psnorm {publipha} | R Documentation |
Publication Selection Meta-analysis Model
Description
Density, distribution, quantile, random variate generation, and expectation calculation for the distribution for the publication selection meta-analysis model
Usage
dpsnorm(x, theta, sigma, alpha = c(0, 0.025, 0.05, 1), eta, log = FALSE)
ppsnorm(
q,
theta,
sigma,
alpha = c(0, 0.025, 0.05, 1),
eta,
lower.tail = TRUE,
log.p = FALSE
)
rpsnorm(n, theta, sigma, alpha = c(0, 0.025, 0.05, 1), eta)
Arguments
x , q |
vector of quantiles. |
theta |
vector of means. |
sigma |
vector of study standard deviations. |
alpha |
vector of thresholds for publication bias. |
eta |
vector of publication probabilities, normalized to sum to 1. |
log , log.p |
logical; If |
lower.tail |
logical; If |
n |
number of observations. If |
Details
The effect size distribution for the publication selection model is not
normal, but has itself been selected for. These functions assume
one-sided selection on the effects. These functions do not assume the
existence of an underlying effect size distribution. For these, see
mpsnorm
.
Value
dpsnorm
gives the density, ppsnorm
gives the distribution
function, and rpsnorm
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" Forthcoming (2019)
Examples
rpsnorm(100, theta = 0, sigma = 0.1, eta = c(1, 0.5, 0.1))