medrc-methods: medrc methods

In daniel-gerhard/medrc: Mixed effect dose-response curves

Description

Methods for objects of class medrc

Usage

## S3 method for class 'medrc'
df.residual(object, ...)
## S3 method for class 'medrc'
predict(object, ..., newdata = NULL, level = NULL, type=c("conditional", "marginal"), nGQ=5)
## S3 method for class 'medrc'
residuals(object, ...)
## S3 method for class 'medrc'
vcov(object, ...)
## S3 method for class 'medrc'
summary(object, ...)
## S3 method for class 'medrc'
ranef(object, ...)
## S3 method for class 'medrc'
VarCorr(x, sigma = 1, ...)
## S3 method for class 'medrc'
AIC(object, ..., k = 2)
## S3 method for class 'medrc'
BIC(object, ...)
## S3 method for class 'medrc'
logLik(object, REML = FALSE, ...)
## S3 method for class 'medrc'
print(x, ..., digits = max(3, getOption("digits") - 3))

Arguments

object	An object of class medrc
x	An object of class medrc
newdata	an optional data frame to be used for obtaining the predictions. All variables used in the fixed and random effects models, as well as the grouping factors, must be present in the data frame. If missing, the fitted values are returned.
level	an optional integer vector giving the level(s) of grouping to be used in obtaining the predictions. Level values increase from outermost to innermost grouping, with level zero corresponding to the population predictions. Defaults to the highest or innermost level of grouping.
type	character, either "conditional" or "marginal" for predictions conditional on the random effects or marginal predictions (conditional on the estimated variance components).
nGQ	integer. Number of nodes for Gauss-Hermite quadrature, when type = "marginal".
k	numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.
REML	an optional logical value. If TRUE the restricted log-likelihood is returned, else, if FALSE, the log-likelihood is returned. Defaults to FALSE.
sigma	an optional numeric value used as a multiplier for the standard deviations. Default is 1.
digits	minimal number of significant digits
...	further arguments

Author(s)

Daniel Gerhard

daniel-gerhard/medrc documentation built on May 14, 2019, 3:38 p.m.