Some statistics and data links I liked:;

• Economics 584Time Series Econometrics – Lecture notes, readings etc. on time series – excellent.
• Martin-Quinn Scores : Description – Measuring the relative location of U.S. Supreme Court justices on an ideological continuum allows us to better understand the politics of the high court. In addition, such measures are an important building blocking of statistical models of the Supreme Court, the separation of powers system, and the judicial hierarchy. This website contains the so-called “Martin-Quinn” measures of judicial ideology developed by Andrew D. Martin (Washington University, School of Law) and Kevin M. Quinn (Harvard University, Department of Government)
• Data.gov – The purpose of Data.gov is to increase public access to high value, machine readable datasets generated by the Executive Branch of the Federal Government.
• CRAN – Package LearnBayes – LearnBayes contains a collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.
• Event History Analysis: Statnotes, from North Carolina State University, Public Administration Program – Event history analysis (also called survival analysis, duration analysis, or transition analysis) is an umbrella term for a set of procedures for time series analysis. Coleman (1981: 1) defined event history analysis in terms of three attributes: (1) data units (ex., individuals or organizations) move along a finite series of states; (2) at any time point, changes (events) may occur, not just at certain time points; and (3) factors influencing events are of two types, time-constant and time-dependent. Event history models focus on the hazard function, which has to do with the probabilities that an event will occur after any given duration. Duration to the hazard of death was the classic example in medical research, but the hazard may have a positive meaning also, such as duration until the event of adoption of an innovation in diffusion research.
• Professor Jan Box-Steffensmeier Political Science 867 Event History – With reading list and slidesTopic 1: Event History Models: Introduction and Overview
Topic 2: Parametric Models
Topic 3: Cox’s Proportional Hazards Model
Topic 4: Discrete Time Formulations
Topic 5: Model Selection
Topic 6: Model Selection, Assessment, Specification, & Diagnostic Methods
Topic 7: Heterogeneity and Multiple Events

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