Hsu and Berger (J. Amer. Statist. Assoc. 50 (1999) 468) proposed a stepwise confidence interval procedure for identifying the minimum effective dose in dose-response studies under homoscedasticity. In practice, homogeneity of variance is often in doubt. In this paper, we extend Hsu and Berger's...

Semiparametric methods for longitudinal data with dependence within subjects have recently received considerable attention. Existing approaches that focus on modeling the mean structure require a correct specification of the covariance structure as misspecified covariance structures may lead to...

Generalized iterative scaling (GIS) has become a popular method for getting the maximum likelihood estimates for log-linear models. It is basically a sequence of successive I-projections onto sets of probability vectors with some given linear combinations of probability vectors. However, when a...

Regression analysis of the odds ratios for sparse data has received a lot of attention. However, existing works are restricted to the parametric case, and a parametric model may be a misspecification, which may lead to biased and inefficient estimators. Little attention is received for...

This paper identifies and estimates the relative average treatment effect in the presence of misclassification. We propose consistent estimators based on nonparametric methods. The simulation results reported illustrate the performance of the proposed estimators.

type="main" xml:id="sjos12057-abs-0001" <title type="main">ABSTRACT</title>Motivated by an entropy inequality, we propose for the first time a penalized profile likelihood method for simultaneously selecting significant variables and estimating unknown coefficients in multiple linear regression models in this article. The...