OBJECTIVES/HYPOTHESIS The need for class I and II studies on the efficacy of liberatory maneuvers in the treatment of lateral canal benign paroxysmal positional vertigo (LC-BPPV) motivated the present double-blind randomized trial on the short-term efficacy of the Gufoni liberatory maneuver (GLM). STUDY DESIGN Double-blind randomized controlled trial. METHODS Seventy-two patients with unila...

The current paper critically reviews the Risk-Need-Responsivity (RNR) and Good Lives Model (GLM) approaches to correctional treatment. Research, or the lack thereof, is discussed in terms of whether there is a need for a new model of offender rehabilitation. We argue that although there is a wealth of research in support of RNR approaches, there is presently very little available research demon...

We consider structured multi-armed bandit problems based on the Generalized Linear Model (GLM) framework of statistics. For these bandits, we propose a new algorithm, called GLM-UCB. We derive finite time, high probability bounds on the regret of the algorithm, extending previous analyses developed for the linear bandits to the non-linear case. The analysis highlights a key difficulty in genera...

BACKGROUND Some rheumatoid arthritis (RA) patients initially respond to treatment with infliximab (IFX), but subsequently their responsiveness decreases. OBJECTIVES Our objective was to evaluate the efficacy and safety of switching from IFX to subcutaneous golimumab (GLM-SC) in RA patients. METHODS Thirty-three patients who had been treated for a mean 4.4 years with IFX (3-6 mg/kg/8 weeks) ...

In this study, the generalized linear model (GLM) and four ensemble methods (partial least squares (PLS), boosting, bagging, Bayesian) were applied to predict forest fire hazard in Chalus Rood watershed Mazandaran Province, Iran. Data from 108 historical events collected through field surveys as basis of analysis. About 70% data used for training models, while remaining 30% was testing. A total...

Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in ris...

In this review, we first set out the general linear model (GLM) for the non technical reader, as a tool able to do both linear regression and ANOVA within the same flexible framework. We present a short history of its development in the fMRI community, and describe some interesting examples of its early use. We offer a few warnings, as the GLM relies on assumptions that may not hold in all situ...

We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLM), a new class of methods for nonparametric regression. Given a data set of input-response pairs, the DP-GLM produces a global model of the joint distribution through a mixture of local generalized linear models. DP-GLMs allow both continuous and categorical inputs, and can model the same class of responses that can be mo...

In this paper, we focus on predicting the visibility of packet losses in MPEG-2 compressed video streams. We develop a generalized linear model (GLM) to predict the probability that a packet loss will be visible to an average viewer. The GLM input consists of parameters that can be easily extracted from the video near the location of the loss, and outputs an estimate of the probability that tha...

The impact of using motion estimates as covariates of no interest was examined in general linear modeling (GLM) of both block design and rapid event-related functional magnetic resonance imaging (fMRI) data. The purpose of motion correction is to identify and eliminate artifacts caused by task-correlated motion while maximizing sensitivity to true activations. To optimize this process, a combin...