snorm: Selected Normal Effect Size Distribution

In publipha: Bayesian Meta-Analysis with Publications Bias and P-Hacking

Selected Normal Effect Size Distribution

Description

Density, random variate generation, and expectation calculation for the effect size distribution of the one-sided normal publication bias model.

Usage

dsnorm(x, theta0, tau, sigma, alpha = c(0, 0.025, 0.05, 1), eta, log = FALSE)

rsnorm(n, theta0, tau, sigma, alpha = c(0, 0.025, 0.05, 1), eta)

esnorm(theta0, tau, sigma, alpha, eta)

Arguments

x	vector of quantiles.
theta0	vector of means.
tau	vector of heterogeneity parameters.
sigma	vector of study standard deviations.
alpha	vector of thresholds for publication bias.
eta	vector of publication probabilities, normalized to sum to 1.
log	logical; If TRUE, probabilities are given as log(p).
n	number of observations. If length(n) > 1, the length is taken to be the number required.

Details

The effect size distribution for the publication selection model is not normal, but has itself been selected for. These functions assume a normal underlying effect size distribution and one-sided selection on the effects.

Value

dsnorm gives the density, psnorm gives the distribution function, and rsnorm generates random deviates.

References

Hedges, Larry V. "Modeling publication selection effects in meta-analysis." Statistical Science (1992): 246-255.

Moss, Jonas and De Bin, Riccardo. "Modelling publication bias and p-hacking" (2019) arXiv:1911.12445

Examples

rsnorm(100, theta0 = 0, tau = 0.1, sigma = 0.1, eta = c(1, 0.5, 0.1))

publipha documentation built on April 4, 2023, 5:19 p.m.