Examples in ARM book
These are all included as subdirectories at http://www.stat.columbia.edu/~gelman/arm/
academy.awards: Iain Pardoe's data on Academy Award nominees, used in an exercise on discrete choice models in Chapter 6
age.guessing: students' guesses of persons' ages based on photographs, used as an exercise in Chapter 13 for a model with unequal variances
arsenic: data on switching drinking water wells in Bangladesh, used in Chapter 5 to illustrate logistic regression
beauty: Daniel Hamermesh's data on beauty and teaching evaluations, used in regression exercises in Chapters 3 and 4
beta.blockers: data from a meta-analysis of medical experiments, used in Gelman et al. (2003, chapter 5) and in an exercise in Chapter 17 to illustrate multilevel logistic regression
bypass: hypothetical data from a coronary bypass experiment for an exercise in Chapter 10
cd4: CD4 counts for a panel study of children with hiv, used to illustrate repeated measurement data in an exercise in Chapter 11, multilevel model fitting in an exercise in Chapter 12, sample size calculations in Chapter 20, and methods of summarizing a fitted model in Chapter 21
censoring: data for height and weight, and R and Bugs code for censored data model in Section 18.5
chicks: estimates from a series of experiments on the effect of low-frequency magnetic fields on chick brains, used in Chapter 21 to illustrate multiple comparisons and in an exercise in Chapter 22 to illustrate analysis of variance
child.iq: study of children's IQ's used in Chapter 3 to illustrate linear regression
congress: data on elections to the U.S. House of Representatives, incumbency status, and ideology of Congressmembers, used in Chapter 7 to illustrate simulation-based predictions, in Chapter 10 to illustrate regression discontinuity analysis, and in exercises in Chapters 9 and 10 for causal inference in observational studies
coop: tallies from an election for the board of a cooperative housing organization, used in Chapter 2 for testing the hypothesis of underdispersion in count data
correlation: fake data simulation showing "regression to the mean" in Chapter 4
cows: a messy randomized experiment, used in an exercise in Chapter 9 to illustrate ignorability
death.polls: time series of Gallup polls on the death penalty, used in Chapter 2 to show simple confidence intervals
death.sentences: death penalty reversal rates by state and year, used in Chapter 14 as an example of a overdispersed binomial model with non-nested groupings
dogs: data from the Solomon and Wynne experiment on shock-avoidance trials in 30 dogs, used in Chapter 24 to illustrate checking the fit of multilevel models
earnings: data on height, weight, earnings, and other variables from a national survey (Chapters 4 and 13)
election88: pre-election polls from 1988, along with Census data, used to estimate public opinion by state with multilevel logistic regression in Chapter 14
electric.company: before/after data from an experiment in which elementary-school classes were shown or not shown the Electric Company television show, used in Chapter 9 to illustrate causal inference using regression
exam: data on correct and incorrect exam questions, used in Chapter 14 for an exercise on item-response modeling
girls: the proportion of girl births in Vienna for 24 consecutive months, from Mises (1953), used in an exercise in Chapter 2 for testing the binomial model
lalonde: data from the National Supported Work study analyzed by Lalonde and used in an exercise in Chapter 6
lightspeed: Simon Newcomb's measurements of the speed of light, used in Chapter 8 to illustrate model checking
moderation: ideology and vote of U.S. Congressmembers, used in a regression discontinuity analysis in Chapter 10
nes: data from the National Election Study, used in Chapters 4 and 5 to show a time series of linear and logistic regressions and in an exercise in Chapter 5 to illustrate nonidentifiability in logistic regression
olympics: figure-skating judgments from the 1992 Winter Olympics, used in exercises in Chapter 11 and 22 to illustrate non-nested multilevel structure and analysis of variance
pictures: code for some pictures of models used in different chapters of the book
pilots: data from a flight-simulator experiment, used in Chapter 12 as an example of non-nested groupings
pollution: old dataset of mortality and pollution in 60 U.S. cities, used in an exercise in Chapter 4 to illustrate transformations in linear regression
pyth: simple dataset for a linear regression exercise in Chapter 3
radon: survey of home radon levels, used throughout Parts 2 and 3 to illustrate basic multilevel modeling
risky.behavior: data from an experiment on a behavioral intervention for HIV transmission, used in an exercise in Chapter 6 to show Poisson regression
roaches: before/after data from an experiment on pest control in a small sample of city apartments, used in Chapters 6 and 8 to illustrate overdispersed Poisson regression
rodents: data on rodent infestation in a large sample of city apartments, used in exercises in Chapters 5 and 14 on classical and multilevel logistic regression
rsquared: simple simulation illustrating residual standard deviation and explained variance in Chapter 3
samplesize: simulations for sample size calculations in Chapter 20
schools: educational testing experiments in 8 schoools, from Rubin (1981) and Gelman et al. (2003, chapter 5), used in Chapter 19 to evaluate prior distributions for the group-level variance parameter
sesame: data from an experiment showing children the Sesame Street television program, used in an exercise in Chapter 9 as an example of a randomized encouragement design
simulation: examples of simulations from Chapters 7 and 8
sis: NYC Social Indicators Survey, used in Chapter 25 to illustrate missing-data imputation
smoking: data from John Carlin's survey of adolescent smoking, used in Section 11.3 to illustrate repeated measurements
speed.dating: data from Ray Fisman's and Sheena Iyengar's speed-dating experiment, used in an exercise in Chapter 13 on multilevel logistic regression
storable: data from storable votes experiment used in Chapter 6 as an example of ordered multinomial logistic regression
supreme.court: Spaeth's database of U.S. Supreme Court votes, used in Chapter 14 for an exercise on ideal-point modeling
unemployment: unemployment time series, used in Chapter 8 to illustrate simulation-based model checking