New Statistical Methods (new + statistical_methods)

Distribution by Scientific Domains

Selected Abstracts

Detecting hybridization between wild species and their domesticated relatives

Abstract The widespread occurrence of free-ranging domestic or feral carnivores (dogs, cats) or ungulates (pigs, goats), and massive releases of captive-reproduced game stocks (galliforms, waterfowl) is raising fear that introgressive hybridization with wild populations might disrupt local adaptations, leading to population decline and loss of biodiversity. Detecting introgression through hybridization is problematic if the parental populations cannot be sampled (unlike in classical stable hybrid zones), or if hybridization is sporadic. However, the use of hypervariable DNA markers (microsatellites) and new statistical methods (Bayesian models), have dramatically improved the assessment of cryptic population structure, admixture analyses and individual assignment testing. In this paper, I summarize results of projects aimed to identify occurrence and extent of introgressive hybridization in European populations of wolves (Canis lupus), wildcats (Felis silvestris), rock partridges and red-legged partridges (Alectoris graeca and Alectoris rufa), using genetic methods. Results indicate that introgressive hybridization can be locally pervasive, and that conservation plans should be implemented to preserve the integrity of the gene pools of wild populations. Population genetic methods can be fruitfully used to identify introgressed individuals and hybridizing populations, providing data which allow evaluating risks of outbreeding depression. The diffusion in the wild of invasive feral animals, and massive restocking with captive-reproduced game species, should be carefully controlled to avoid loss of genetic diversity and disruption of local adaptations. [source]

Theory & Methods: On the importance of being smooth

B. M. Brown
This paper makes the proposition that the only statistical analyses to achieve widespread popular use in statistical practice are those whose formulations are based on very smooth mathematical functions. The argument is made on an empirical basis, through examples. Given the truth of the proposition, the question ,why should it be so?' is intriguing, and any discussion has to be speculative. To aid that discussion, the paper starts with a list of statistical desiderata, with the view of seeing what properties are provided by underlying smoothness. This provides some rationale for the proposition. After that, the examples are considered. Methods that are widely used are listed, along with other methods which, despite impressive properties and possible early promise, have languished in the arena of practical application. Whatever the underlying causes may be, the proposition carries a worthwhile message for the formulation of new statistical methods, and for the adaptation of some of the old ones. [source]

Adjusted Exponentially Tilted Likelihood with Applications to Brain Morphology

BIOMETRICS, Issue 3 2009
Hongtu Zhu
Summary In this article, we develop a nonparametric method, called adjusted exponentially tilted (ET) likelihood, and apply it to the analysis of morphometric measures. The adjusted exponential tilting estimator is shown to have the same first-order asymptotic properties as that of the original ET likelihood. The adjusted ET likelihood ratio statistic is applied to test linear hypotheses of unknown parameters, such as the associations of brain measures (e.g., cortical and subcortical surfaces) with covariates of interest, such as age, gender, and gene. Simulation studies show that the adjusted exponential tilted likelihood ratio statistic performs as well as the,t -test when the imaging data are symmetrically distributed, while it is superior when the imaging data have skewed distribution. We demonstrate the application of our new statistical methods to the detection of statistically significant differences in the morphology of the hippocampus between two schizophrenia groups and healthy subjects. [source]

Does what happens in group care stay in group care?

The relationship between problem behaviour trajectories during care, post-placement functioning
ABSTRACT Residential programmes for youth may improve youth behaviour during placement, but it is not clear whether there is an association between a youth's behaviour pattern during placement and post-placement outcomes. Life course perspective has been used to understand longitudinal patterns and pathways, and new statistical methods have been developed to identify latent trajectory groups. This study used administrative data from a family-style group care programme to assess whether a youth's externalizing behaviour trajectory while in placement can significantly predict delinquency and adjustment outcomes at discharge and 6-month follow-up. Findings from multinomial logistic regression revealed a statistically significant relationship between a youth's behaviour trajectory class and outcomes. Behaviour pattern during care was a stronger predictor of outcome than cross-sectional measures such as other demographic factors, placement history or mental-health need indicators. [source]