| p_value {sjstats} | R Documentation |
This function returns the p-values for fitted model objects.
p_value(fit, p.kr = FALSE)
fit |
A fitted model object of class |
p.kr |
Logical, if |
For linear mixed models (lmerMod-objects), the computation of
p-values (if p.kr = TRUE) is based on conditional F-tests
with Kenward-Roger approximation for the df, using the
pbkrtest-package. If pbkrtest is not available or
p.kr = FALSE, or if x is a glmerMod-object,
computation of p-values is based on normal-distribution assumption,
treating the t-statistics as Wald z-statistics.
If p-values already have been computed (e.g. for merModLmerTest-objects
from the lmerTest-package), these will be returned.
A tibble with the model coefficients' names (term),
p-values (p.value) and standard errors (std.error).
data(efc)
# linear model fit
fit <- lm(neg_c_7 ~ e42dep + c172code, data = efc)
p_value(fit)
# Generalized Least Squares fit
library(nlme)
fit <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary,
correlation = corAR1(form = ~ 1 | Mare))
p_value(fit)
# lme4-fit
library(lme4)
fit <- lmer(Reaction ~ Days + (Days | Subject), data = sleepstudy)
p_value(fit, p.kr = TRUE)