Likelihood ratio tests based on subglobal optimization: A power comparison in exponential mixture models

The paper compares several versions of the likelihood ratio test for exponential homogeneity against mixtures of two exponentials. They are based on different implementations of the likelihood maximization algorithm. We show that global maximization of the likelihood is not appropriate to obtain a good power of the LR test. A simple starting strategy for the EM algorithm, which under the null hypothesis often fails to find the global maximum, results in a rather powerful test. On the other hand, a multiple starting strategy that comes close to global maximization under both the null and the alternative hypotheses leads to inferior power.     

Using order statistics to assess the sampling variability of personnel selection utility estimates

Virtually all models for the utility of personnel selection are based on the average criterion score of the predictor selected applicants. This paper indicates how standard results from the theory on order statistics can be used to determine the expected value, the standard error and the sampling distribution of the average criterion score statistic when a finite number of employees is selected. Exact as well as approximate results are derived and it is shown how these results can be used to construct intervals that will contain, with a given probability 1 - f , the average criterion score associated with a particular implementation of the personnel selection. These interval estimates are particularly helpful to the selection practitioner because they can be used to state the confidence level with which the selection payoff will be above a specific value. In addition, for most realistic selection scenarios, it is found that the corresponding utility interval estimate is quite large. For situations in which multiple selections are performed over time, the utility intervals are, however, smaller.     

Changes in professional vision in the context of practice

In initial teacher education, it is a challenge to foster the development of teaching skills proximal to classroom action. In this study, the impact of a combined practical and theoretical university-based term on preservice teachers’ professional vision is investigated by a video-based approach to supervising their knowledge acquisition and assessing their learning outcomes. Participants were N = 109 preservice teachers attending a 5-month theory practice term guided through video-based courses about effective teaching and learning. We measured their changes in professional vision using the video-based tool Observer. Our results show that preservice teachers positively change their professional vision during the theory practice term, especially if they show low entry levels at the beginning. Their notes on the observed teaching lessons illustrate these changes.     

Statistical estimation of nonlinear regression functions

In order to obtain the first and second moments of a matrix quadratic form under normality assumptions its moment generating function will be derived and then differentiated.

Use is being made of matrix differential calculus as developed by the author