lrt_poisson function

Likelihood Ratio Test under the (vanilla, non-zero-inflated) Poisson model

Likelihood Ratio Test under the (vanilla, non-zero-inflated) Poisson model

lrt_poisson(contin_table, nsim = 10000, parametrization = "rrr", ...) lrt_vanilla_poisson(contin_table, nsim = 10000, parametrization = "rrr", ...)

Arguments

  • contin_table: IxJ contingency table showing pairwise counts of adverse events for I AE (along the rows) and J Drugs (along the columns)
  • nsim: Number of simulated null contingency table to use for computing the p-value of the test
  • parametrization: Type of parametrization to use in the LR test. Available choices are "rrr", "lambda", "rr", and "p-q". The relative reporting ratio (default) parametrization of the test is used when when parametrization %in% c("rrr", "lambda"), and the reporting rate parametrization is used otherwise. NOTE: zero inflation can be handled only for the relative reporting ratio parametrization.
  • ...: additional arguments. Currently unused.

Returns

Returns a pvlrt object. See pvlrt for more details.

Note

lrt_poisson() and lrt_vanilla_poisson()

are both wrappers for pvlrt() with omega_vec = rep(0, ncol(contin_table))

Examples

data("statin46") # 500 bootstrap iterations (nsim) in the example below # are for quick demonstration only -- # we recommended setting nsim to 10000 (default) or bigger # no grouping -- each drug forms its own class test1 <- lrt_poisson(lovastatin, nsim = 500)

See Also

pvlrt

  • Maintainer: Saptarshi Chakraborty
  • License: GPL-3
  • Last published: 2023-03-06

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