chooseModel.asrtests {asremlPlus}  R Documentation 
asrtests.object
,
taking into account the hierarchy or marginality relations of the terms.Performs a series of hypothesis tests taking into account the
marginality of terms. In particular, a term will not be tested if it is
marginal to (or nested in) one that is significant. For example, if A:B is significant, then
neither A nor B will be tested. For a random term, the term is removed from
the model fit, any boundary terms are removed using rmboundary.asrtests
and a REML likelihood ratio test is performed using REMLRT.asreml
.
If it is not significant and drop.ran.ns
is TRUE, the term is permanently removed
from the model. Note that if boundary terms are removed, the reduced model may not
be nested in the full model in which case the test is not valid. For fixed terms,
the Wald tests are performed and the pvalue for the term obtained. If it is not
significant and drop.fix.ns
is TRUE, the term is permanently removed
from the model. A row that records the outcome of a test is added to
test.summary
for each term that is tested.
## S3 method for class 'asrtests' chooseModel(object, terms.marginality=NULL, alpha = 0.05, allow.unconverged = TRUE, checkboundaryonly = FALSE, drop.ran.ns=TRUE, positive.zero = FALSE, bound.test.parameters = "none", drop.fix.ns=FALSE, denDF = "numeric", dDF.na = "none", dDF.values = NULL, trace = FALSE, update = TRUE, set.terms = NULL, ignore.suffices = TRUE, bounds = "P", initial.values = NA, IClikelihood = "none", ...)
object 
an 
terms.marginality 
A square matrix of ones and zeros with row and column names
being the names of the terms.
The names of fixed terms must match those in the 
alpha 
The significance level for the test. 
allow.unconverged 
A 
checkboundaryonly 
If 
drop.ran.ns 
A logical indicating whether to drop nonsignificant random terms from the model. 
positive.zero 
Indicates whether the hypothesized values for the
variance components being tested are on the boundary
of the parameter space. For example, this is true
for positivelyconstrained variance components that,
under the reduced model, are zero. This argument does
not need to be set if 
bound.test.parameters 
Indicates whether for the variance components
being tested, at least some of the hypothesized values
are on the boundary of the parameter space.
The possibilities are 
drop.fix.ns 
A logical indicating whether to drop a fixed term from the model when it is nonsignificant 
denDF 
Specifies the method to use in computing approximate denominator
degrees of freedom when 
dDF.na 
The method to use to obtain substitute denominator degrees of freedom.
when the numeric or algebraic methods produce an 
dDF.values 
A 
trace 
If TRUE then partial iteration details are displayed when ASRemlR functions are invoked; if FALSE then no output is displayed. 
update 
If 
set.terms 
A character vector specifying the terms that are to have
bounds and/or initial values set prior to fitting.
The names must match those in the 
ignore.suffices 
A logical vector specifying whether the suffices of the

bounds 
A 
initial.values 
A character vector specifying the initial values for
the terms specified in 
IClikelihood 
A 
... 
further arguments passed to 
A list containing:
asrtests.obj
: an asrtests.object
containing the
components (i) asreml.obj
, (ii) wald.tab
, and
(iii) test.summary
.;
sig.tests
: a character vector
whose elements are the
the significant terms amongst those tested.
Chris Brien
Kenward, M. G., & Roger, J. H. (1997). Small sample inference for fixed effects from restricted maximum likelihood. Biometrics, 53, 983997.
chooseModel
, chooseModel.data.frame
,
as.asrtests
, testranfix.asrtests
,
testresidual.asrtests
, REMLRT.asreml
,
rmboundary.asrtests
, newfit.asreml
,
changeModelOnIC.asrtests
, changeTerms.asrtests
,
reparamSigDevn.asrtests
## Not run: data(WaterRunoff.dat) asreml.options(keep.order = TRUE) #required for asremlR4 only current.asr < asreml(log.Turbidity ~ Benches + (Sources * (Type + Species)) * Date, random = ~Benches:MainPlots:SubPlots:spl(xDay), data = WaterRunoff.dat, keep.order = TRUE) current.asrt < as.asrtests(current.asr, NULL, NULL) terms.treat < c("Sources", "Type", "Species", "Sources:Type", "Sources:Species") terms < sapply(terms.treat, FUN=function(term){paste("Date:",term,sep="")}, simplify=TRUE) terms < c("Date", terms) terms < unname(terms) marginality < matrix(c(1,0,0,0,0,0, 1,1,0,0,0,0, 1,0,1,0,0,0, 1,0,1,1,0,0, 1,1,1,0,1,0, 1,1,1,1,1,1), nrow=6) rownames(marginality) < terms colnames(marginality) < terms choose < chooseModel(current.asrt, marginality) current.asrt < choose$asrtests.obj sig.terms < choose$sig.terms ## End(Not run)