Propensity score matching provides an estimate of the effect of a 'treatment' variable on an outcome variable that is largely free of bias arising from an association between treatment status and observable variables. However, matching methods are not robust against 'hidden bias' arising from...

The polychoric correlation is an ML estimator for the correlation parameter between two latent variables. Each latent variable is only observed as an ordered categorical indicator. This estimator is based on an assumption on the joint distribution for the latent variables which in this case is...

In nonparametric curve estimation the decision about the type of smoothing parameter is critical for the practical performance. The nearest neighbor bandwidth as introduced by Gefeller and Dette 1992 for censored data in survival analysis is specified by one parameter, namely the number of...

For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly. A common strategy to deal with this problem within the context of design is to construct maximin...

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian...

In this paper a new method for monotone estimation of a regression function is proposed. The estimator is obtained by the combination of a density and a regression estimate and is appealing to users of conventional smoothing methods as kernel estimators, local polynomials, series estimators or...

Motivated in part by applications in model selection in statistical genetics and sequential monitoring of financial data, we study an empirical process framework for a class of stopping rules which rely on kernel-weighted averages of past data. We are interested in the asymptotic distribution...

The paper reports a robust parameter design experiment, where we have used Taguchi's product array and a combined array simultaneously. This was done as part of a research project dealing with experimental design to optimise the process of sheet metal spinning. We found that the classical...

In many applications one is interested to detect certain (known) patterns in the mean of a process with smallest delay. Using an asymptotic framework which allows to capture that feature, we study a class of appropriate sequential nonparametric kernel procedures under local nonparametric...

Die relative Kaufkraftparitätentheorie (KKPT) wird am Beispiel des DM-Peseten-Kurses auf ihre Stichhaltigkeit in der langen Frist überprüft. Methodisch wird dabei auf zwei Verfahren der Kointegrationsanalyse zurückgegriffen. Trotz einer Vielzahl von Ansätzen kann nur in zwei Fällen...