Description Usage Arguments Details Value Author(s) References See Also Examples

These are the user-interface functions to test the nullity of variance components, using linear score tests, projected quadratic score tests, or restricted likelihood ratio tests.

1 2 3 4 5 6 7 | ```
varComp.test(object, ...)
## S3 method for class 'formula'
varComp.test(object, data, random1, varcov1,
random2, varcov2, fit.control, test.control, ...)
## S3 method for class 'varComp'
varComp.test(object, object2, additional.varcov, null,
test = "LinScore", control = varCompTest.control(test), ...)
``` |

`object, object2` |
An R object. In |

`data` |
The same as in |

`random1, random2` |
The random effect formulas for the first and the second models, respectively. Specification is the same as in |

`varcov1, varcov2` |
The lists of variance-covariance matrices for the first and the second models, respectively. Specification is the same as in |

`fit.control` |
A list of arguments of class |

`test.control, control` |
A list of arguments of class |

`additional.varcov` |
An optional list of variance-covariance matrices. It is only used when |

`null` |
An optional integer vector, indicating the variance components in the null model. It is only used when |

`test` |
A character vector, specifying the tests to be performed. This does not need to be a vector of length 1. Available choices are given in |

`...` |
Place holder. |

The formula interface `varComp.test.formula`

is primarily used to test two variance component models with the same fixed-effect formula. The two models need to be nested.

In the `varComp.test.varComp`

interface, exactly *one* of `object2`

, `additional.varcov`

and `null`

needs to be given. If `object2`

is given, two-model comparison is performed against `object`

. If `additional.varcov`

is given, `object`

is treated as the null and `additional.varcov`

is treated as the additional variance components to be tested. If `null`

is given, `object`

is treated as the alternative and the components not in `null`

will be tested.

A list of class `varComp.test`

of the same length as `test`

. Each component is either an object of `htest`

or a list of `htest`

objects, depending upon whether multiple methods are requested under the same `test`

. See `varCompTest.control`

for more details on controlling the tests to be performed.

Long Qu

Qu L, Guennel T, Marshall SL. (2013) Linear Score Tests for Variance Components in Linear Mixed Models and Applications to Genetic Association Studies. *Biometrics*, Volume 69, Issue 4, pages 883–892.

Daniel B. Hall and Jens T. Praestgaard (2001) Order-restricted tests for homogeneity in generalised linear and nonlinear mixed models. *Biometrika*, 88, 739–751.

Mervyn J. Silvapulle and Paramsothy Silvapulle (1995) A score test against one-sided alternatives. *Journal of the American Statistical Association*, 90, 342–349.

Geert Verbeke and Geert Molenberghs (2003) The use of score tests for inference on variance components. *Biometrics*, 59, 254–262.

Ciprian M. Crainiceanu and David Ruppert (2003) Likelihood ratio tests in linear mixed models with one variance component. *Journal of the Royal Statistical Society: Series B (Statistical Methodology)*, 66, 165–185.

Greven S, Crainiceanu CM Kuchenhoff H and Peters A (2008) Restricted Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models. *Journal of Computational and Graphical Statistics*, 17, 870–891.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ```
### Oxide/Semiconductor data example
library(nlme)
data(Oxide)
lmef = lme(Thickness~Source, Oxide, ~1|Lot/Wafer)
vcf = varComp(Thickness~Source, Oxide, ~Lot/Wafer)
VarCorr(lmef)
coef(vcf, 'varComp') ## same values as above
varComp.test(vcf) ## test against linear model
varComp.test(vcf, null=1) ## test against model with only Lot random effect
### Genetics example
trt=gl(2, 15)
set.seed(2340)
dat=data.frame(trt=trt)
dat$SNP=matrix(sample(0:2, 120, replace=TRUE), 30)
dat$Y = as.numeric(trt)+rnorm(30) + dat$SNP%*%rnorm(4)
(vcf0 = varComp(Y~trt, dat, ~ibs(SNP)))
(vcf1 = varComp(Y~trt, dat, ~ibs(SNP):trt)) ## two variance components
varComp.test(vcf0)
varComp.test(vcf1)
varComp.test(vcf0, vcf1)
varComp.test(vcf1, null=1)
varComp.test(Y~trt, dat, random1=~ibs(SNP), random2=~trt:ibs(SNP))
``` |

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