`install.packages('epiR')`

13,779

2.0.53

GPL (>= 2)

October 31st, 2022

epi.2by2

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

epi.betabuster

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

epi.ccc

Concordance correlation coefficient

epi.SClip

Lip cancer in Scotland 1975 - 1980

epi.asc

Write matrix to an ASCII raster file

epi.conf

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

epi.bohning

Bohning's test for overdispersion of Poisson data

epi.blcm.paras

Number of parameters to be inferred and number of informative priors required for a Bayesian latent class model

epi.RtoBUGS

R to WinBUGS data conversion

epi.about

The library epiR: summary information

epi.cpresids

Covariate pattern residuals from a logistic regression model

epi.dsl

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

epi.descriptives

Descriptive statistics

epi.directadj

Directly adjusted incidence rate estimates

epi.convgrid

Convert British National Grid georeferences to easting and northing coordinates

epi.cp

Extract unique covariate patterns from a data set

epi.edr

Estimated dissemination ratio

epi.dgamma

Estimate the precision of a [structured] heterogeneity term

epi.empbayes

Empirical Bayes estimates of observed event counts

epi.dms

Decimal degrees and degrees, minutes and seconds conversion

epi.iv

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

epi.incin

Laryngeal and lung cancer cases in Lancashire 1974 - 1983

epi.kappa

Kappa statistic

epi.epidural

Rates of use of epidural anaesthesia in trials of caregiver support

epi.herdtest

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

epi.mh

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

epi.ltd

Lactation to date and standard lactation milk yields

epi.indirectadj

Indirectly adjusted incidence risk estimates

epi.interaction

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

epi.insthaz

Event instantaneous hazard based on Kaplan-Meier survival estimates

epi.psi

Proportional similarity index

epi.prev

Estimate true prevalence and the expected number of false positives

epi.popsize

Estimate population size on the basis of capture-recapture sampling

epi.prcc

Partial rank correlation coefficients

epi.smr

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

epi.smd

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

epi.pooled

Estimate herd test characteristics when pooled sampling is used

epi.nomogram

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

epi.offset

Create offset vector

epi.occc

Overall concordance correlation coefficient (OCCC)

epi.sscompc

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

epi.sscompb

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

epi.sscc

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

epi.ssclus1estc

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

epi.ssclus2estc

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

epi.ssclus2estb

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

epi.ssclus1estb

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

epi.sscohortt

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

epi.sscohortc

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

epi.sscomps

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

epi.ssstrataestb

Sample size to estimate a binary outcome using stratified random sampling

epi.ssequb

Sample size for a parallel equivalence trial, binary outcome

epi.ssequc

Sample size for a parallel equivalence trial, continuous outcome

epi.ssdxtest

Sample size to validate a diagnostic test in the absence of a gold standard

epi.ssninfc

Sample size for a non-inferiority trial, continuous outcome

epi.ssdetect

Sample size to detect an event

epi.sssimpleestc

Sample size to estimate a continuous outcome using simple random sampling

epi.sssimpleestb

Sample size to estimate a binary outcome using simple random sampling

epi.ssninfb

Sample size for a non-inferiority trial, binary outcome

epi.ssdxsesp

Sample size to estimate the sensitivity or specificity of a diagnostic test

epi.ssstrataestc

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

epi.sssupb

Sample size for a parallel superiority trial, binary outcome

epi.tests

Sensitivity, specificity and predictive value of a diagnostic test

rsu.adjrisk

Adjusted risk values

rsu.pfree.equ

Equilibrium probability of disease freedom assuming representative or risk based sampling

rsu.pfree.rs

Calculate the probability of freedom for given population sensitivity and probability of introduction

rsu.epinf

Effective probability of disease

epi.ssxsectn

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

epi.sssupc

Sample size for a parallel superiority trial, continuous outcome

rsu.dxtest

Sensitivity and specificity of diagnostic tests interpreted in series or parallel

rsu.sep.rbvarse

Surveillance system sensitivity assuming risk based sampling and varying unit sensitivity

rsu.sep.cens

Surveillance system sensitivity assuming data from a population census

rsu.sep.pass

Surveillance system sensitivity assuming passive surveillance and representative sampling within clusters

rsu.sep.rb2rf

Surveillance system sensitivity assuming risk-based sampling on two risk factors

rsu.sep.rs

Surveillance system sensitivity assuming representative sampling

rsu.sep.rb1rf

Surveillance system sensitivity assuming risk-based sampling on one risk factor

rsu.sep.rb

Surveillance system sensitivity assuming risk-based sampling and varying unit sensitivity

rsu.pstar

Design prevalence back calculation

rsu.sep

Probability that the prevalence of disease in a population is less than or equal to a specified design prevalence

rsu.sep.rsmult

Surveillance system sensitivity by combining multiple surveillance components

rsu.sep.rb2st

Surveillance system sensitivity assuming risk based, two-stage sampling

rsu.sssep.rb2st2rf

Sample size to achieve a desired surveillance system sensitivity assuming risk-based 2-stage sampling on two risk factors at either the cluster level, unit level, or both

rsu.sep.rs2st

Surveillance system sensitivity assuming representative two-stage sampling

rsu.sep.rspool

Surveillance system sensitivity assuming representative sampling, imperfect pooled sensitivity and perfect pooled specificity

rsu.sssep.rbmrg

Sample size to achieve a desired surveillance system sensitivity assuming risk-based sampling and multiple sensitivity values within risk groups

rsu.sep.rsfreecalc

Surveillance system sensitivity for detection of disease assuming representative sampling and imperfect test sensitivity and specificity.

rsu.sssep.rsfreecalc

Sample size to achieve a desired surveillance system sensitivity to detect disease at a specified design prevalence assuming representative sampling, imperfect unit sensitivity and specificity

rsu.sssep.rs2st

Sample size to achieve a desired surveillance system sensitivity assuming two-stage sampling

rsu.sep.rsvarse

Surveillance system sensitivity assuming representative sampling and varying unit sensitivity

rsu.sssep.rbsrg

Sample size to achieve a desired surveillance system sensitivity assuming risk-based sampling and a single sensitivity value for each risk group

rsu.spp.rs

Surveillance system specificity assuming representative sampling

rsu.sspfree.rs

Sample size to achieve a desired probability of disease freedom assuming representative sampling

rsu.sssep.rs

Sample size to achieve a desired surveillance system sensitivity assuming representative sampling

rsu.sssep.rb2st1rf

Sample size to achieve a desired surveillance system sensitivity assuming risk-based 2-stage sampling on one risk factor at the cluster level

rsu.sssep.rspool

Sample size to achieve a desired surveillance system sensitivity using pooled samples assuming representative sampling