eco: R package for ecological inference in 2 × 2 tables

Kosuke Imai, Ying Lu, Aaron Strauss

Research output: Contribution to journalArticlepeer-review

Abstract

eco is a publicly available R package that implements the Bayesian and likelihood methods proposed in Imai, Lu, and Strauss (2008b) for ecological inference in 2 × 2 tables as well as the method of bounds introduced by (Duncan and Davis 1953). The package ts both parametric and nonparametric models using either the Expectation-Maximization algorithms (for likelihood models) or the Markov chain Monte Carlo algorithms (for Bayesian models). For all models, the individual-level data can be directly incorporated into the estimation whenever such data are available. Along with in-sample and out-of-sample predictions, the package also provides a functionality which allows one to quantify the e ect of data aggregation on parameter estimation and hypothesis testing under the parametric likelihood models. This paper illustrates the usage of eco with several real data examples that are also part of the package.

Original languageEnglish (US)
Pages (from-to)1-23
Number of pages23
JournalJournal of Statistical Software
Volume42
Issue number5
DOIs
StatePublished - Jun 2011

Keywords

  • Aggregate data
  • Bayesian inference
  • Bounds
  • Likelihood inference
  • Missing data
  • Missing information

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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