A multivariate one-way classification model with random effects

Identification of outliers in a one-way random effects model

We distinguish between three types of outliers in a one way ran dom e ects model These are formally described in terms of their position relative to the main part of the observations We propose simple rules for identifying such outliers and give an example which involves median based statistics

Assessing Occupational Exposure Via the One-Way Random Effects Model With Balanced Data

A one-way randomeffectsmodel is consideredfor the log-transformedshift-longpersonal exposure measurements, where the random effect in the model represents an effect due to the worker. Following a previousapproach,we address a hypothesis-testingproblem involving the proportionof workers for whom the mean exposure exceeds the occupational exposure limit. A conŽ dence interval is constructed for t...

Assessing occupational exposure via the one-way random effects model with unbalanced data

This article considers a one-way random effects model for assessing the proportion of workers whose mean exposures exceed the occupational exposure limit (OEL) based on exposure measurements from a random sample of workers. Hypothesis testing and interval estimation for the relevant parameter of interest are proposed when the exposure data are unbalanced. The methods are based on the generalize...

Trapdoor one-way permutations and multivariate polynominals

Bias-corrected estimator for intraclass correlation coefficient in the balanced one-way random effects model

BACKGROUND Intraclass correlation coefficients (ICCs) are used in a wide range of applications. However, most commonly used estimators for the ICC are known to be subject to bias. METHODS Using second order Taylor series expansion, we propose a new bias-corrected estimator for one type of intraclass correlation coefficient, for the ICC that arises in the context of the balanced one-way random...