Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles : a simulation study

Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

Acoustic Variability in the Production of English Vowels by Native and Non-Native Speakers

The features of non-native speech which distinguish it from native speech are often difficult to pin down. It is possible to be a native speaker of any of a vast number of varieties of English. These varieties each have their phonetic characteristics which allow them to be identified by speakers of the varieties in question and by others. The phonetic differences between the accents represented by these varieties are very great. It is impossible to indicate any particular configuration of vowels in the acoustic vowel space or set of consonant articulations which all native-speaker varieties of English have in common and which non-native speakers do not share. This study considers the vowel quality in a single word by native and non-native speakers.