logLik.pvlrt: Overall Log-likelihood for a pvlrt object

In pvLRT: Likelihood Ratio Test-Based Approaches to Pharmacovigilance

Overall Log-likelihood for a pvlrt object

Description

Overall Log-likelihood for a pvlrt object

Usage

## S3 method for class 'pvlrt'
logLik(object, type = "full-zip", ...)

Arguments

object	a pvlrt object, which is the output of the function pvlrt or one of its wrappers such as lrt_zi_poisson, lrt_poisson and lrt_vanilla_poisson.
type	Type of model and hypothesis combination. Available choices are "full-poisson", "null-poisson", "full-zip" (default), and "null-zip". See details.
...	other input parameters. Currently unused.

Details

The function extracts the overall log-likelihood and degrees of freedom (the number of estimated parameters) from a pvlrt object. There are four possible choices of distribution and hypothesis combinations, supplied through the argument type, with the default being type = "full-zip". In a "full" model the signal parameters lambdas are estimated for all cells in the contingency table from the data (subject to the condition lambda >= 1), whereas under a "null" model each lambda is fixed at 1 for each cell. In a "zip" model (type = "full-zip" and type = "null-zip") the log-likelihood under a zero-inflated Poisson model with estimated or supplied zero inflation parameters ( through zi_prob in pvlrt) is returned. The degrees of freedom reflects whether the zero-inflation parameters are estimated. Note that if an ordinary Poisson LRT is run either by setting zi_prob = 0 in pvlrt or equivalently through lrt_poisson then "full-zip" and "null-zip" refer to zero-inflated poisson models with presepecified zero-inflation probabilities equal to 0. Thus, in such cases the results with type = "full-zip" and type = "null-zip" are identical to type = "full-poisson" and type = "null-poisson" respectively. See examples.

Value

An object of class logLik. See Details.

Note

The overall log likelihood must be computed during the original pvlrt run. This is ensured by setting return_overall_loglik = TRUE, and parametrization = "lambda" (or parametrization = "rrr") while running pvlrt().

See Also

pvlrt; AIC

Examples

# 500 bootstrap iterations (nsim) in each example below
# are for quick demonstration only --
# we recommended setting nsim to 10000 (default) or bigger

set.seed(100)
# estimates zero inflation probabilities
test1 <- pvlrt(statin46, nsim = 500)
logLik(test1)
AIC(test1)
BIC(test1)

# compare with and without zero inflation
BIC(logLik(test1, type = "full-zip"))
BIC(logLik(test1, type = "full-poisson"))

# ordinary poisson model
## equivalent to pvlrt(statin46, zi_prob = 0, nsim = 500)
test2 <- lrt_poisson(statin46, nsim = 500)

all.equal(logLik(test2, "full-zip"), logLik(test2, "full-poisson"))

pvLRT documentation built on March 7, 2023, 7:17 p.m.