p-values for Marginal Effects Models
This function attempts to return, or compute, p-values of marginal effects models from package mfx.
## S3 method for class 'poissonmfx'
p_value(model, component = c("all", "conditional", "marginal"), ...)
## S3 method for class 'betaor'
p_value(model, component = c("all", "conditional", "precision"), ...)
## S3 method for class 'betamfx'
p_value(
model,
component = c("all", "conditional", "precision", "marginal"),
...
)model |
A statistical model. |
component |
Should all parameters, parameters for the conditional model, precision-component or marginal effects be returned? |
... |
Currently not used. |
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.
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")
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.