mc_beta_effect_measures: Monte Carlo Sim of Effect Measures using the Beta...

In FrankLef/fciR: Data and functions used with Fundamentals of Causal Inference by Babette Brumback

Monte Carlo Sim of Effect Measures using the Beta distribution

Description

Monte Carlo Sim of Effect Measures using the Beta distribution.

Usage

mc_beta_effect_measures(
  shape1_prms = 1,
  shape2_prms = 1,
  nrep = 5000,
  constrained = FALSE
)

Arguments

shape1_prms	Vector of shape 2 parameter for the rbeta function
shape2_prms	Vector of shape 2 parameter for the rbeta function
nrep	Nb of repetitions
constrained	Logical. If FALSE the data is not constrained. Otherwise it is constrained. That is when RR0 and RR1 are on different sides of 1, the data point is excluded.

Details

Perform a Monte Carlo simulation of effect measures using a grid of shape1 and shape2 parameters. See the rbeta() function for more details

Value

List of matrices. One per event of effect measure.

Source

Section 4.2.1

Examples

## Not run: 
mc_beta_effect_measures(shape1 = c(0.5, 1, 3, 5, 7),
 shape2 = c(0.5, 1, 3, 5, 7), nrep = 5000)

## End(Not run)

FrankLef/fciR documentation built on Nov. 12, 2023, 6:09 a.m.