Primary sarcopenia is a common geriatric syndrome characterised by age-related decline in muscle strength, mass, and quality, which associated with reduced quality of life significant social burden. We report results from an analysis arm ageing on 478,438 UK Biobank participants aged 40-82 yr. A clear sexual dimorphism was identified: while the sex difference strength modest, mass loss considerably more pronounced males, both absolute percentage terms. also introduce novel measure showed...

Journal Article On asymptotic validity of naive inference with an approximate likelihood Get access H. E. Ogden Search for other works by this author on: Oxford Academic Google Scholar Biometrika, Volume 104, Issue 1, March 2017, Pages 153–164, https://doi.org/10.1093/biomet/asx002 Published: 18 February 2017 history Received: 29 January 2016

The likelihood for the parameters of a generalized linear mixed model involves an integral which may be very high dimension. Because this intractability, many approximations to have been proposed, but all can fail when is sparse, in that there only small amount information available on each random effect. sequential reduction method described paper exploits dependence structure posterior distribution effects reduce substantially cost finding accurate approximation models with sparse structure.

Abstract The paper discusses very general extensions to existing inflation models for discrete random variables, allowing an arbitrary set of points in the sample space be either inflated or deflated relative a baseline distribution. term flation is introduced cover deflation counts. Examples include one-inflated count where distribution zero-truncated and data with few unusual large values. main result that inference about can based solely on truncated which arises when entire truncated. A...

Abstract We present a topological method for the detection and quantification of bone microstructure from non-linear microscopy images. Specifically, we analyse second harmonic generation (SHG) two photon excited autofluorescence (TPaF) images tissue which capture distribution matrix (fibrillar collagen) structure autofluorescent molecules, respectively. Using persistent homology statistics with signed Euclidean distance transform filtration on binary patches images, are able to quantify...

Laplace approximations are commonly used to approximate high‐dimensional integrals in statistical applications, but the quality of such as dimension integral grows is not well understood. In this paper, we provide a new result on size error first‐ and higher‐order approximations, terms rate growth information about each integrated variables. By contrast with many existing results, allow for variation among different We apply our results investigate likelihood some generalized linear mixed models.

Composite likelihoods are a class of alternatives to the full likelihood which may be used for inference in many situations where itself is intractable.A composite estimator will robust certain types model misspecification, since it computed without need specify distribution response.This potential increased robustness has been widely discussed recent years, and considered secondary motivation use likelihood.The purpose this paper show that there some actually suffer loss compared maximum...

Abstract Background In binary logistic regression data are ‘separable’ if there exists a linear combination of explanatory variables which perfectly predicts the observed outcome, leading to non-existence some maximum likelihood coefficient estimates. A popular solution obtain finite estimates even with separable is Firth’s (FL), was originally proposed reduce bias in The question convergence becomes more involved when analyzing clustered as frequently encountered clinical research, e.g....

We propose a new method for estimating subject-specific mean functions from longitudinal data. aim to do this in flexible manner (without restrictive assumptions about the shape of functions), while exploiting similarities between different subjects. Functional principal components analysis fulfils both requirements, and methods functional have been developed However, we find that these existing sometimes give fitted which are more complex than needed provide good fit develop penalised...

Composite likelihoods are a class of alternatives to the full likelihood which widely used in many situations itself is intractable. A composite may be computed without need specify distribution response, means that some resulting estimator will more robust model misspecification than maximum estimator. The purpose this note show such increased robustness not guaranteed. An example given various marginal estimators inconsistent under misspecification, even though consistent.

Laplace approximations are commonly used to approximate high-dimensional integrals in statistical applications, but the quality of such as dimension integral grows is not well understood. In this paper, we prove a new result on size error first- and higher-order approximations, apply investigate likelihood some generalized linear mixed models.

ABSTRACT We present a topological method for the detection and quantification of bone microstructure from non-linear microscopy images. Specifically, we analyse second harmonic generation (SHG) two photon excited autofluorescence (TPaF) images tissue which capture distribution matrix (fibrillar collagen) structure autofluorescent molecules, respectively. Using persistent homology statistics with signed Euclidean distance transform filtration on binary patches images, are able to quantify...

Many statistical models have likelihoods which are intractable: it is impossible or too expensive to compute the likelihood exactly. In such settings, a common approach replace with an approximation, and proceed inference as if approximate were exact likelihood. this paper, we describe conditions on guarantee that naive has same first-order asymptotic properties We investigate implications of these results for using Laplace approximation in simple two-level latent variable model, reduced...

You have accessThe ASHA LeaderInbox1 Nov 2011Technology Reservations Helen Ogden Google Scholar More articles by this author https://doi.org/10.1044/leader.IN1.16152011.2 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In As much as I enjoy using my own iPad for a multitude of purposes, reservations about it treatment tool (“Apps: An Emerging Tool SLPs,” Oct. 11). True, is engaging, but our students are rapidly losing the ability become engaged anything that not on screen. We...

The likelihood for the parameters of a generalized linear mixed model involves an integral which may be very high dimension. Because this intractability, many approximations to have been proposed, but all can fail when is sparse, in that there only small amount information available on each random effect. sequential reduction method described paper exploits dependence structure posterior distribution effects reduce substantially cost finding accurate approximation models with sparse structure.

You have accessThe ASHA LeaderInbox1 Apr 2011Dream Come True? Helen Ogden Google Scholar More articles by this author https://doi.org/10.1044/leader.IN5.16042011.45 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In I was wondering if there some missing information in the ”Teamwork That Works” article Feb. 15 issue. As a school-based speech-language pathologist California who at beginning of year had two schools with total enrollment 1,505 students, plus preschools, can only...

Abstract Background In binary logistic regression data are ‘separable’ if there exists a linear combination of explanatory variables which perfectly predicts the observed outcome, leading to non-existence some maximum likelihood coefficient estimates. A popular solution obtain finite estimates even with separable is Firth’s regression, was originally proposed reduce bias in The question convergence becomes more involved when analyzing clustered as frequently encountered clinical research,...