Learn R Programming

⚠️There's a newer version (2.0.89) of this package.Take me there.

epiR (version 0.9-27)

Functions for analysing epidemiological data

Description

A package for analysing epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.

Copy Link

Version

Install

install.packages('epiR')

Monthly Downloads

16,014

Version

0.9-27

License

GPL (>= 2)

Maintainer

Mark Stevenson

Last Published

September 20th, 2010

Functions in epiR (0.9-27)

Summary measures for count data presented in a 2 by 2 table

epi.indirectadj

Indirectly adjusted rates

Estimate population size

Instantaneous hazard computed on the basis of a Kaplan-Meier survival function

Bohning's test for overdispersion of Poisson data

Kappa statistic

Estimate herd test characteristics

Confidence intervals for means, proportions, incidence, and standardised mortality ratios

Convert British National Grid georeferences to easting and northing coordinates

The library epiR: summary information

Concordance correlation coefficient

Write matrix to an ASCII raster file

epi.descriptives

Descriptive statistics

Estimate true prevalence

Fixed-effects meta-analysis of binary outcomes using the Mantel-Haenszel method

Laryngeal and lung cancer cases in Lancashire 1974 - 1983

Post-test probability of disease given sensitivity and specificity of a test

Empirical Bayes estimates

epi.cluster2size

Sample size under under two-stage cluster sampling

Sample size under under simple random sampling

Estimate herd test characteristics when pooled sampling is used

Sample size to detect disease

Estimated dissemination ratio

epi.cluster1size

Sample size under under one-stage cluster sampling

Extract unique covariate patterns from a data set

Sample size under under stratified random sampling

Rates of use of epidural anaesthesia in trials of caregiver support

epi.interaction

Relative excess risk due to interaction in a case-control study

R to WinBUGS data conversion

Estimate the precision of a [structured] heterogeneity term

Lip cancer in Scotland 1975 - 1980

Decimal degrees and degrees, minutes and seconds conversion

Covariate pattern residuals from a logistic regression model

Directly adjusted measures of disease frequency

Fixed-effect meta-analysis of binary outcomes using the inverse variance method

Estimate the sample size to compare means, proportions, and survival

Fixed-effect meta-analysis of continuous outcomes using the standardised mean difference method

Lactation to date and standard lactation milk yields

epi.clustersize

Sample size for cluster-sample surveys

Mixed-effects meta-analysis of binary outcomes using the DerSimonian and Laird method

Partial rank correlation coefficients

Sensitivity, specificity and predictive value of a diagnostic test

Create offset vector