BayesSenMC (version 0.1.5)

paramEst: Parameter estimates of the GLMM model

Description

Get parameter estimates of the GLMM model to plug into modeling functions in BayesSenMC for Bayesian inference of adjusted odds ratio.

Usage

paramEst(model, lower = 0.5, upper = 1)

Value

It returns a list of parameter estimates which can be input into the Bayesian model functions in BayesSenMC. (m.lg.se, s.lg.se) and (m.lg.sp, s.lg.sp) are the logit prior distributions for Se and Sp. se and sp are the corresponding mean values given the logit prior means. rho is the correlation estimate between Se and Sp. m.fisher is the Fisher's mean of the correlation assume a Fisher's distribution.

Arguments

model

a GLMM model built with the nlmeNDiff() function.

lower

an optional argument matching the lower bound assumption of Se and Sp of the input model. Default to 0.5 as in nlmeNDiff().

upper

an optional argument matching the upper bound assumption of Se and Sp. Default to 1 as in nlmeNDiff.

Examples

data(bd_meta)

mod <- nlmeNDiff(bd_meta, lower = 0) # see \code{nlmeNDiff()} for detailed example.
prior_list <- paramEst(mod)