151–174CrossRefGoogle Scholar
Laudan, Larry. 1984. Science and Values: The Aims of Science and Their Role in Scientific Debate. Berkeley, CA: University of California PressGoogle Scholar
Laudan, Larry. 1996. Beyond Positivism and Relativism: Theory, Method and Evidence. Boulder, CO: Westview PressGoogle Scholar
Lawson, Charles L. and Hanson, Richard J.. 1974. Solving Least Squares Problems. Englewood Cliffs, NJ: Prentice-HallGoogle Scholar
Lewis, Jeffrey B. and King, Gary. 1999No Evidence on Directional vs. Proximity Voting.” Political Analysis, 8:21–33CrossRefGoogle Scholar
Lewis, Jeffrey B. and Poole, Keith T.. 2004. “Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap.” Political Analysis, 12:105–127CrossRefGoogle Scholar
Livingstone, Margaret S. 2002. Vision and Art: The Biology of Seeing. New York: Harry N. AbramsGoogle Scholar
Londregan, John B. 2000a. “Estimating Legislators' Preferred Points.” Political Analysis, 8(1):35–56CrossRefGoogle Scholar
Londregan, John B. 2000b. Legislative Institutions and Ideology in Chile. New York: Cambridge University PressCrossRefGoogle Scholar
Londregan, John B. and Snyder, James M. Jr. 1994Comparing Committee and Floor Preferences.” Legislative Studies Quarterly, 19:233–266CrossRefGoogle Scholar
Loomis, Michael. 1995. “Constituent Influences Outside the Spatial Structure of Legislative Voting.” Doctoral Dissertation, Carnegie-Mellon University
Lord, Frederic M. 1983Unbiased Estimates of Ability Parameters, of Their Variance, and of Their Parallel Forms Reliability.” Psychometrika, 48:477–482CrossRefGoogle Scholar
Lott, John R. Jr. and Bronars, Stephen G.. 1993Time Series Evidence on Shirking in the U.S. House of Representatives.” Public Choice, 76:125–150CrossRefGoogle Scholar
Lublin, David (1997). The Paradox of Representation: Racial Gerrymandering and Minority Representation in Congress. Princeton, NJ: Princeton University PressGoogle Scholar
Macdonald, Stuart, Rabinowitz, George, and Listhaug, Ola. 2001Sophistry versus Science: On Further Efforts to Rehabilitate the Proximity Model.” The Journal of Politics, 63:482–500CrossRefGoogle Scholar
MacRae, Duncan Jr. 1958. Dimensions of Congressional Voting. Berkeley: University of California PressGoogle Scholar
MacRae, Duncan Jr. 1970. Issues and Parties in Legislative Voting. New York: Harper and RowGoogle Scholar
McCarty, Nolan M. 1997. “Presidential Reputation and the Veto.” Economics and Politics, 9(1):1–26CrossRefGoogle Scholar
McCarty, Nolan M. 2000. “Proposal Rights, Veto Rights, and Political Bargaining.” American Journal of Political Science, 44(3):506–522CrossRefGoogle Scholar
McCarty, Nolan M. and Poole, Keith T.. 1995. “Veto Power and Legislation: An Empirical Analysis of Executive and Legislative Bargaining from 1961–1986.” Journal of Law, Economics, and Organization, 11:Google Scholar
McCarty, Nolan M., Poole, Keith T., and Rosenthal, Howard. 1997. Income Redistribution and the Realignment of American Politics. Washington, DC: AEI PressGoogle Scholar
McCarty, Nolan M., Poole, Keith T., and Rosenthal, Howard. 2001The Hunt for Party Discipline in Congress.” American Political Science Review, 95:673–687CrossRefGoogle Scholar
McCarty, Nolan M., Keith T. Poole, and Howard Rosenthal. 2003. “Political Polarization and Income Inequality.” Manuscript, University of Houston
McCarty, Nolan M. and Rothenberg, Lawrence S. (1996). “Commitment and the Campaign Contribution Contract.” American Journal of Political Science, 40:872–904CrossRefGoogle Scholar
McCarty, Nolan M. and Razaghian, Rose. 1999. “Advice and Consent: Senate Response to Executive Branch Nominations 1885–1996.” American Journal of Political Science, 43(3):1122–1143CrossRefGoogle Scholar
McFadden, Daniel. 1976Quantal Choice Analysis: A Survey.” Annals of Economic and Social Measurement, 5:363–390Google Scholar
Manski, Charles F. 1975Maximum Score Estimation of the Stochastic Utility Model of Choice.” Journal of Econometrics, 3:205–228CrossRefGoogle Scholar
Manski, Charles F. 1985Semiparametric Analysis of Discrete Response: Asymptotic Properties of the Maximum Score Estimator.” Journal of Econometrics, 27:313–333CrossRefGoogle Scholar
Manski, Charles F. and Thompson, T. Scott. 1986Operational Characteristics of Maximum Score Estimation.” Journal of Econometrics, 32:85–108CrossRefGoogle Scholar
Martin, Andrew D. 2003Bayesian Inference for Heterogeneous Event Counts.” Sociological Methods and Research, 32:30–63CrossRefGoogle Scholar
Martin, Andrew D. and Kevin M. Quinn. 2001. “Bayesian Learning about Ideal Points of U. S. Supreme Court Justices, 1953–1999.” Working Paper, Washington University, St. Louis
Martin, Andrew D. and Quinn, Kevin M.. 2002Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999.” Political Analysis, 10:134–153CrossRefGoogle Scholar
Merrill, Samuel III and Grofman, Bernard. 1999. A Unified Theory of Voting: Directional and Proximity Models. New York: Cambridge University PressCrossRefGoogle Scholar
Metropolis, Nicholas C. and Ulam, Stanislaw. 1949The Monte Carlo Method.” Journal of the American Statistical Association, 44:335–341CrossRefGoogle ScholarPubMed
Miller, George A. 1956The Magical Number Seven, Plus Minus One: Some Limits on our Capacity for Processing Information.” Psychological Review, 63:81–97CrossRefGoogle Scholar
Morgenstern, Scott. 2004. Patterns of Legislative Politics: Roll-Call Voting in Latin America and the United States. New York: Cambridge University PressGoogle Scholar
Morrison, Richard J. 1972A Statistical Model for Legislative Roll Call Analysis.” Journal of Mathematical Sociology, 2:235–247CrossRefGoogle Scholar
Morton, Rebecca B. 1987A Group Majority Voting Model of Public Good Provision.” Social Choice and Welfare, 4:117–131CrossRefGoogle Scholar
Neyman, Jerzy and Scott, Elizabeth L.. 1948Consistent Estimates Based on Partially Consistent Observations.” Econometrica, 16:1–32CrossRefGoogle Scholar
Nie, Norman H., Verba, Sidney, and Petrocik, John R.. 1979. The Changing American Voter. New York: Replica BooksCrossRefGoogle Scholar
Nokken, Timothy P. 2000Dynamics of Congressional Loyalty: Party Defection and Roll Call Behavior, 1947–1997.” Legislative Studies Quarterly, 25:417–444CrossRefGoogle Scholar
Nokken, Timothy P. and Keith T. Poole. 2004. “Congressional Party Defection in American History.” Legislative Studies Quarterly, forthcoming
Nosofsky, Robert M. 1984Choice, Similarity, and the Context Theory of Classification.” Journal of Experimental Psychology: Learning, Memory and Cognition, 10:104–114Google ScholarPubMed
Nosofsky, Robert M. 1986Attention, Similarity, and the Identification–Categorization Relationship.” Journal of Experimental Psychology: General, 115:39–57CrossRefGoogle ScholarPubMed
Nosofsky, Robert M. 1988On Exemplar-Based Exemplar Representations: Reply to Ennis (1988).” Journal of Experimental Psychology: General, 117:412–414CrossRefGoogle Scholar
Nosofsky, Robert M. 1991Stimulus Bias, Asymmetric Similarity, and Classification.” Cognitive Psychology, 23:94–140CrossRefGoogle Scholar
Nosofsky, Robert M. 1992Similarity Scaling and Cognitive Process Models.” Annual Review of Psychology, 43:25–53CrossRefGoogle Scholar
Oppenheimer, Bruce I. 2000. “The Roll Call Behavior of Members Who Switch Parties, 1900–99: The Effect of Variations in Party Strength.” Paper Presented at the Annual Meeting of the Midwest Political Science Association, Chicago
Ordeshook, Peter C. 1976. “The Spatial Theory of Elections: A Review and a Critique.” In Party Identification and Beyond, edited by Budge, Ian, Crewe, Ivor, and Farlie, Dennis. New York: WileyGoogle Scholar
Ordeshook, Peter C. 1996. “Engineering or Science: What is the Study of Politics?” In The Rational Choice Controversy, edited by Friedman, Jeffrey. New Haven: Yale University PressGoogle Scholar
Palfrey, Thomas R. 1984Spatial Equilibrium with Entry.” Review of Economic Studies, 51:139–157CrossRefGoogle Scholar
Perlstein, Rick. 2001. Before the Storm: Barry Goldwater and the Unmaking of the American Consensus. New York: Hill and WangGoogle Scholar
Platt, Glenn, Poole, Keith T., and Rosenthal, Howard. 1992Directional and Euclidean Theories of Voting Behavior: A Legislative Comparison.” Legislative Studies Quarterly, 17:561–572CrossRefGoogle Scholar
Poole, Keith T. 1981. “Dimensions of Interest Group Evaluations of the U.S. Senate, 1969–1978.” American Journal of Political Science, 25(1):49–67CrossRefGoogle Scholar
Poole, Keith T. 1984Least Squares Metric, Unidimensional Unfolding.” Psychometrika, 49:311–323CrossRefGoogle Scholar
Poole, Keith T. 1988Recent Developments in Analytical Models of Voting in the U.S. Congress.” Legislative Studies Quarterly, 13:117–133CrossRefGoogle Scholar
Poole, Keith T. 1990Least Squares Metric, Unidimensional Scaling of Multivariate Linear Models.” Psychometrika, 55:123–149CrossRefGoogle Scholar
Poole, Keith T. 1997. “Non-parametric Analysis of Binary Choice Data.” Manuscript, University of Houston
Poole, Keith T. 1998Recovering a Basic Space From a Set of Issue Scales.” American Journal of Political Science, 42:954–993CrossRefGoogle Scholar
Poole, Keith T. 1999NOMINATE: A Short Intellectual History.” The Political Methodologist, 9:1–6Google Scholar
Poole, Keith T. 2000a. “Non-parametric Unfolding of Binary Choice Data.” Political Analysis, 8(3):211–237CrossRefGoogle Scholar
Poole, Keith T. 2000b. “Appendix to Non-parametric Unfolding of Binary Choice Data.” Manuscript, University of Houston
Poole, Keith T. 2001. “The Geometry of Multidimensional Quadratic Utility in Models of Parliamentary Roll Call Voting.” Political Analysis, 9(3):211–226CrossRefGoogle Scholar
Poole, Keith T. 2003. “Changing Minds? Not in Congress!” Manuscript, University of Houston
Poole, Keith T. and Romer, Thomas. 1993Ideology, Shirking and Representation.” Public Choice, 77:185–196CrossRefGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 1984a. “U.S. Presidential Elections 1968–1980: A Spatial Analysis.” American Journal of Political Science, 28:282–312CrossRefGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 1984b. “The Polarization of American Politics.” Journal of Politics, 46:1061–1079CrossRefGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 1985A Spatial Model for Legislative Roll Call Analysis.” American Journal of Political Science, 29:357–384CrossRefGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 1987Analysis of Congressional Coalition Patterns: A Unidimensional Spatial Model.” Legislative Studies Quarterly, 12:55–75CrossRefGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 1991. “Patterns of Congressional Voting.” American Journal of Political Science, 35:228–278CrossRefGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 1997. Congress: A Political–Economic History of Roll Call Voting. New York: Oxford University PressGoogle Scholar
Poole, Keith T. and Rosenthal, Howard. 2001. “D-NOMINATE After 10 Years: A Comparative Update to Congress: A Political–Economic History of Roll Call Voting.” Legislative Studies Quarterly, 26:5–26CrossRefGoogle Scholar
Poole, Keith T., Sowell, Fallaw B., and Spear, Stephen E.. 1992Evaluating Dimensionality in Spatial Voting Models.” Mathematical and Computer Modeling, 16: 85–101CrossRefGoogle Scholar
Quinn, Kevin M. 2004Bayesian Factor Analysis for Mixed Ordinal and Continuous Responses.” Political Analysis, 12:338–353CrossRefGoogle Scholar
Quinn, Kevin M. and Martin, Andrew D.. 2002An Integrated Computational Model of Multiparty Electoral Competition.” Statistical Science, 17:405–419Google Scholar
Quinn, Kevin M., Martin, Andrew D., and Whitford, Andrew B.. 1999Voter Choice in Multi-party Democracies: A Test of Competing Theories and Models.” American Journal of Political Science, 43:1231–1247CrossRefGoogle Scholar
Rabinowitz, George. 1976A Procedure for Ordering Object Pairs Consistent with the Multidimensional Unfolding Model.” Psychometrika, 45:349–373CrossRefGoogle Scholar
Rabinowitz, George and Macdonald, Stuart. 1989A Directional Theory of Issue Voting.” American Political Science Review, 83:93–121CrossRefGoogle Scholar
Rasch, Georg. 1961. “On General Laws and the Meaning of Measurement in Psychology.” In Proceedings of the IV Berkeley Symposium on Mathematical Statistics and Probability, vol. 4, pp. 321–333
Riker, William H. 1982/1988. Liberalism Against Populism: A Confrontation Between the Theory of Democracy and the Theory of Social Choice. Prospect Heights, IL: Waveland PressGoogle Scholar
Rivers, Douglas. 2004. “Identification of Multidimensional Spatial Voting Models.” Manuscript, Stanford University
Romano, Roberta. 1997The Political Dynamics of Derivative Securities Regulation.” Yale Journal on Regulation, 14:279–406Google Scholar
Rosenberg, Seymour, Nelson, Carnot, and Vivekananthan, P. S.. 1968A Multidimensional Approach to the Structure of Personality Impressions.” Journal of Personality and Social Psychology, 9:283–294CrossRefGoogle ScholarPubMed
Rosenthal, Howard and Voeten, Erik. 2004. “Analyzing Roll Calls with Perfect Spatial Voting: France 1946–1958.” American Journal of Political Science, 48:620–632CrossRefGoogle Scholar
Ross, John and Cliff, Norman. 1964A Generalization of the Interpoint Distance Model.” Psychometrika, 29:167–176CrossRefGoogle Scholar
Rothenberg, Lawrence S. and Sanders, Mitchell S.. 2000Severing the Electoral Connection: Shirking in the Contemporary Congress.” American Journal of Political Science, 44:316–325CrossRefGoogle Scholar
Rothkopf, Ernst Z. 1957A Measure of Stimulus Similarity and Errors in Some Paired-Associate Learning Tasks.” Journal of Experimental Psychology, 53:94–101CrossRefGoogle ScholarPubMed
Ruger, Theodore W., Kim, Pauline T., Martin, Andrew D., and Quinn, Kevin M.. 2004. “The Supreme Court Forecasting Project: Legal and Political Science Approaches to Predicting Supreme Court Decision-Making.” Columbia Law Review, 104:1150–1209CrossRefGoogle Scholar
Schofield, Norman. 1996. “Rational Choice Theory and Political Economy.” In The Rational Choice Controversy, edited by Friedman, Jeffrey. New Haven: Yale University PressGoogle Scholar
Schofield, Norman, Martin, Andrew D., Quinn, Kevin M., and Whitford, Andrew B.. 1998Multiparty Electoral Competition in the Netherlands and Germany: A Model Based on Multinomial Probit.” Public Choice, 97:257–293CrossRefGoogle Scholar
Schonemann, Peter H. 1966A Generalized Solution of the Orthogonal Procrustes Problem.” Psychometrika, 31:1–10CrossRefGoogle Scholar
Schonemann, Peter H. 1970Fitting a Simplex Symmetrically.” Psychometrika, 35: 1–21CrossRefGoogle Scholar
Schonemann, Peter H. and Carroll, Robert M.. 1970Fitting One Matrix to Another Under Choice of a Central Dilation and Rigid Motion.” Psychometrika, 35:245–256CrossRefGoogle Scholar
Schonhardt-Bailey, Cheryl. 2003. “Ideology, Party and Interests in the British Parliament of 1841–1847,” British Journal of Political Science, 33:581–605CrossRefGoogle Scholar
Schonhardt-Bailey, Cheryl. 2004. Interests, Ideas and Institutions: Repeal of the Corn Laws Re-told. Manuscript, London School of Economics and Political Science
Sen, Amartya K. 1970. Collective Choice and Social Welfare. San Francisco, CA: Holden-DayGoogle Scholar
Shepard, Roger N. 1962a. “The Analysis of Proximities: Multidimensional Scaling with an Unknown Distance Function. I.” Psychometrika, 27:125–139CrossRefGoogle Scholar
Shepard, Roger N. 1962b. “The Analysis of Proximities: Multidimensional Scaling with an Unknown Distance Function. II.” Psychometrika, 27: 219–246CrossRefGoogle Scholar
Shepard, Roger N. 1963Analysis of Proximities as a Technique for the Study of Information Processing in Man.” Human Factors, 5:33–48CrossRefGoogle Scholar
Shepard, Roger N. 1986Discrimination and Generalization in Identification and Classification: Comment on Nosofsky.” Journal of Experimental Psychology: General, 115:58–61CrossRefGoogle Scholar
Shepard, Roger N. 1987Toward a Universal Law of Generalization for Psychological Science.” Science, 237:1317–1323CrossRefGoogle Scholar
Shepard, Roger N. 1988a. “Technical Comments: Toward a Universal Law of Generalization.” Science, 242:944CrossRefGoogle Scholar
Shepard, Roger N. 1988b. “Time and Distance in Generalization and Discrimination: Reply to Ennis (1988).” Journal of Experimental Psychology: General, 117:415–416CrossRefGoogle Scholar
Shepard, Roger N. 1991. “Integrality Versus Separability of Stimulus Dimensions: Evolution of the Distinction and a Proposed Theoretical Basis.” In Perception of Structure, edited by Pomerantz, James R. and Lockhead, Gregory. Washington, DC: APAGoogle Scholar
Shepsle, Kenneth A. 1996. “Statistical Political Philosophy and Positive Political Theory.” In The Rational Choice Controversy, edited by Friedman, Jeffrey. New Haven: Yale University PressGoogle Scholar
Shipan, Charles R. and Moraski, Bryon. 1999The Politics of Supreme Court Nominations: A Theory of Institutional Constraints and Choices.” American Journal of Political Science, 43:1069–1095Google Scholar
Silvapulle, Mervyn J. 1981. “On the Existence of Maximum Likelihood Estimators for the Binomial Response Models.” Journal of the Royal Statistical Society Series B, 43(3):310–313Google Scholar
Simmons, George F. 1972. Differential Equations with Applications and Historical Notes. New York: McGraw-HillGoogle Scholar
Smithies, Arthur. 1941Optimum Location in Spatial Competition.” The Journal of Political Economy, 49:423–439CrossRefGoogle Scholar
Snyder, James M. Jr. 1992Artificial Extremism in Interest Group Ratings.” Legislative Studies Quarterly, 17:319–345CrossRefGoogle Scholar
Snyder, James M. Jr., and Groseclose, Timothy. 2000. “Estimating Party Influence in Congressional Roll-Call Voting.” American Journal of Political Science, 44(2):193–211CrossRefGoogle Scholar
Sowell, Thomas. 1987. A Conflict of Visions: Ideological Origins of Political Struggles. New York: QuillGoogle Scholar
Spector, David. 2000Rational Debate and One-Dimensional Conflict.” Quarterly Journal of Economics, 115:181–200CrossRefGoogle Scholar
Stratmann, Thomas. 2000Congressional Voting Over Legislative Careers: Shifting Positions and Changing Constraints.” The American Political Science Review, 94:665–676CrossRefGoogle Scholar
Tajfel, Henri. 1981. Human Groups and Social Categories. London: Cambridge University PressGoogle Scholar
Thomas, Martin. 1985. “Election Proximity and Senatorial Roll Call Voting.” American Journal of Political Science, 29(1):96–111CrossRefGoogle Scholar
Torgerson, Warren S. 1952Multidimensional Scaling: I. Theory and Method.” Psychometrika, 17:401–419CrossRefGoogle Scholar
Treier, Shawn and Simon Jackman. 2003. “Democracy as a Latent Variable.” Manuscript, Stanford University
Tucker, Ledyard R. 1960. “Intra-individual and Inter-individual Multidimensionality.” In Psychological Scaling: Theory and Applications, edited by Gulliksen, Harold and Messick, Samuel. New York: WileyGoogle Scholar
Tversky, Amos. 1977Features of Similarity.” Psychological Review, 84:327–352CrossRefGoogle Scholar
Voeten, Erik. 2000Clashes in the Assembly.” International Organization, 54:185–215CrossRefGoogle Scholar
Voeten, Erik. 2001Outside Options and the Logic of Security Council Action.” The American Political Science Review, 95:845–858CrossRefGoogle Scholar
Voeten, Erik. 2004. “Resisting the Lonely Superpower: Responses of States in the U.N. to U.S. Dominance.” Journal of Politics, 66:729–754CrossRefGoogle Scholar
Wang, Ming-Mei, Schonemann, Peter H., and Rusk, Jerrold G.. 1975A Conjugate Gradient Algorithm for the Multidimensional Analysis of Preference Data.” Multivariate Behavioral Research, 10:45–80CrossRefGoogle ScholarPubMed
Weisberg, Herbert F. 1968. Dimensional Analysis of Legislative Roll Calls. Doctoral Dissertation, University of Michigan
Weisberg, Herbert F. 1978Evaluating Theories of Congressional Roll-Call Voting.” American Journal of Political Science, 22:551–577CrossRefGoogle Scholar
Weisberg, Herbert F. 1983Alternative Baseline Models and Their Implications for Understanding Coalition Behavior in Congress.” Journal of Politics, 45:657–671CrossRefGoogle Scholar
Weisberg, Herbert F. and Rusk, Jerrold G.. 1970Dimensions of Candidate Evaluation.” American Political Science Review, 64:1167–1185CrossRefGoogle Scholar
Wills, Garry. 1982. The Federalist Papers by Alexander Hamilton, James Madison, and John Jay. New York: Bantam Books
Wish, Myron. 1971. “Individual Differences in Perceptions and Preferences Among Nations.” In Attitude Research Reaches New Heights, edited by King, Charles W. and Tigert, Douglas J.. Chicago: American Marketing AssociationGoogle Scholar
Wish, Myron and Carroll, J. Douglas. 1974. “Applications of Individual Differences Scaling to Studies of Human Perception and Judgment.” In Handbook of Perception, vol. 2, edited by Carterette, Edward C. and Friedman, Morton P.. New York: Academic PressGoogle Scholar
Wittman, Donald A. 1977Candidates with Policy Preferences: A Dynamic Model.” Journal of Economic Theory, 14:180–189CrossRefGoogle Scholar
Wittman, Donald A. 1983. “Candidate Motivations: A Synthesis of Alternatives.” American Political Science Review, 77:142–157CrossRefGoogle Scholar
Wright, Gerald C. and Berkman, Michael B.. 1986. “Candidates and Policy in United States Senate Elections.” American Political Science Review, 80(2):567–588CrossRefGoogle Scholar
Wright, Gerald C. and Schaffner, Brian F.. 2002The Influence of Party: Evidence from the State Legislatures.” American Political Science Review, 96:367–379CrossRefGoogle Scholar
Young, Gale and Householder, A. S.. 1938Discussion of a Set of Points in Terms of their Mutual Distances.” Psychometrika, 3:19–22CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • Keith T. Poole, University of California, San Diego
  • Book: Spatial Models of Parliamentary Voting
  • Online publication: 24 November 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511614644.009
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Keith T. Poole, University of California, San Diego
  • Book: Spatial Models of Parliamentary Voting
  • Online publication: 24 November 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511614644.009
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Keith T. Poole, University of California, San Diego
  • Book: Spatial Models of Parliamentary Voting
  • Online publication: 24 November 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511614644.009
Available formats
×