This function attempts to return, or compute, p-values of marginal effects models from package mfx.
# S3 method for poissonmfx
p_value(model, component = c("all", "conditional", "marginal"), ...)# S3 method for betaor
p_value(model, component = c("all", "conditional", "precision"), ...)
# S3 method for betamfx
p_value(
model,
component = c("all", "conditional", "precision", "marginal"),
...
)
A data frame with at least two columns: the parameter names and the p-values. Depending on the model, may also include columns for model components etc.
A statistical model.
Should all parameters, parameters for the conditional model,
precision-component or marginal effects be returned? component
may be one
of "conditional"
, "precision"
, "marginal"
or "all"
(default).
Currently not used.
if (require("mfx", quietly = TRUE)) {
set.seed(12345)
n <- 1000
x <- rnorm(n)
y <- rnegbin(n, mu = exp(1 + 0.5 * x), theta = 0.5)
d <- data.frame(y, x)
model <- poissonmfx(y ~ x, data = d)
p_value(model)
p_value(model, component = "marginal")
}
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