fwerapprox: The fwerapprox package
In oyvind-bakke/fwerapprox: FWER Approximations
Description
(1) Computes score test statistics for testing whether each of a large number of
coefficients (typically corresponding to genetic markers) in a GLM is zero in
presence of a smaller number of covariates (typically environmental covariates),
and provides estimates of correlations between the test
statistics, and (2) computes Glaz–Johnson-type intersection approximations of the
asymptotic multivariate normal distribution of the test statistics. See Halle et al.,
"Efficient and powerful familywise error control in genome-wide association studies
using generalised linear models".
Details
Use library(help = "fwerapprox") to get a list of functions and data sets.
Functions
scorestatcorrComputes score test statistics for testing whether each of a large number of
coefficients (typically corresponding to genetic markers) in a GLM with canonical
link is zero
in presence of a smaller number of covariates (typically environmental
covariates), and provides estimates of correlations
between the test statistics.
gamma2Computes a second-order Glaz–Johnson approximation to a multivariate
standard normal probability with a given correlation matrix. Gives a
familywise error rate level bound in multiple testing for a given local
(per-hypothesis) significance level.
gamma_kComputes an order k Glaz–Johnson approximation to a multivariate
standard normal probability with a given correlation matrix. Gives a familywise error rate level
bound in multiple testing for a given local (per-hypothesis) significance level.
Use ?scorestatcorr, ?gamma2, ?gamma_k for more information.
oyvind-bakke/fwerapprox documentation built on May 29, 2019, 7:35 a.m.
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Description
(1) Computes score test statistics for testing whether each of a large number of coefficients (typically corresponding to genetic markers) in a GLM is zero in presence of a smaller number of covariates (typically environmental covariates), and provides estimates of correlations between the test statistics, and (2) computes Glaz–Johnson-type intersection approximations of the asymptotic multivariate normal distribution of the test statistics. See Halle et al., "Efficient and powerful familywise error control in genome-wide association studies using generalised linear models".
Details
Use library(help = "fwerapprox") to get a list of functions and data sets.
Functions
scorestatcorrComputes score test statistics for testing whether each of a large number of coefficients (typically corresponding to genetic markers) in a GLM with canonical link is zero in presence of a smaller number of covariates (typically environmental covariates), and provides estimates of correlations between the test statistics.
gamma2Computes a second-order Glaz–Johnson approximation to a multivariate standard normal probability with a given correlation matrix. Gives a familywise error rate level bound in multiple testing for a given local (per-hypothesis) significance level.
gamma_kComputes an order k Glaz–Johnson approximation to a multivariate standard normal probability with a given correlation matrix. Gives a familywise error rate level bound in multiple testing for a given local (per-hypothesis) significance level.
Use ?scorestatcorr, ?gamma2, ?gamma_k for more information.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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