choose.model.asrtests {asreml3Plus}R Documentation

Determines the set of significant terms taking into account the hierarchy or marginality relations.

Description

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 reml.lrt.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 p-value 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 is added to test.summary for each term that is tested.

Usage

choose.model.asrtests(terms.marginality=NULL, asrtests.obj, 
                      alpha = 0.05, allow.unconverged = TRUE, drop.ran.ns=TRUE, 
                      positive.zero = FALSE, bound.test.parameters = "none", 
                      drop.fix.ns=FALSE, denDF = "default",  dDF.na = "none", 
                      dDF.values = NULL, trace = FALSE, update = TRUE, 
                      set.terms = NULL, ignore.suffices = TRUE, 
                      constraints = "P", initial.values = NA, ...)

Arguments

terms.marginality

a square matrix of ones and zeros with row and column names being the names of the terms. The diagonal elements should be one, indicating that a term is marginal to itself. Elements should be one if the row term is marginal to the column term. All other elements should be zero.

asrtests.obj

an asrtests object for a fitted model that is a list containing an asreml object, a wald.tab data.frame with 4 columns, and a data.frame with 5 columns that records any previous changes and tests in the fitted model.

alpha

the significance level for the test.

allow.unconverged

A logical indicating whether to accept a new model even when it does not converge. If FALSE and a fit when a term is removed does not converge, the term will not be removed.

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 positively-constrained variance components that, under the reduced model, are zero. This argument does not need to be set if bound.test.parameters is set.

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 default is "none". Other possibilities are "onlybound" and "one-and-one". The latter signifies that there are two parameters being tested, one of which is bound and the other is not. For example, the latter is true for testing a covariance and a positively-constrained variance component that, under the reduced model, are zero.

drop.fix.ns

a logical indicating whether to drop a fixed term from the model when it is nonsignificant

denDF

Specifies the enthod 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 autommatically 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.

dDF.na

the method to use to obtain substitute denominator degrees of freedom. when the numeric or algebraic methods produce an NA. If dDF.na = "none", no subtitute denominator degrees of freedom are employed; if dDF.na = "residual", the residual degrees of freedom from asreml.obj$nedf are used; if dDF.na = "maximum", the maximum of those denDF that are available, excluding that for the Intercept, is used; if all denDF are NA, asreml.obj$nedf is used. If dDF.na = "supplied", a vector of values for the denominator degrees of freedom is to be supplied in dDF.values. Any other setting is ignored and a warning message produced. Generally, substituting these degrees of freedom is anticonservative in that it is likely that the degrees of freedom used will be too large.

dDF.values

A vector of values to be used when dDF.na = "supplied". Its values will be used when denDF in a test for a fixed effect is NA. This vector must be the same length as the number of fixed terms, including (Intercept) whose value could be NA.

trace

if TRUE then partial iteration details are displayed when ASReml-R functions are invoked; if FALSE then no output is displayed.

update

if TRUE then update.asreml is called in testing models. In doing this the arguments R.param and G.param are set to those in the asreml object stored in asrtests.obj so that the values from the previous model are used as starting values. If FALSE then a call is made to asreml in which the only changes to the asreml.obj stored in the supplied asrtests.obj are (i) to the terms in the fixed and random models corresponding to terms in terms.marginality and (ii) those modifications specified via ....

set.terms

a character vector specifying the terms that are to have constraints and/or initial values set prior to fitting.

ignore.suffices

a logical vector specifying whether the suffices of the asreml-assigned names of the variance terms (i.e. the information to the right of an "!", other than "R!") is to be ignored in matching elements of terms. If TRUE for an element of terms, the suffices are stripped from the asreml-assigned names. If FALSE for an element of terms, the element must exactly match an asreml-assigned name for a variance term. This vector must be of length one or the same length as terms. If it is of length one then the same action is applied to the asreml-assigned suffices for all the terms in terms.

constraints

a character vector specifying the constraints to be applied to the terms specified in terms. This vector must be of length one or the same length as terms. If it is of length one then the same constraint is applied to all the terms in terms. If any of the constraints are equal to NA then they are left unchanged for those terms.

initial.values

a character vector specifying the initial values for the terms specified in terms. This vector must be of length one or the same length as terms. If it is of length one then the same initial value is applied to all the terms in terms. If any of the initial.values are equal to NA then they are left unchanged for those terms.

...

further arguments passed to asreml and wald.asreml via testranfix.asrtests.

Value

A list containing:

  1. asrtests.obj: an asrtests object, containing the asreml object correspondiing to the final fit, a wald.tab data.frame, and a test.summary data.frame that contains a record of the testing of the terms (see asrtests for more details);

  2. sig.tests: a character vector whose elements are the the significant terms amongst those tested.

See Also

asrtests, testranfix.asrtests, testrcov.asrtests, reml.lrt.asreml, rmboundary.asrtests,
newfit.asreml, addrm.terms.asrtests, sig.devn.reparam.asrtests

Examples

## Not run: 
data(WaterRunoff.dat)
current.asr <- asreml(log.Turbidity ~ Benches + (Sources * (Type + Species)) * Date, 
                      random = ~Benches:MainPlots:SubPlots:spl(xDay), 
                      data = WaterRunoff.dat, keep.order = TRUE)
current.asrt <- 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 <- choose.model.asrtests(marginality, current.asrt) 
         current.asrt <- choose$asrtests.obj
         sig.terms <- choose$sig.terms

## End(Not run)

[Package asreml3Plus version 2.0-14 Index]