Inference under unequal probability sampling with the Bayesian exponentially tilted empirical likelihood.

Fully Bayesian inference in the presence of unequal probability sampling requires stronger structural assumptions on the data-generating distribution than frequentist semiparametric methods, but offers the potential for improved small-sample inference and convenient evidence synthesis. We demonstrate that the Bayesian exponentially tilted empirical likelihood can be used to combine the practical benefits of Bayesian inference with the robustness and attractive large-sample properties of frequentist approaches. Estimators defined as the solutions to unbiased estimating equations can be used to define a semiparametric model through the set of corresponding moment constraints. We prove Bernstein-von Mises theorems which show that the posterior constructed from the resulting exponentially tilted empirical likelihood becomes approximately normal, centred at the chosen estimator with matching asymptotic variance; thus, the posterior has properties analogous to those of the estimator, such as double robustness, and the frequentist coverage of any credible set will be approximately equal to its credibility. The proposed method can be used to obtain modified versions of existing estimators with improved properties, such as guarantees that the estimator lies within the parameter space. Unlike existing Bayesian proposals, our method does not prescribe a particular choice of prior or require posterior variance correction, and simulations suggest that it provides superior performance in terms of frequentist criteria.

Two-Part and Related Regression Models for Longitudinal Data.

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution.

Changes in severity of 2009 pandemic A/H1N1 influenza in England: a Bayesian evidence synthesis.

OBJECTIVE: To assess the impact of the 2009 A/H1N1 influenza pandemic in England during the two waves of activity up to end of February 2010 by estimating the probabilities of cases leading to severe events and the proportion of the population infected. DESIGN: A Bayesian evidence synthesis of all available relevant surveillance data in England to estimate severity of the pandemic. DATA SOURCES: All available surveillance systems relevant to the pandemic 2009 A/H1N1 influenza outbreak in England from June 2009 to February 2010. Pre-existing influenza surveillance systems, including estimated numbers of symptomatic cases based on consultations to the health service for influenza-like illness and cross sectional population serological surveys, as well as systems set up in response to the pandemic, including follow-up of laboratory confirmed cases up to end of June 2009 (FF100 and Fluzone databases), retrospective and prospective follow-up of confirmed hospitalised cases, and reported deaths associated with pandemic 2009 A/H1N1 influenza. Main outcome measures Age specific and wave specific probabilities of infection and symptomatic infection resulting in hospitalisation, intensive care admission, and death, as well as infection attack rates (both symptomatic and total). The probabilities of intensive care admission and death given hospitalisation over time are also estimated to evaluate potential changes in severity across waves. RESULTS: In the summer wave of A/H1N1 influenza, 0.54% (95% credible interval 0.33% to 0.82%) of the estimated 606,100 (419,300 to 886,300) symptomatic cases were hospitalised, 0.05% (0.03% to 0.08%) entered intensive care, and 0.015% (0.010% to 0.022%) died. These correspond to 3200 (2300 to 4700) hospital admissions, 310 (200 to 480) intensive care admissions, and 90 (80 to 110) deaths in the summer wave. In the second wave, 0.55% (0.28% to 0.89%) of the 1,352,000 (829,900 to 2,806,000) estimated symptomatic cases were hospitalised, 0.10% (0.05% to 0.16%) were admitted to intensive care, and 0.025% (0.013% to 0.040%) died. These correspond to 7500 (5900 to 9700) hospitalisations, 1340 (1030 to 1790) admissions to intensive care, and 240 (310 to 380) deaths. Just over a third (35% (26% to 45%)) of infections were estimated to be symptomatic. The estimated probabilities of infections resulting in severe events were therefore 0.19% (0.12% to 0.29%), 0.02% (0.01% to 0.03%), and 0.005% (0.004% to 0.008%) in the summer wave for hospitalisation, intensive care admission, and death respectively. The corresponding second wave probabilities are 0.19% (0.10% to 0.32%), 0.03% (0.02% to 0.06%), and 0.009% (0.004% to 0.014%). An estimated 30% (20% to 43%) of hospitalisations were detected in surveillance systems in the summer, compared with 20% (15% to 25%) in the second wave. Across the two waves, a mid-estimate of 11.2% (7.4% to 18.9%) of the population of England were infected, rising to 29.5% (16.9% to 64.1%) in 5-14 year olds. Sensitivity analyses to the evidence included suggest this infection attack rate could be as low as 5.9% (4.2% to 8.7%) or as high as 28.4% (26.0% to 30.8%). In terms of the probability that an infection leads to death in the second wave, these correspond, respectively, to a high estimate of 0.017% (0.011% to 0.024%) and a low estimate of 0.0027% (0.0024% to 0.0031%). CONCLUSIONS: This study suggests a mild pandemic, characterised by case and infection severity ratios increasing between waves. Results suggest low ascertainment rates, highlighting the importance of systems enabling early robust estimation of severity, to inform optimal public health responses, particularly in light of the apparent resurgence of the 2009 A/H1N1 strain in the 2010-11 influenza season.

Estimating time to onset of swine influenza symptoms after initial novel A(H1N1v) viral infection.

Characterization of the incubation time from infection to onset is important for understanding the natural history of infectious diseases. Attempts to estimate the incubation time distribution for novel A(H1N1v) have been, up to now, based on limited data or peculiar samples. We characterized this distribution for a generic group of symptomatic cases using laboratory-confirmed swine influenza case-information. Estimates of the incubation distribution for the pandemic influenza were derived through parametric time-to-event analyses of data on onset of symptoms and exposure dates, accounting for interval censoring. We estimated a mean of about 1·6-1·7 days with a standard deviation of 2 days for the incubation time distribution in those who became symptomatic after infection with the A(H1N1v) virus strain. Separate analyses for the <15 years and ≥ 15 years age groups showed a significant (P<0·02) difference with a longer mean incubation time in the older age group.

Development and initial validation of a screening questionnaire for psoriatic arthritis: the Toronto Psoriatic Arthritis Screen (ToPAS).

OBJECTIVE: To develop and validate a psoriatic arthritis (PsA) screening questionnaire: the Toronto Psoriatic Arthritis Screen (ToPAS). METHODS: The ToPAS was developed through review of items seen in patients with PsA and evaluation by patients with PsA and patients with other rheumatological conditions, and was administered to consecutive consenting patients attending five clinics: PsA, psoriasis, general dermatology, general rheumatology (excluding PsA patients) and family medicine. All patients were assessed by a rheumatologist according to a standard protocol. A three-step analysis strategy was adopted: a stepwise logistic regression to identify the questions most important in discriminating between those with and without PsA; a logistic model was fitted to three clinically relevant domains for PsA: skin, joints and nails; and a simpler weighting of each of the domains used in step 2. Receiver operating characteristic (ROC) curves were obtained based on these various models. RESULTS: In all, there were 134 patients from the PsA clinic, 123 with psoriasis, 118 from dermatology, 135 from rheumatology and 178 from family medicine. A simplified discriminatory score based on the skin, joint and nail domains gave results comparable to other methods with an observed overall sensitivity and specificity, based on a single cut point, of 86.8% and 93.1%. When the patients with PsA were compared with each of the other four patient groups individually, the sensitivity and specificity of the ToPAS were: psoriasis 89.1%, 86.3%; dermatology 91.9%, 95.2%; rheumatology 92.6%, 85.7%; and family medicine 90.4%, 100%. CONCLUSION: Our simplified index is very good at classifying those who are not diagnosed with PsA and those who are diagnosed with PsA.

Cardiovascular morbidity in psoriatic arthritis.

BACKGROUND: Increasing evidence for cardiovascular mortality among patients with psoriasis and psoriatic arthritis (PsA) has accumulated, together with evidence for increased prevalence of risk factors for cardiovascular disease (CVD). OBJECTIVES: To describe cardiovascular morbidity in PsA, determine its prevalence and identify risk factors for its development. METHODS: At the University of Toronto, patients were followed up prospectively according to a standard protocol, including disease-related features and comorbidities. Patients with CVD, including myocardial infarction (MI), angina, hypertension and cerebrovascular accident (CVA), were identified. The prevalence of CVD morbidities in these patients was compared with data from the Canadian Community Health Survey through standardised prevalence ratios (SPRs). Cox relative risk regression analysis was used to analyse risk factors. RESULTS: At the time of analysis, 648 patients were registered in the database. After clinic entry, 122 developed hypertension, 38 had an MI and 5, 21 and 11 had CVA, angina and congestive heart failure (CHF), respectively. 155 patients had at least one of these conditions. The SPRs for MI (2.57; 95% CI 1.73 to 3.80), angina (1.97; 95% CI 1.24 to 3.12) and hypertension (1.90; 95% CI 1.59 to 2.27) were statistically significant, whereas the SPRs for CHF (1.19; 95% CI 0.50 to 2.86) and CVA (0.91; 95% CI 0.34 to 2.43) were not. Factors associated with CVD included diabetes, hyperlipidaemia and high Psoriasis Area and Severity Index scores. CONCLUSION: Patients with PsA are at increased risk of cardiovascular morbidities compared with the general population. In addition to known risk factors for CVD, severe psoriasis is an important predictor in patients with PsA.

Common mental disorder symptom counts in populations: are there distinct case groups above epidemiological cut-offs?

BACKGROUND: At the lower end of IQ distributions in general populations, there is a clear excess of cases, representing the distinct pathology of severe learning disability. This study aimed to establish whether such a subpopulation exists in distributions of common mental disorder and depression symptom scores, above epidemiological 'case' cut-offs. METHOD: Data from 9556 non-psychotic respondents to the 1993 OPCS (Office of Population Censuses and Surveys) National Household Psychiatric Morbidity Survey were analysed. The distribution of total neurotic symptom and depression scores from the revised Clinical Interview Schedule were examined. Automated least squares methods were used to fit the best single statistical distribution to the data. RESULTS: A single exponential curve provided the best fit for the whole population, but floor effects produced deviations at symptom counts of 0-3. After truncation, exponential distributions fitted excellently. Proportions of the population above conventional cut-offs of > or = 12 symptoms differed by < 12% from expected for a range of low and high prevalence groups. The single exponential model also fitted the depression score. CONCLUSIONS: Symptom counts for the common mental disorders fall within single population distributions, with little apparent numerical excess in the case range. High and low prevalences of these disorders appear to be population characteristics, with shifts in exponential means predicting proportions above case cut-offs.

Natural head posture--considerations of reproducibility.

This three-part study investigated the reproducibility of natural head posture (NHP) using radiographs and photographs. In part 1, reproducibility of cephalograms 1 year after the introduction of NHP was investigated and found to be less favourable (Dahlberg coefficient of 2.99 degrees) than most other previous investigations. In order to minimize radiation exposure of patients, reproducibility of photographs and method agreement between photographs and cephalograms were investigated in part 2. Reproducibility of the two photographs was poor (2.71 degrees). However, method agreement between cephalograms and the photographs taken at the same time was good (1.39 degrees). Replacement of the radiographic method with the photographic method for assessing NHP reproducibility appeared justified. Changing the protocol for achieving NHP in part 3 of the study improved reproducibility substantially (1.41 degrees). Various statistical methods were used to assess reproducibility and method agreement. Bland and Altman's graphical representation was found to be the most appropriate for method agreement. The Dahlberg coefficient, commonly used to assess NHP repeatability/reproducibility, does not provide an extreme enough interval to allow a sufficient clinical assessment of a method to be undertaken, compared with the reproducibility coefficient. That is, the latter provides a 95 per cent range, compared with 52 per cent with Dahlberg.