Description Usage Arguments Details Value Author(s) References Examples
Returns the MR fit (and results for inference) for a linear model with cluster correlated data. The objective function is a sum of dispersion functions, one for each cluster/center/block.
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x |
n by p design matrix |
y |
n by 1 response vector |
center |
n by 1 vector denoting cluster membership |
beta0 |
initial fit (default is JR estimate) |
The multiple rankings (MR) dispersion function is defined as D(beta) = sum Dj(beta) where Dj(beta) is Jaeckel's (1972) dispersion function for the jth cluster/center/block. A separate set of rankings is computed for each center. D(beta) is the objective function to minimize for the MR estimate of beta.
Returns an object of class mrfit
betahat |
Estimated regression coefficients |
tauhat |
Estimate of the scale parameter tau |
disp |
Value of the MR dispersion function evaluated at betahat |
sebetahat |
estimated standard errors of the regression coefficients |
x |
Centered design matrix |
y |
response vector |
center |
vector denoting cluster membership |
John Kloke kloke@biostat.wisc.edu
Hettmansperger, T.P. and McKean J.W. (2011), Robust Nonparametric Statistical Methods, 2nd ed., New York: Chapman-Hall.
Rashid, M.M., McKean, J.W., Kloke, J.D. (2011). R Estimates and Associated Inferences for Mixed Models with Covariates in a Multi-Center Clinical Trial. Statistics in Biopharmaceutical Research.
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