pleio.q.test: Single test of the number of traits associated with genotype
In pleio: Pleiotropy Test for Multiple Traits on a Genetic Marker

Description Usage Arguments Details Value Author(s) References Examples

View source: R/pleio.q.test.R

Perform single test of the number of traits associated with a genotype, by allowing a specified number of regression beta's to be unconstrained.

1	pleio.q.test(obj.fit, count.nonzero.beta = 0)

`obj.fit`	result of pleio.q.fit
`count.nonzero.beta`	Number of non-zero betas. A non-zero beta is allowed to be unconstrained, while all other beta's are constrained to be zero.

By specifying the number of non-zero beta's, the algorithm evaluates all possible ways of choosing unconstrained and constrained beta's, and for each configuration a statistic (tk) is computed. This tk statistic can be considered a measure of fit of a model. The minimum tk over all possible configurations provides a global test of whether one of the models fits well.

A list containing:

`stat`	global test statistict
`df`	degrees of freedom of the statistic
`pval`	p-value for the test
`index.nonzero.beta`	index of the non-zero beta(s) that provide(s) the minimum tk goodness of fit statistic - this configuration is assumed to have beta's for all other indices equal to zero.
`tests`	data.frame containing the tests performed. For m traits, and k = count.nonzero.beta, there are m-choose-k tests considered in the null hypothesis. The data.frame provides the indices of the unconstrained betas and the corresponding tk test statistic for the configuration.

Dan Schaid and Jason Sinnwell

Schaid DJ, Tong X, Larrabee B, Kennedy RB, Poland GA, Sinnwell JP. Statistical Methods for Testing Genetic Pleiotropy. Genetics. 2016 Oct;204(2):483-497.

data(pleio.qdemo)
fit <- pleio.q.fit(y, geno)
## usual multivariate test of whether all betas = 0
test0 <- pleio.q.test(fit, count.nonzero.beta = 0)
test0
## test whether allowing 2 betas to be non-zero fits data
test2 <- pleio.q.test(fit, count.nonzero.beta = 2)
test2