This is a generic S3 function that gets point estimates of fixed effects of a statistical model, implemented on a wide range of models and that can be extended to new models.
fixcoef(model, ...)# S3 method for lmerMod
fixcoef(model, ...)
# S3 method for glmerMod
fixcoef(model, ...)
# S3 method for lmerModLmerTest
fixcoef(model, ...)
# S3 method for lme
fixcoef(model, ...)
# S3 method for multinom
fixcoef(model, ...)
# S3 method for mlm
fixcoef(model, ...)
# S3 method for default
fixcoef(model, ...)
a fitted statistical model
argument unused by p_value_contrast.default but that may be useful to some specializations.
Simple numeric vector with one item for each fixed effect of the model.
lmerMod: implementation for lme4::lmer
glmerMod: implementation for lme4::glmer
lmerModLmerTest: implementation for lmerTest::lmer
lme: implementation for nlme::lme
multinom: implementation for nnet::multinom
mlm: implementation for multiple responses linear models generated by stats::lm when the response is a matrix.
It transforms the matrix to a vector, consistent with stats::vcov.
default: default implementation, simply calls coef(model).
It must return only estimates of fixed-effects of a model. Random effects are ignored.
The names of the element of this vector must be consistent
with the rownames and colnames
of the variance-covariance matrix that vcov_fixcoef returns.
The vcov_fixcoef function, on the same model, must return a matrix
with the same number and names of rows and columns as the length of the vector returned by fixcoef.
The functions vcov_fixcoef and fixcoef would be pointless if the behavior of
vcov and coef were not inconsistent from package to package.
fixcoef and vcov_fixcoef, together with df_for_wald are used by p_value_contrast.default
Other Wald-related functions:
df_for_wald(),
p_value_contrast(),
vcov_fixcoef()
# NOT RUN {
data(mtcars)
fixcoef(lm(data=mtcars, hp ~ 1)) # get mean horse power of cars listed in mtcars
# }
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