computeConfidenceInterval: Compute the point estimate and confidence interval given a...

In EvidenceSynthesis: Synthesizing Causal Evidence in a Distributed Research Network

Compute the point estimate and confidence interval given a likelihood function approximation

Description

Compute the point estimate and confidence interval given a likelihood function approximation

Usage

computeConfidenceInterval(approximation, alpha = 0.05)

Arguments

approximation	An approximation of the likelihood function as fitted using the approximateLikelihood() function.
alpha	The alpha (expected type I error).

Details

Compute the point estimate and confidence interval given a likelihood function approximation.

Value

A data frame containing the point estimate, and upper and lower bound of the confidence interval.

Examples

# Simulate some data for this example:
populations <- simulatePopulations()

cyclopsData <- Cyclops::createCyclopsData(Surv(time, y) ~ x + strata(stratumId),
  data = populations[[1]],
  modelType = "cox"
)
cyclopsFit <- Cyclops::fitCyclopsModel(cyclopsData)
approximation <- approximateLikelihood(cyclopsFit, "x")
computeConfidenceInterval(approximation)

EvidenceSynthesis documentation built on May 31, 2023, 9:05 p.m.