A robust procedure for estimating the five parameters of a mixture of two normals is proposed. The procedure is based on a robustification of the steps of the EM algorithm. This results in the use of an iteratively reweighted median and MAD. Simulation results are presented that show the...

The linear step-up multiple testing procedure controls the false discovery rate at the desired level q for independent and positively dependent test statistics. When all null hypotheses are true, and the test statistics are independent and continuous, the bound is sharp. When some of the null...

The final prediction error (FPE) criterion has been used widely in model selection. The criterion for a linear regression model with k parameters can be written as RSS(k) + [lambda]k2, where RSS(k) is the residual sums of squares, 2 is an unbiased estimate of the error variance and [lambda] is a...

Increasingly, conjoint analysts are being asked to design and analyze studies involving large numbers of attributes and/or attribute levels. Various types of approaches, including attribute bridging, Adaptive Conjoint Analysis, and hybrid models have been proposed to deal with the problem. This...

Increasingly, researchers in marketing are recognizing the “lability” of attribute importance weights derived from measurement techniques, such as conjoint analysis. As has been suggested by Simonson and Tversky, attribute importance weights can be sensitive to competitive product context...