CopulaDTA (version 0.0.2)

cdtamodel: Specify the copula based bivariate beta-binomial distribution to fit to the diagnostic data.

Description

Specify the copula based bivariate beta-binomial distribution to fit to the diagnostic data.

Usage

cdtamodel(copula, modelargs = list())

Value

An object of cdtamodel class.

References

{Agresti A (2002). Categorical Data Analysis. John Wiley & Sons, Inc.}

{Clayton DG (1978). A model for Association in Bivariate Life Tables and its Application in Epidemiological Studies of Familial Tendency in Chronic Disease Incidence. Biometrika,65(1), 141-151.}

{Frank MJ (1979). On The Simultaneous Associativity of F(x, y) and x + y - F(x, y). Aequationes Mathematicae, pp. 194-226.}

{Farlie DGJ (1960). The Performance of Some Correlation Coefficients for a General Bivariate Distribution. Biometrika, 47, 307-323.}

{Gumbel EJ (1960). Bivariate Exponential Distributions. Journal of the American Statistical Association, 55, 698-707.}

{Meyer C (2013). The Bivariate Normal Copula. Communications in Statistics - Theory and Methods, 42(13), 2402-2422.}

{Morgenstern D (1956). Einfache Beispiele Zweidimensionaler Verteilungen. Mitteilungsblatt furMathematische Statistik, 8, 23 - 235.}

{Sklar A (1959). Fonctions de Repartition a n Dimensions et Leurs Marges. Publications de l'Institut de Statistique de L'Universite de Paris, 8, 229-231.}

Examples

data(telomerase)
model1 <-  cdtamodel(copula = 'fgm')

model2 <- cdtamodel(copula = 'fgm',
               modelargs=list(param=2,
                              prior.lse='normal',
                              par.lse1=0,
                              par.lse2=5,
                              prior.lsp='normal',
                              par.lsp1=0,
                              par.lsp2=5))

model3 <-  cdtamodel(copula = 'fgm',
               modelargs = list(formula.se = StudyID ~ Test - 1))