compareCoefs
Print estimated coefficients and their standard errors in a table for several regression models.
This function extracts estimates of regression parameters and their standard errors from one or more models and prints them in a table.
- Keywords
Usage
compareCoefs(..., se = TRUE, zvals = FALSE, pvals = FALSE, vcov.,
print = TRUE, digits = 3)
Arguments
- …
One or more regression-model objects. These may be of class
lm
,glm
,nlm
, or any other regression method for which the functionscoef
andvcov
return appropriate values, or if the object inherits from themer
class created by thelme4
package orlme
in thenlme
package.- se
If
TRUE
, the default, show standard errors as well as estimates.- zvals
If
TRUE
(the default isFALSE
), print Wald statistics, the ratio of each coefficient to its standard error.- pvals
If codeTRUE (the default is
FALSE
), print two-sided p-values from the standard normal distribution corresponding to the Wald statistics.- vcov.
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 usingprintCoefmat
. IfFALSE
, the results are returned as a matrix- digits
Passed to the
printCoefmat
function for printing the result.
Value
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.
References
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Examples
# 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))
# }