2,089 research outputs found
Asymptotics and optimal bandwidth selection for highest density region estimation
We study kernel estimation of highest-density regions (HDR). Our main
contributions are two-fold. First, we derive a uniform-in-bandwidth asymptotic
approximation to a risk that is appropriate for HDR estimation. This
approximation is then used to derive a bandwidth selection rule for HDR
estimation possessing attractive asymptotic properties. We also present the
results of numerical studies that illustrate the benefits of our theory and
methodology.Comment: Published in at http://dx.doi.org/10.1214/09-AOS766 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
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Interventions for treating pain and disability in adults with complex regional pain syndrome - An overview of systematic reviews
This article is available open access through the publisher’s website at the link below. Copyright © 2013 The Cochrane Collaboration.Background - There is currently no strong consensus regarding the optimal management of complex regional pain syndrome although a multitude of interventions have been described and are commonly used.
Objectives - To summarise the evidence from Cochrane and non-Cochrane systematic reviews of the effectiveness of any therapeutic intervention used to reduce pain, disability or both in adults with complex regional pain syndrome (CRPS).
Methods - We identified Cochrane reviews and non-Cochrane reviews through a systematic search of the following databases: Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (DARE), Ovid MEDLINE, Ovid EMBASE, CINAHL, LILACS and PEDro. We included non-Cochrane systematic reviews where they contained evidence not covered by identified Cochrane reviews. The methodological quality of reviews was assessed using the AMSTAR tool. We extracted data for the primary outcomes pain, disability and adverse events, and the secondary outcomes of quality of life, emotional well being and participants' ratings of satisfaction or improvement. Only evidence arising from randomised controlled trials was considered. We used the GRADE system to assess the quality of evidence.
Main results - We included six Cochrane reviews and 13 non-Cochrane systematic reviews. Cochrane reviews demonstrated better methodological quality than non-Cochrane reviews. Trials were typically small and the quality variable.
There is moderate quality evidence that intravenous regional blockade with guanethidine is not effective in CRPS and that the procedure appears to be associated with the risk of significant adverse events.
There is low quality evidence that bisphosphonates, calcitonin or a daily course of intravenous ketamine may be effective for pain when compared with placebo; graded motor imagery may be effective for pain and function when compared with usual care; and that mirror therapy may be effective for pain in post-stroke CRPS compared with a 'covered mirror' control. This evidence should be interpreted with caution. There is low quality evidence that local anaesthetic sympathetic blockade is not effective. Low quality evidence suggests that physiotherapy or occupational therapy are associated with small positive effects that are unlikely to be clinically important at one year follow up when compared with a social work passive attention control.
For a wide range of other interventions, there is either no evidence or very low quality evidence available from which no conclusions should be drawn.
Authors' conclusions - There is a critical lack of high quality evidence for the effectiveness of most therapies for CRPS. Until further larger trials are undertaken, formulating an evidence-based approach to managing CRPS will remain difficult
General Design Bayesian Generalized Linear Mixed Models
Linear mixed models are able to handle an extraordinary range of
complications in regression-type analyses. Their most common use is to account
for within-subject correlation in longitudinal data analysis. They are also the
standard vehicle for smoothing spatial count data. However, when treated in
full generality, mixed models can also handle spline-type smoothing and closely
approximate kriging. This allows for nonparametric regression models (e.g.,
additive models and varying coefficient models) to be handled within the mixed
model framework. The key is to allow the random effects design matrix to have
general structure; hence our label general design. For continuous response
data, particularly when Gaussianity of the response is reasonably assumed,
computation is now quite mature and supported by the R, SAS and S-PLUS
packages. Such is not the case for binary and count responses, where
generalized linear mixed models (GLMMs) are required, but are hindered by the
presence of intractable multivariate integrals. Software known to us supports
special cases of the GLMM (e.g., PROC NLMIXED in SAS or glmmML in R) or relies
on the sometimes crude Laplace-type approximation of integrals (e.g., the SAS
macro glimmix or glmmPQL in R). This paper describes the fitting of general
design generalized linear mixed models. A Bayesian approach is taken and Markov
chain Monte Carlo (MCMC) is used for estimation and inference. In this
generalized setting, MCMC requires sampling from nonstandard distributions. In
this article, we demonstrate that the MCMC package WinBUGS facilitates sound
fitting of general design Bayesian generalized linear mixed models in practice.Comment: Published at http://dx.doi.org/10.1214/088342306000000015 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Prevalence, characteristics and management of headache experienced by people with schizophrenia and schizoaffective disorder: a cross sectional cohort study
Objective: Headache is the most common type of pain reported by people with schizophrenia. This study aimed to establish prevalence, characteristics and management of these headache.
Method: One-hundred participants with schizophrenia/schizoaffective disorder completed a reliable and valid headache questionnaire. Two clinicians independently classified each headache as migraine (MH), tension-type (TTH), cervicogenic (CGH) or other (OH).
Results: The twelve-month prevalence of headache (57%) was higher than the general population (46%) with no evidence of a relationship between psychiatric clinical characteristics and presence of headache. Prevalence of CGH (5%) and MH (18%) was comparable to the general population. TTH (16%) had a lower prevalence and 19% of participant’s experienced OH. No-one with MH was prescribed migraine specific medication, no-one with CGH and TTH received best-practice treatment
Conclusion: Headache is a common complaint in people with schizophrenia/schizoaffective disorder with most fitting recognised diagnostic criteria for which effective interventions are available. No-one in this sample was receiving best-practice care for their headache
Variational inference for count response semiparametric regression
© 2015 International Society for Bayesian Analysis. Fast variational approximate algorithms are developed for Bayesian semiparametric regression when the response variable is a count, i.e., a nonnegative integer. We treat both the Poisson and Negative Binomial families as models for the response variable. Our approach utilizes recently developed methodology known as non-conjugate variational message passing. For concreteness, we focus on generalized additive mixed models, although our variational approximation approach extends to a wide class of semiparametric regression models such as those containing interactions and elaborate random effect structure
Self reported aggravating activities do not demonstrate a consistent directional pattern in chronic non specific low back pain patients: An observational study
Question: Do the self-reported aggravating activities of chronic non-specific low back pain
patients demonstrate a consistent directional pattern? Design: Cross-sectional observational
study. Participants: 240 chronic non specific low back pain patients. Outcome measure: We
invited experienced clinicians to classify each of the three self-nominated aggravating
activities from the Patient Specific Functional Scale by the direction of lumbar spine
movement. Patients were described as demonstrating a directional pattern if all nominated
activities moved the spine into the same direction. Analyses were undertaken to determine if
the proportion of patients demonstrating a directional pattern was greater than would be
expected by chance. Results: In some patients, all tasks did move the spine into the same
direction, but this proportion did not differ from chance (p = 0.328). There were no clinical or
demographic differences between those who displayed a directional pattern and those who did
not (all p > 0.05). Conclusion: Using patient self-reported aggravating activities we were
unable to demonstrate the existence of a consistent pattern of adverse movement in patients
with chronic non-specific low back pain
Functional regression via variational bayes
We introduce variational Bayes methods for fast approximate inference in functional regression analysis. Both the standard cross-sectional and the increasingly common longitudinal settings are treated. The method- ology allows Bayesian functional regression analyses to be conducted with- out the computational overhead of Monte Carlo methods. Confidence in- tervals of the model parameters are obtained both using the approximate variational approach and nonparametric resampling of clusters. The latter approach is possible because our variational Bayes functional regression ap- proach is computationally efficient. A simulation study indicates that varia- tional Bayes is highly accurate in estimating the parameters of interest and in approximating the Markov chain Monte Carlo-sampled joint posterior distribution of the model parameters. The methods apply generally, but are motivated by a longitudinal neuroimaging study of multiple sclerosis patients. Code used in simulations is made available as a web-supplement
More SPASS with Isabelle: superposition with hard sorts and configurable simplification
Sledgehammer for Isabelle/HOL integrates automatic theorem provers to discharge interactive proof obligations. This paper considers a tighter integration of the superposition prover SPASS to increase Sledgehammer’s success rate. The main enhancements are native support for hard sorts (simple types) in SPASS, simplification that honors the orientation of Isabelle simp rules, and a pair of clause-selection strategies targeted at large lemma libraries. The usefulness of this integration is confirmed by an evaluation on a vast benchmark suite and by a
case study featuring a formalization of language-based security
Asymptotic normality and valid inference for Gaussian variational approximation
We derive the precise asymptotic distributional behavior of Gaussian variational approximate estimators of the parameters in a single-predictor Poisson mixed model. These results are the deepest yet obtained concerning the statistical properties of a variational approximation method. Moreover, they give rise to asymptotically valid statistical inference. A simulation study demonstrates that Gaussian variational approximate confidence intervals possess good to excellent coverage properties, and have a similar precision to their exact likelihood counterparts
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