| epi.2by2 |
Summary measures for count data presented in a 2 by 2 table |
| epi.about |
The library epiR: summary information |
| epi.asc |
Write matrix to an ASCII raster file |
| epi.betabuster |
An R version of Wes Johnson and Chun-Lung Su's Betabuster |
| epi.blcm.paras |
Number of parameters to be inferred and number of informative priors required for a Bayesian latent class model |
| epi.bohning |
Bohning's test for overdispersion of Poisson data |
| epi.ccc |
Concordance correlation coefficient |
| epi.conf |
Confidence intervals for means, proportions, incidence, and standardised mortality ratios |
| epi.convgrid |
Convert British National Grid georeferences to easting and northing coordinates |
| epi.cp |
Extract unique covariate patterns from a data set |
| epi.cpresids |
Covariate pattern residuals from a logistic regression model |
| epi.descriptives |
Descriptive statistics |
| epi.dgamma |
Estimate the precision of a [structured] heterogeneity term |
| epi.directadj |
Directly adjusted incidence rate estimates |
| epi.dms |
Decimal degrees and degrees, minutes and seconds conversion |
| epi.dsl |
Mixed-effects meta-analysis of binary outcomes using the DerSimonian and Laird method |
| epi.edr |
Estimated dissemination ratio |
| epi.empbayes |
Empirical Bayes estimates of observed event counts |
| 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.incin |
Laryngeal and lung cancer cases in Lancashire 1974 - 1983 |
| epi.indirectadj |
Indirectly adjusted incidence risk estimates |
| epi.insthaz |
Event instantaneous hazard based on Kaplan-Meier survival estimates |
| epi.interaction |
Relative excess risk due to interaction in a case-control study |
| epi.iv |
Fixed-effects meta-analysis of binary outcomes using the inverse variance method |
| epi.kappa |
Kappa statistic |
| epi.ltd |
Lactation to date and standard lactation milk yields |
| epi.mh |
Fixed-effects meta-analysis of binary outcomes using the Mantel-Haenszel method |
| epi.nomogram |
Post-test probability of disease given sensitivity and specificity of a test |
| epi.occc |
Overall concordance correlation coefficient (OCCC) |
| epi.offset |
Create offset vector |
| epi.pooled |
Estimate herd test characteristics when pooled sampling is used |
| epi.popsize |
Estimate population size on the basis of capture-recapture sampling |
| epi.prcc |
Partial rank correlation coefficients |
| epi.prev |
Estimate true prevalence and the expected number of false positives |
| epi.psi |
Proportional similarity index |
| epi.realrisk |
An R version of the Winton Centre's RealRisk calculator |
| epi.RtoBUGS |
R to WinBUGS data conversion |
| epi.SClip |
Lip cancer in Scotland 1975 - 1980 |
| epi.smd |
Fixed-effects meta-analysis of continuous outcomes using the standardised mean difference method |
| epi.smr |
Confidence intervals and tests of significance of the standardised mortality [morbidity] ratio |
| epi.sscc |
Sample size, power or minimum detectable odds ratio for an unmatched or matched case-control study |
| epi.ssclus1estb |
Sample size to estimate a binary outcome using one-stage cluster sampling |
| epi.ssclus1estc |
Sample size to estimate a continuous outcome using one-stage cluster sampling |
| epi.ssclus2estb |
Number of clusters to be sampled to estimate a binary outcome using two-stage cluster sampling |
| epi.ssclus2estc |
Number of clusters to be sampled to estimate a continuous outcome using two-stage cluster sampling |
| epi.sscohortc |
Sample size, power or minimum detectable incidence risk ratio for a cohort study using individual count data |
| epi.sscohortt |
Sample size, power or minimum detectable incidence rate ratio for a cohort study using person or animal time data |
| epi.sscompb |
Sample size and power when comparing binary outcomes |
| epi.sscompc |
Sample size and power when comparing continuous outcomes |
| epi.sscomps |
Sample size and power when comparing time to event |
| epi.ssdetect |
Sample size to detect an event |
| epi.ssdxsesp |
Sample size to estimate the sensitivity or specificity of a diagnostic test |
| epi.ssdxtest |
Sample size to validate a diagnostic test in the absence of a gold standard |
| epi.ssequb |
Sample size for a parallel equivalence or equality trial, binary outcome |
| epi.ssequc |
Sample size for a parallel equivalence or equality trial, continuous outcome |
| epi.ssninfb |
Sample size for a non-inferiority trial, binary outcome |
| epi.ssninfc |
Sample size for a non-inferiority trial, continuous outcome |
| epi.sssimpleestb |
Sample size to estimate a binary outcome using simple random sampling |
| 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.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.sssupc |
Sample size for a parallel superiority trial, continuous outcome |
| epi.ssxsectn |
Sample size, power or minimum detectable prevalence ratio or odds ratio for a cross-sectional study |
| epi.tests |
Sensitivity, specificity and predictive value of a diagnostic test |
| rsu.adjrisk |
Adjusted risk values |
| rsu.dxtest |
Sensitivity and specificity of diagnostic tests interpreted in series or parallel |
| rsu.epinf |
Effective probability of disease |
| 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.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.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.rb |
Surveillance system sensitivity assuming risk-based sampling and varying unit sensitivity |
| rsu.sep.rb1rf |
Surveillance system sensitivity assuming risk-based sampling on one risk factor |
| rsu.sep.rb2rf |
Surveillance system sensitivity assuming risk-based sampling on two risk factors |
| rsu.sep.rb2st |
Surveillance system sensitivity assuming risk based, two-stage sampling |
| rsu.sep.rbvarse |
Surveillance system sensitivity assuming risk based sampling and varying unit sensitivity |
| rsu.sep.rs |
Surveillance system sensitivity assuming representative sampling |
| rsu.sep.rs2st |
Surveillance system sensitivity assuming representative two-stage sampling |
| rsu.sep.rsfreecalc |
Surveillance system sensitivity for detection of disease assuming representative sampling and imperfect test sensitivity and specificity. |
| rsu.sep.rsmult |
Surveillance system sensitivity by combining multiple surveillance components |
| rsu.sep.rspool |
Surveillance system sensitivity assuming representative sampling, imperfect pooled sensitivity and perfect pooled specificity |
| rsu.sep.rsvarse |
Surveillance system sensitivity assuming representative sampling and varying unit sensitivity |
| 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.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.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.sssep.rbmrg |
Sample size to achieve a desired surveillance system sensitivity assuming risk-based sampling and multiple sensitivity values within risk groups |
| 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.sssep.rs |
Sample size to achieve a desired surveillance system sensitivity assuming representative sampling |
| rsu.sssep.rs2st |
Sample size to achieve a desired surveillance system sensitivity assuming two-stage sampling |
| 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.rspool |
Sample size to achieve a desired surveillance system sensitivity using pooled samples assuming representative sampling |
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)