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epiR (version 1.0-15)

Tools for the Analysis of Epidemiological Data

Description

Tools for the analysis of 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.

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Version

Install

install.packages('epiR')

Monthly Downloads

13,920

Version

1.0-15

License

GPL (>= 2)

Maintainer

Mark Stevenson

Last Published

June 14th, 2020

Functions in epiR (1.0-15)

The library epiR: summary information

Lip cancer in Scotland 1975 - 1980

An R version of Wes Johnson and Chun-Lung Su's Betabuster

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

R to WinBUGS data conversion

Convert British National Grid georeferences to easting and northing coordinates

Write matrix to an ASCII raster file

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

Bohning's test for overdispersion of Poisson data

Extract unique covariate patterns from a data set

Concordance correlation coefficient

Estimated dissemination ratio

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

Decimal degrees and degrees, minutes and seconds conversion

epi.descriptives

Descriptive statistics

Kappa statistic

Directly adjusted incidence rate estimates

Rates of use of epidural anaesthesia in trials of caregiver support

Estimate the precision of a [structured] heterogeneity term

Lactation to date and standard lactation milk yields

Empirical Bayes estimates of observed event counts

Create offset vector

Overall concordance correlation coefficient (OCCC)

epi.indirectadj

Indirectly adjusted incidence risk estimates

Sample size, power or minimum detectable incidence risk ratio for a cohort study using individual count data

epi.ssclus2estc

Number of clusters to be sampled to estimate a continuous outcome using two-stage cluster sampling

Event instantaneous hazard based on Kaplan-Meier survival estimates

Sample size for a parallel equivalence trial, continuous outcome

Estimate herd test characteristics when pooled sampling is used

epi.ssstrataestc

Sample size to estimate a continuous outcome using a stratified random sampling design

Covariate pattern residuals from a logistic regression model

epi.interaction

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

Sample size for a parallel superiority trial, binary outcome

Sample size for a non-inferiority trial, binary outcome

Partial rank correlation coefficients

Sample size, power or minimum detectable incidence rate ratio for a cohort study using person or animal time data

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

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

Estimate true prevalence

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

Estimate the characteristics of diagnostic tests applied at the herd (group) level

Sample size, power or minimum detectable odds ratio for an unmatched or matched case-control study

Sample size, power and minimum detectable risk ratio when comparing binary outcomes

epi.sssimpleestc

Sample size to estimate a continuous outcome using simple random sampling

epi.ssstrataestb

Sample size to estimate a binary outcome using stratified random sampling

epi.ssclus2estb

Number of clusters to be sampled to estimate a binary outcome using two-stage cluster sampling

epi.ssclus1estc

Sample size to estimate a continuous outcome using one-stage cluster sampling

Sample size to detect an event

Estimate population size

epi.ssclus1estb

Sample size to estimate a binary outcome using one-stage cluster sampling

Sample size for a parallel equivalence trial, binary outcome

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

Laryngeal and lung cancer cases in Lancashire 1974 - 1983

Sample size for a parallel superiority trial, continuous outcome

Sample size, power and minimum detectable hazard when comparing time to event

Confidence intervals and tests of significance of the standardised mortality [morbidity] ratio

Sample size for a non-inferiority trial, continuous outcome

Sample size, power and minimum detectable difference when comparing continuous outcomes

Sample size, power or minimum detectable prevalence ratio for a cross-sectional study

epi.sssimpleestb

Sample size to estimate a binary outcome using simple random sampling

epiR-deprecated

Deprecated epiR functions

Sensitivity, specificity and predictive value of a diagnostic test