An asrtests.object that is a list consisting of
the components asreml.obj, wald.tab and test.summary.
A call to as.asrtests with test.summary = NULL re-initializes the
test.summary
data.frame.
If there is no wald.tab, wald.asreml is called. In all cases,
recalcWaldTab is called and any changes made as specified by the
recalcWaldTab arguments supplied via ....
The label argument can be used to include an entry in test.summary
for the starting model. If a label is included, (i) the information criteria
calculated using the asreml.obj will be added to the test.summary, if
IClikelihood is not set to none and (ii) the number of variance
parameters is included in the denDF column, if IClikelihood is set to none.
as.asrtests(asreml.obj, wald.tab = NULL, test.summary = NULL,
denDF = "numeric", label = NULL,
IClikelihood = "none", bound.exclusions = c("F","B","S","C"), ...)An object of S3-class asrtests that also inherits S3-class list.
an asreml object for a fitted model.
A data.frame containing a pseudo-anova table for
the fixed terms produced by wald.asreml; it should have 4 or 6 columns.
Sometimes wald.asreml returns a data.frame and at other
times a list. For example, it may return a list when
denDF is used. In this case, the Wald component of the
list is to be extracted and stored. It is noted that,
as of asreml version 4, wald.asreml has a kenadj argument.
A data.frame with columns term,
DF, denDF, p and action containing the
results of previous hypothesis tests.
Specifies the method to use in computing approximate denominator
degrees of freedom when wald.asreml is called. Can be none
to suppress the computations, numeric for numerical methods,
algebraic for algebraic methods or default, the default,
to automatically choose numeric or algebraic computations depending
on problem size. The denominator degrees of freedom are calculated
according to Kenward and Roger (1997) for fixed terms in the dense
part of the model.
A character to use as an entry in the terms column in
test.summary to indicate as far as is possible the nature of the
model that has been fitted. The action column in test.summary
will be Starting model.
A character that controls both the occurrence and the type
of likelihood for information criterion in the test.summary
of the new asrtests.object. If none, none are
included. Otherwise, if REML, then the AIC and BIC based
on the Restricted Maximum Likelihood are included; if full,
then the AIC and BIC based on the full likelihood, evaluated
using REML estimates, are included.
(See also infoCriteria.asreml.)
A character specifying the bound (constraint) codes that
will result in a variance parameter being excluded from the count of
estimated variance parameters in calculating information criteria.
If set to NULL then none will be excluded.
further arguments passed to wald.asreml and
recalcWaldTab.
Chris Brien
Kenward, M. G., & Roger, J. H. (1997). Small sample inference for fixed effects from restricted maximum likelihood. Biometrics, 53, 983-997.
asremlPlus-package, is.alldiffs, as.alldiffs,
recalcWaldTab,
testranfix.asrtests, chooseModel.asrtests,
rmboundary.asrtests,
reparamSigDevn.asrtests
if (FALSE) {
data(Wheat.dat)
# Fit initial model
current.asr <- asreml(yield ~ Rep + WithinColPairs + Variety,
random = ~ Row + Column + units,
residual = ~ ar1(Row):ar1(Column),
data=Wheat.dat)
# Load current fit into an asrtests object
current.asrt <- as.asrtests(current.asr, NULL, NULL)
# Check for and remove any boundary terms
current.asrt <- rmboundary(current.asrt)
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