Search results for "GLMM"

Influence diagnostics for generalized linear mixed models: a gradient-like statistic

2013

In the literature, many influence measures proposed for Generalized Linear Mixed Models (GLMMs) require the information matrix that can be difficult to calculate. In the present paper, a known influence measure is approximated to get a simpler form, for which the information matrix is no more necessary. The proposed measure is showed to have a form similar to the gradient statistic, recently introduced. Good performances have been obtained through simulation studies.

Reference growth charts for assessing growth performance of Posidonia oceanica (L.) Delile

2016

Posidonia oceanica is considered a key species due to its different roles as primary producer, substrate for many species, shoreline erosion protector and long-term carbon store (1).The importance of P. oceanicahas stimulated several studies aimed at quantifying its status. In particular growth performance of rhizomes has become among the most used descriptors for monitoring changes of P. oceanicameadows induced by human or naturalexogenous factors (2). However, ability to detect any change of growth in space or in time is often confounded by natural age-induced variations, which involves serious interpretation problems (3). A general approach adopted to overcome this problem is to build gr…

The Performance of the Gradient-Like Influence Measure in Generalized Linear Mixed Models

2015

A gradient-like statistic, recently introduced as an influence measure, has been proven to work well in large sample, thanks to its asymptotic properties. In this work, through small-scale simulation schemes, the performance of such a diagnostic measure is further investigated in terms of concordance with the main influence measures used for outlier identification. The simulation studies are performed by using generalized linear mixed models (GLMMs).

Modeling temporal and spatial colony‐site dynamics in a long‐lived seabird

2003

We studied the determinants of colony site dynamics in Audouin's gull, Larus audouinii, breeding in a small archipelago of the western Mediterranean. Data on island occupation were available for a series of 25 years, since first colonization of the archipelago in 1973. Group behavior was studied in relation to the components of dispersal: permanence or abandonment (extinction) on an island previously occupied and permanence or occupation (colonization) of another island. Generalized Linear Mixed Models (GLMMs) were used to identify the relative contribution of each explanatory variable to the probability of colony abandonment. Gulls showed a low probability (3%) of abandoning one of the isl…

Item Response Trees: a recommended method for analyzing categorical data in behavioral studies

2015

Behavioral data are notable for presenting challenges to their statistical analysis, often due to the difficulties in measuring behavior on a quantitative scale. Instead, a range of qualitative alternative responses is recorded. These can often be understood as the outcome of a sequence of binary decisions. For example, faced by a predator, an individual may decide to flee or stay. If it stays, it may decide to freeze or display a threat and if it displays a threat, it may choose from several alternative forms of display. Here we argue that instead of being analyzed using traditional nonparametric statistics or a series of separate analyses split by response categories, this kind of data ca…

Model interpretation from the additive elements of the PWRSS in GLMMs

2013

Generalized Linear Mixed models(GLMMs)have rapidly become a widely used tool for modelling clustered and longitudinal data with non-Normal responses. Although a large amount of work has been done in the literature on likelihood-based inference on GLMMs,little seems to have been done on the decomposition of the total variability associated to the different components of a mixed model.In this work we try to generalize the idea of likelihood additive elements Whittaker,1984), proposed in the context of GLMs,to the case of GLMMs by using the Penalized Weighted Residual Sum of Squares(PWRSS). The proposal is illustrated by means of areal application.

A gradient-based deletion diagnostic measure for generalized linear mixed models

2016

ABSTRACTA gradient-statistic-based diagnostic measure is developed in the context of the generalized linear mixed models. Its performance is assessed by some real examples and simulation studies, in terms of ability in detecting influential data structures and of concordance with the most used influence measures.

A model-based approach to Spotify data analysis: a Beta GLMM

2020

Digital music distribution is increasingly powered by automated mechanisms that continuously capture, sort and analyze large amounts of Web-based data. This paper deals with the management of songs audio features from a statistical point of view. In particular, it explores the data catching mechanisms enabled by Spotify Web API and suggests statistical tools for the analysis of these data. Special attention is devoted to songs popularity and a Beta model, including random effects, is proposed in order to give the first answer to questions like: which are the determinants of popularity? The identification of a model able to describe this relationship, the determination within the set of char…

Modeling confidential data via modified hurdle mixed models

2013

Prediction of the gene expression measure by means of a GLMM

2007

Microarrays permit to scientists the screening of thousands of genes simultaneously to determine, for example, whether those genes are active, hyperactive or silent in normal or cancerous tissues. A primary task in microarray analysis is to obtain a good measure of the gene expression that can be used for a so called higher level analysis. Different methods have been proposed for high density oligonucleotide arrays (see Cope et al. (2004) for a review). Aim of this paper is to obtain a new gene expression measure based on the background correction model proposed by Mineo et al. (2006). The proposed method is validated by means of a free available data-set called Spike-In133 experiment, wher…