experimentD: Running a computer experiment

Description Usage Arguments Details Value Examples

View source: R/methods-for-experiments.R

Description

Runs a computer experiment that evaluates the performance of different inference methods for the random effects meta regression model with respect to heterogeneity and regression coefficients.

Usage

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  experimentD(n, h, d, s, x, b, sgnf, piv_draws)

Arguments

n

number of draws.

h

heterogeneity.

d

heteroscedasticity.

s

vector study sizes.

x

design matrix.

b

regression coefficients.

sgnf

significance levels.

piv_draws

privotal draws.

Details

This also includes methods adjusting for uncertainty in the heteroscedasticity vector. In particular, the study sizes need to be known, here.

Value

Data frame of accumulated performance measures.

Examples

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h_test <- 0.03
x_test <- cbind(1,1:7)
b_test <- c(.5, .25)
sgnf_test <- c(0.025, 0.01)

set.seed(5133568) # for reproducibility
d_test <- rchisq(7, df=0.02)
s_test <- runif(7, min=200, max=2000)

# In an actual computer experiment, use 'piv_draws=1000' instead!!
experimentD(n=5, h=h_test, d=d_test, s=s_test, x=x_test, b=b_test,
  sgnf=sgnf_test, piv_draws=50)

metagen documentation built on May 29, 2017, 7:13 p.m.