Krahasoni metodat

	Manifesto Coding	Ideal Point Estimation
Fusha	Political Science	Political Science
Familja	Process / pipeline	Latent structure
Viti i origjinës	2001	2004
Krijuesi	Manifesto Research Group / Comparative Manifesto Project (CMP/MARPOR)	Clinton, Jackman & Rivers (Bayesian formulation); Poole & Rosenthal (spatial tradition)
Lloji	Quantitative content analysis of party manifestos	Latent-variable spatial model of binary choice data
Burimi themelues	Budge, I., Klingemann, H.-D., Volkens, A., Bara, J., & Tanenbaum, E. (2001). Mapping Policy Preferences: Estimates for Parties, Electors, and Governments 1945–1998. Oxford: Oxford University Press. ISBN: 9780199244003	Clinton, J., Jackman, S., & Rivers, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355–370.
Emërtime të tjera	CMP coding, MARPOR coding, Manifesto content analysis, Party manifesto coding	Ideal point model, Item response theory for roll calls, Spatial voting model, Bayesian ideal points
Të lidhura	4	4
Përmbledhja	Manifesto coding is the quantitative content-analysis methodology of the Comparative Manifesto Project (CMP/MARPOR) for measuring parties' policy preferences from their election manifestos. Trained coders break each manifesto into quasi-sentences and assign every unit to one of a fixed set of policy categories. Counting how often each category appears yields salience measures, and combining pro- and anti- categories produces position scores such as the left–right RILE index, giving comparable estimates of party positions across more than fifty democracies since 1945.	Ideal point estimation recovers the latent policy positions — ideal points — of political actors from their observed binary choices, most often legislators' yea/nay votes on roll calls. Building on the spatial theory of voting and formalized as a Bayesian item-response model by Clinton, Jackman, and Rivers in 2004, it places each legislator and each bill in a low-dimensional policy space and estimates positions so that the probability a legislator votes yea increases as the bill's 'yea' outcome moves closer to that legislator's ideal point.