Aligned rank tests in measurement error model

Rank tests and regression rank score tests in measurement error models

The rank and regression rank score tests of linear hypothesis in the linear regressionmodel are modified for measurement error models. The modified tests are still distribution free. Some tests of linear subhypotheses are invariant to the nuisance parameter, others are based on the aligned ranks using the R-estimators. The asymptotic relative efficiencies of tests with respect to tests in model...

Aligned rank tests for the linear model with heteroscedastic errors

We consider the problem of testing subhypotheses in a heteroscedastic linear regression model. The proposed test statistics are based on the ranks of scaled residuals obtained under the null hypothesis. Any estimator that is n”2-consistent under the null hypothesis can be used to form the residuals. The error variances are estimated through a parametric model. This extends the theory of aligned...

Aligned Rank Tests for Interactions in Split-Plot Designs: Distributional Assumptions and Stochastic Heterogeneity

Score Tests in Generalized Linear Measurement Error Models

Measurement error of visual field tests in glaucoma.

AIM Psychophysical strategies designed for clinical visual field testing produce rapid estimates of threshold with relatively few stimulus presentations and so represent a trade-off between test quality and efficiency. The aim of this study was to determine the measurement error of a staircase algorithm similar to full threshold with standard automated perimetry (SAP) and frequency doubling per...