This function extracts estimates of regression parameters and their standard errors from one or more models and prints them in a table.
compareCoefs(..., se = TRUE, zvals = FALSE, pvals = FALSE, vcov.,
print = TRUE, digits = 3)One or more regression-model objects. These may be of class lm, glm,
nlm, or any other regression method for which the functions coef and
vcov return appropriate values, or if the object inherits from the mer
class created by the lme4 package or lme in the nlme
package.
If TRUE, the default, show standard errors as well as estimates.
If TRUE (the default is FALSE), print Wald statistics, the
ratio of each coefficient to its standard error.
If codeTRUE (the default is FALSE), print two-sided p-values
from the standard normal distribution corresponding to the Wald statistics.
an optional argument, specifying a function to be applied to all of the models, returning a coefficient covariance matrix
for each, or a list with one element for each model, with each element either containing a function to
be applied to the corresponding model or a coefficient covariance matrix for that model. If omitted, vcov is applied to
each model.
If TRUE, the defualt, the results are printed in a nice format
using printCoefmat. If
FALSE, the results are returned as a matrix
Passed to the printCoefmat function for printing the result.
This function is mainly used for its side-effect of printing the result. It also invisibly returns a matrix of estimates, standard errors, Wald statistics, and p-values.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
# NOT RUN {
mod1 <- lm(prestige ~ income + education, data=Duncan)
mod2 <- update(mod1, subset=-c(6,16))
mod3 <- update(mod1, . ~ . + type)
mod4 <- update(mod1, . ~ . + I(income + education)) # aliased coef.
compareCoefs(mod1)
compareCoefs(mod1, mod2, mod4)
compareCoefs(mod1, mod2, mod3, zvals=TRUE, pvals=TRUE)
compareCoefs(mod1, mod2, se=FALSE)
compareCoefs(mod1, mod1, vcov.=list(vcov, hccm))
# }