mpsnorm | R Documentation |
Density, distribution, and random variate generation for the marginalized distribution of the publication selection meta-analysis model
dmpsnorm(x, theta0, tau, sigma, alpha = c(0, 0.025, 0.05, 1), eta, log = FALSE)
pmpsnorm(
q,
theta0,
tau,
sigma,
alpha = c(0, 0.025, 0.05, 1),
eta,
lower.tail = TRUE,
log.p = FALSE
)
rmpsnorm(n, theta0, tau, sigma, alpha = c(0, 0.025, 0.05, 1), eta)
x, q |
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, log.p |
logical; If |
lower.tail |
logical; If |
n |
number of observations. If |
These functions assume a normal underlying effect size distribution and
one-sided selection on the effects. For the fixed effects publication
bias model see psnorm
.
dmpsnorm
gives the density, pmpsnorm
gives the distribution
function, and rmpsnorm
generates random deviates.
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)
rmpsnorm(100, theta0 = 0, tau = 0.1, sigma = 0.1, eta = c(1, 0.5, 0.1))
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