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CopulaDTA (version 0.0.1)

Copula Based Bivariate Beta-Binomial Model for Diagnostic Test Accuracy Studies

Description

Modelling of sensitivity and specificity on their natural scale using copula based bivariate beta-binomial distribution to yield marginal mean sensitivity and specificity. The intrinsic negative correlation between sensitivity and specificity is modelled using a copula function. A forest plot can be obtained for categorical covariates or for the model with intercept only.

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Version

Install

install.packages('CopulaDTA')

Monthly Downloads

18

Version

0.0.1

License

GPL-2

Maintainer

Victoria N Nyaga

Last Published

December 3rd, 2015

Functions in CopulaDTA (0.0.1)

ascus

ASCUS dataset
forestplot

Produce forest plots for categorical covariates.
waic

Compute log pointwise predictive density, effective number of parameters and WAIC.
printcopula

Print a summary of the fitted model.
tracecopula

Trace plot using ggplot2.
summarycopula

Print a summary of the fitted model.
prep.data

Prepare the data
fitcopula

Fit copula based bivariate beta-binomial distribution to diagnostic data.
ft

Compute transform omega to ktau.
telomerase

Telomerase dataset