Get Model Summaries for Use with "mtable"
getSummary.Rd
A generic function and methods to collect coefficients
and summary statistics from a model object. It is used in mtable
Usage
# S3 method for class 'lm'
getSummary(obj, alpha=.05,...)
# S3 method for class 'glm'
getSummary(obj, alpha=.05,...)
# S3 method for class 'merMod'
getSummary(obj, alpha=.05, ...)
# These are contributed by Christopher N. Lawrence
# S3 method for class 'clm'
getSummary(obj, alpha=.05,...)
# S3 method for class 'polr'
getSummary(obj, alpha=.05,...)
# S3 method for class 'simex'
getSummary(obj, alpha=.05,...)
# These are contributed by Jason W. Morgan
# S3 method for class 'aftreg'
getSummary(obj, alpha=.05,...)
# S3 method for class 'coxph'
getSummary(obj, alpha=.05,...)
# S3 method for class 'phreg'
getSummary(obj, alpha=.05,...)
# S3 method for class 'survreg'
getSummary(obj, alpha=.05,...)
# S3 method for class 'weibreg'
getSummary(obj, alpha=.05,...)
# These are contributed by Achim Zeileis
# S3 method for class 'ivreg'
getSummary(obj, alpha=.05,...)
# S3 method for class 'tobit'
getSummary(obj, alpha=.05,...)
# S3 method for class 'hurdle'
getSummary(obj, alpha=.05,...)
# S3 method for class 'zeroinfl'
getSummary(obj, alpha=.05,...)
# S3 method for class 'betareg'
getSummary(obj, alpha=.05,...)
# S3 method for class 'multinom'
getSummary(obj, alpha=.05,...)
# A variant that reports exponentiated coefficients.
# The default method calls 'getSummary()' internally and should
# be applicable to all classes for which 'getSummary()' methods exist.
getSummary_expcoef(obj, alpha=.05,...)
# Default S3 method
getSummary_expcoef(obj, alpha=.05,...)
Details
The generic function getSummary
is called by mtable
in order to obtain the coefficients and summaries of model objects.
In order to adapt mtable
to models of classes other
than lm
or glm
one needs to
define getSummary
methods for these classes and
to set a summary template via setSummaryTemplate
Value
Any method of getSummary
must return a list with the following
components:
- coef
an array with coefficient estimates; the lowest dimension must have the following names and meanings:
est
the coefficient estimates, se
the estimated standard errors, stat
t- or Wald-z statistics, p
significance levels of the statistics, lwr
lower confidence limits, upr
upper confidence limits. The higher dimensions of the array correspond to the individual coefficients and, in multi-equation models, to the model equations.
- sumstat
a vector containing the model summary statistics; the components may have arbitrary names.