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

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

Chiral nematic liquid crystals in torus-shaped and cylindrical cavities

We present a Monte Carlo simulation study of chiral nematic liquid crystals confined in torus-shaped and cylindrical cavities. For an achiral nematic with planar degenerate anchoring confined to a toroidal or cylindrical cavity, the ground state is defect free, with an untwisted director field. As chirality is introduced, the ground state remains defect free but the director field becomes twisted within the cavity. For homeotropic anchoring, the ground state for an achiral nematic within a toroidal cavity consists of two disclination rings, one large and one small, that follow the major circumference of the torus. As chirality is introduced and increased, this ground state becomes unstable with respect to twisted configurations. The closed nature of the toroidal cavity requires that only a half integer number of twists can be formed and this leads to the ground state being either a single disclination line that encircles the torus twice or a pair of intertwined disclination rings forming stable, knotted defect structures

Citizen Science 2.0 : Data Management Principles to Harness the Power of the Crowd

Citizen science refers to voluntary participation by the general public in scientific endeavors. Although citizen science has a long tradition, the rise of online communities and user-generated web content has the potential to greatly expand its scope and contributions. Citizens spread across a large area will collect more information than an individual researcher can. Because citizen scientists tend to make observations about areas they know well, data are likely to be very detailed. Although the potential for engaging citizen scientists is extensive, there are challenges as well. In this paper we consider one such challenge – creating an environment in which non-experts in a scientific domain can provide appropriate and accurate data regarding their observations. We describe the problem in the context of a research project that includes the development of a website to collect citizen-generated data on the distribution of plants and animals in a geographic region. We propose an approach that can improve the quantity and quality of data collected in such projects by organizing data using instance-based data structures. Potential implications of this approach are discussed and plans for future research to validate the design are described

Treatment-based classification of low back pain – who are the unclear classifications?

A recent focus in low back pain research has been to identify patient subgroups that respond best to certain treatments. To integrate these subgroup findings into a useable form, a treatment-based classification algorithm for LBP was created.1,2 To allow the algorithm to be comprehensive – eg, provide a classification for all patients – additional criteria are provided to assist therapists’ decisions for patients who do not clearly meet a treatment subgroup (unclear classifications). Recent research found that approximately 34% of patients will receive unclear classifications using the algorithm.3 It has also been shown that the reliability of the classification decision for unclear classifications is poor – significant variability between raters exists.3 In addition to poor reliability, outcomes for patients receiving unclear classifications may be inferior to outcomes of those receiving clear classifications.4 Thus the aim of the present study was to determine if people receiving unclear classifications are different from those with clear classifications in the hopes to refine the classification algorithm

The translation, validity and reliability of the German version of the Fremantle Back Awareness Questionnaire

Background: The Fremantle Back Awareness Questionnaire (FreBAQ) claims to assess disrupted self-perception of the back. The aim of this study was to develop a German version of the Fre-BAQ (FreBAQ-G) and assess its test-retest reliability, its known-groups validity and its convergent validity with another purported measure of back perception. Methods: The FreBaQ-G was translated following international guidelines for the transcultural adaptation of questionnaires. Thirty-five patients with non-specific CLBP and 48 healthy participants were recruited. Assessor one administered the FreBAQ-G to each patient with CLBP on two separate days to quantify intra-observer reliability. Assessor two administered the FreBaQ-G to each patient on day 1. The scores were compared to those obtained by assessor one on day 1 to assess inter-observer reliability. Known-groups validity was quantified by comparing the FreBAQ-G score between patients and healthy controls. To assess convergent validity, patient\u27s FreBAQ-G scores were correlated to their two-point discrimination (TPD) scores. Results: Intra- and Inter-observer reliability were both moderate with ICC3.1 = 0.88 (95%CI: 0.77 to 0.94) and 0.89 (95%CI: 0.79 to 0.94), respectively. Intra- and inter-observer limits of agreement (LoA) were 6.2 (95%CI: 5.0±8.1) and 6.0 (4.8±7.8), respectively. The adjusted mean difference between patients and controls was 5.4 (95%CI: 3.0 to 7.8, p\u3c0.01). Patient\u27s FreBAQ-G scores were not associated with TPD thresholds (Pearson\u27s r = -0.05, p = 0.79). Conclusions: The FreBAQ-G demonstrated a degree of reliability and known-groups validity. Interpretation of patient level data should be performed with caution because the LoA were substantial. It did not demonstrate convergent validity against TPD. Floor effects of some items of the FreBAQ-G may have influenced the validity and reliability results. The clinimetric properties of the FreBAQ-G require further investigation as a simple measure of disrupted self-perception of the back before firm recommendations on its use can be made

The DEMS-DOSS study: validating a delirium monitoring tool in hospitalised older adults

Objective: to evaluate the sensitivity, specificity and test–retest reliability of the Delirium Early Monitoring System-Delirium Observation Screening Scale (DEMS-DOSS). Design: prospective diagnostic accuracy study of a convenience sample of admitted older adults with DEMS-DOSS and reference standard assessments. Setting: 60-bed aged care precinct at a metropolitan hospital in Sydney, Australia. Participants: 156 patients (aged ≥65 years old) were recruited to participate between April 2018 and March 2020. One hundred participants were included in the analysis. Measurements: Participants were scored on the DEMS-DOSS. Trained senior aged care nurses conducted a standardised clinical interview based on the Diagnostic and Statistical Manual of Mental Disorder (DSM)-IV delirium criteria, within two hours of DEMS-DOSS completion. The senior aged care nurse undertaking the DSM-IV interview was blinded to the results of the DEMS-DOSS. Results: Participants’ mean age was 84 (SD ±7.3) years and 39% (n = 39) had a documented diagnosis of dementia. Delirium was detected in 38% (n = 38) according to the reference standard. The DEMS-DOSS had a sensitivity of 76.3% and a specificity of 75.8% for delirium. The area under the receiver operating characteristics curve for delirium was 0.76. The test–retest reliability of the DEMS-DOSS was found to be high (r = 0.915). Conclusion: DEMS-DOSS is a sensitive and specific tool to assist with monitoring new onset and established delirium in hospitalised older adults. Further studies are required to evaluate the impact of the monitoring tool on health outcomes