Recent research advocates the use of count models with random parameters as an alternative method for analyzing accident frequencies. In this paper a dataset composed of urban arterials in Vancouver, British Columbia, is considered where the 392 segments were clustered into 58 corridors. The main objective is to assess the corridor effects with alternate specifications. The proposed models were estimated in a Full Bayes context via Markov Chain Monte Carlo (MCMC) simulation and were compared in terms of their goodness of fit and inference. A variety of covariates were found to significantly influence accident frequencies. However, these covariates resulted in random parameters and thereby their effects on accident frequency were found to vary significantly across corridors. Further, a Poisson-lognormal (PLN) model with random parameters for each corridor provided the best fit. Apart from the improvement in goodness of fit, such an approach is useful in gaining new insights into how accident frequencies are influenced by the covariates, and in accounting for heterogeneity due to unobserved road geometrics, traffic characteristics, environmental factors and driver behavior. The inclusion of corridor effects in the mean function could also explain enough variation that some of the model covariates would be rendered non-significant and thereby affecting model inference.
The study is based on a sample of 965 children living in Oulu region (Finland), who were monitored for acute middle ear infections from birth to the age of two years. We introduce a nonparametrically defined intensity model for ear infections, which involves both fixed and time dependent covariates, such as calendar time, current age, length of breast-feeding time until present, or current type of day care. Unmeasured heterogeneity, which manifests itself in frequent infections in some children and rare in others and which cannot be explained in terms of the known covariates, is modelled by using individual frailty parameters. A Bayesian approach is proposed to solve the inferential problem. The numerical work is carried out by Monte Carlo integration (Metropolis-Hastings algorithm).
Monthly dosing with ranibizumab (RBZ) is needed to achieve maximal visual gains in patients with neovascular ('wet') age-related macular degeneration (wAMD). In Sweden, dosing is performed as needed (RBZ PRN), resulting in suboptimal efficacy. Intravitreal aflibercept (IVT-AFL) every 2 months after three initial monthly doses was clinically equivalent to RBZ monthly dosing (RBZ q4) in wAMD clinical trials. We assessed the cost-effectiveness of IVT-AFL versus RBZ q4 and RBZ PRN in Sweden.
A Markov model compared IVT-AFL to RBZ q4 or RBZ PRN over 2 years. Health states were based on visual acuity in better-seeing eye; a proportion discontinued treatment monthly or upon visual acuity
Using the coalescent process, DNA sequences of a sample of individuals can be used to study the phylogenetic history of the individuals. Under the infinitely-many-sites mutation model, the DNA sequence data can be summarized by the number of segregating sites (which is numerically equivalent to the number of mutations on the tree). A number of methods exist, including a recursive method presented in this paper, that obtain an estimate of the age of the most recent common ancestor (MRCA), given the number of mutations. This paper introduces a method for finding the ages of mutations, given the total number of mutations on the tree. While the result is not useful in estimating the age of a specific segregating site, it is useful in examining the underlying assumption of a relatively constant population over time. This utilization of the result is illustrated using DNA sequence data obtained from a sample of Amerindians of the Nuu-Chah-Nulth tribe.
To examine the incidence, mortality and case fatality of acute coronary syndrome (ACS) in Finland during 1993-2007 and to create forecasts of the absolute numbers of ACS cases in the future, taking into account the aging of the population.
Community surveillance study and modelled forecasts of the future.
Two sets of population-based coronary event register data from Finland (FINAMI and the National Cardiovascular Disease Register (CVDR)). Bayesian age-period-cohort (APC) modelling.
24 905 observed ACS events in the FINAMI register and 364 137 in CVDR.
Observed trends of ACS events during 1993-2007, forecasted numbers of ACS cases, and the prevalence of ACS survivors until the year 2050.
In the FINAMI register, the average annual declines in age-standardised incidence of ACS were 1.6% (p
Compared with no alcohol consumption, heavy alcohol intake is associated with a higher rate of heart failure (HF) whereas light-to-moderate intake may be associated with a lower rate. However, several prior studies did not exclude former drinkers, who may have changed alcohol consumption in response to diagnosis. This study aimed to investigate the association between alcohol intake and incident HF.
We conducted a prospective cohort study of 33 760 men aged 45 to 79 years with no HF, diabetes mellitus, or myocardial infarction at baseline participating in the Cohort of Swedish Men Study. We excluded former drinkers. At baseline, participants completed a food frequency questionnaire and reported other characteristics. HF was defined as hospitalization for or death from HF, ascertained by Swedish inpatient and cause-of-death records from January 1, 1998, through December 31, 2011. We constructed Cox proportional hazards models to estimate multivariable-adjusted incidence rate ratios. During follow-up, 2916 men were hospitalized for (n=2139) or died (n=777) of incident HF. There was a U-shaped relationship between total alcohol intake and incident HF (P=0.0004). There was a nadir at light-to-moderate alcohol intake: consuming 7 to
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OBJECTIVE: We explored patterns of alcohol use among American Indian youths as well as concurrent predictors and developmental outcomes 6 years later. METHOD: This study used six semi-annual waves of data collected across 3 years from 861 American Indian youths, ages 14-20 initially, from two western tribes. Using a latent Markov model, we examined patterns of change in latent states of adolescent alcohol use in the past 6 months, combining these states of alcohol use into three latent statuses that described patterns of change across the 3 years: abstainers, inconsistent drinkers, and consistent drinkers. We then explored how the latent statuses differed, both initially and in young adulthood (ages 20-26). RESULTS: Both alcohol use and nonuse were quite stable across time, although we also found evidence of change. Despite some rather troubling drinking patterns as teens, especially among consistent drinkers, most of the youths had achieved important tasks of young adulthood. But patterns of use during adolescence were related to greater levels of substance use in young adulthood. CONCLUSIONS: Latent Markov modeling provided a useful categorization of alcohol use that more finely differentiated those youths who would otherwise have been considered inconsistent drinkers. Findings also suggest that broad-based interventions during adolescence may not be the most important ones; instead, programs targeting later alcohol and other drug use may be a more strategic use of often limited resources.
We present a general algorithm for the detection of genomic variants using the Illumina iSelect platform. The Illumina iSelect platform is designed to detect SNPs, but our algorithm allows for the detections of more general forms of variations, including copy number polymorphisms and microsatellites. The algorithm does not rely on a priori information of the type of polymorphism being studied and is designed to genotype call a large number of individuals simultaneously. The algorithm proceeds by initially normalizing intensity and correcting for batch effects. Then each marker is clustered using a modified Gaussian mixture model where we account for variances in the expression of an individuals and the variance measured in bead level intensities of a probe/marker pair. Finally, these clusters are used to determine genotypes. The algorithm was then run on a dataset of 35,000 Icelandic individuals.
OBJECTIVE: To assess the cost effectiveness of screening men aged 65 for abdominal aortic aneurysm. DESIGN: Cost effectiveness analysis based on a probabilistic, enhanced economic decision analytical model from screening to death. POPULATION AND SETTING: Hypothetical population of men aged 65 invited (or not invited) for ultrasound screening in the Danish healthcare system. DATA SOURCES: Published results from randomised trials and observational epidemiological studies retrieved from electronic bibliographic databases, and supplementary data obtained from the Danish Vascular Registry. DATA SYNTHESIS: A hybrid decision tree and Markov model was developed to simulate the short term and long term effects of screening for abdominal aortic aneurysm compared with no systematic screening on clinical and cost effectiveness outcomes. Probabilistic sensitivity analyses using Monte Carlo simulation were carried out. Results were presented in a cost effectiveness acceptability curve, an expected value of perfect information curve, and a curve showing the expected (net) number of avoided deaths from abdominal aortic aneurysm over time after the introduction of screening. The model was validated by calibrating base case health outcomes and expected activity levels against evidence from the recent Cochrane review of screening for abdominal aortic aneurysm. RESULTS: The estimated costs per quality adjusted life year (QALY) gained discounted at 3% per year over a lifetime for costs and QALYs was pound43 485 (euro54,852; $71,160). At a willingness to pay threshold of pound30,000 the probability of screening for abdominal aortic aneurysm being cost effective was less than 30%. One way sensitivity analyses showed the incremental cost effectiveness ratio varying from pound32,640 to pound66,001 per QALY. CONCLUSION: Screening for abdominal aortic aneurysm does not seem to be cost effective. Further research is needed on long term quality of life outcomes and costs.