Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat

Bayesian networks are now widespread for modelling uncertain knowledge. They graph probabilistic relationships, which are quantified using conditional probability tables (CPTs). When empirical data are unavailable, experts may specify CPTs. Here we propose novel methodology for quantifying CPTs: a Bayesian statistical approach to both elicitation and encoding of expert-specified probabilities, in a way that acknowledges their uncertainty. We illustrate this new approach using a case study describing habitat most at risk from feral pigs. For complicated CPTs, it is difficult to elicit all scenarios (CPT entries). Like the CPT Calculator software program, we ask about a few scenarios (e.g. under a one-factor-at-a-time design) to reduce the experts' workload. Unlike CPT Calculator, we adopt a global rather than local regression to ‘fill out’ CPT entries. Unlike other methods for scenario-based elicitation for regression, we capture uncertainty about each probability in a sequence that explicitly controls biases and enhances interpretation. Furthermore, to utilize all elicited information, we introduce Bayesian rather than Classical generalised linear modelling (GLM). For large CPTs (e.g. >3 levels per parent) we show Bayesian GLM supports richer inference, particularly on interactions, even with few scenarios, providing more information regarding accuracy of encoding.</p

Prevalence and factors associated with low back pain among health care workers in southwestern Saudi Arabia

Abstract Background The purpose was to measure the prevalence and related risk factors of low back pain (LBP) among health care workers (HCWs) at different levels of health care in southwestern Saudi Arabia. Methods A cross-sectional study using a self-administered questionnaire was conducted among HCWs providing primary, secondary and tertiary health care services in the Aseer region, southwestern Saudi Arabia. The questionnaire collected data regarding having LBP in the past 12 months, socio-demographics, work conditions and history of chronic diseases, regular physical exercise and overexertional back trauma. Univariate and multivariable logistic regression analyses were performed. Results Out of 740 participants, the overall prevalence of LBP in the past 12 months amounted to73.9% (95% CI: 70.7–77.0). The prevalence of LBP with neurological symptoms reached 50.0%. The prevalence of LBP necessitating medications and or physiotherapy was 40.5%, while the prevalence of LBP requiring medical consultation was 20%. Using multivariable logistic regression, the following risk factors were identified: working in secondary and tertiary hospitals (aOR = 1.32, 95% CI:1.01–1.76), increased BMI (aOR = 1.10, 95% CI:1.01–3.65), and positive history of overexertional back trauma (aOR = 11.52, 95% CI:4.14–32.08). On the other hand, practising regular physical exercise was a significant protective factor (aOR = 0.61, 95% CI: 0.42–0.89). Conclusions LBP is a common problem among HCWs. Many preventable risk factors have been identified, including exertional back trauma, increased BMI and lack of regular physical exercise. Occupational health and safety programmes to build ergonomically safe working conditions and encourage regular physical exercise are needed

Screening for glucose-6-phosphate dehydrogenase deficiency in neonates: a comparison between cord and peripheral blood samples

Abstract Background The use of cord blood in the neonatal screening for glucose-6-phosphate dehydrogenase (G6PD) deficiency is being done with increasing frequency but has yet to be adequately evaluated against the use of peripheral blood sample which is usually employed for confirmation. We sought to determine the incidence and gender distribution of G6PD deficiency, and compare the results of cord against peripheral blood in identifying G6PD DEFICIENCY neonates using quantitative enzyme activity assay. Methods We carried out a retrospective and cross-sectional study employing review of primary hospital data of neonates born in a tertiary care center from January to December 2008. Results Among the 8139 neonates with cord blood G6PD assays, an overall incidence of 2% for G6PD deficiency was computed. 79% of these were males and 21% were females with significantly more deficient males (p < .001). Gender-specific incidence was 3.06% for males and 0.85% for females. A subgroup analysis comparing cord and peripheral blood samples (n = 1253) showed a significantly higher mean G6PD value for peripheral than cord blood (15.12 ± 4.52 U/g and 14.52 ± 4.43 U/g, respectively, p = 0.0008). However, the proportion of G6PD deficient neonates did not significantly differ in the two groups (p = 0.79). Sensitivity of cord blood in screening for G6PD deficiency, using peripheral G6PD assay as a gold standard was 98.6% with a NPV of 99.5%. Conclusion There was no difference between cord and peripheral blood samples in discriminating between G6PD deficient and non-deficient neonates. A significantly higher mean peripheral G6PD assay reinforces the use of cord blood for neonatal screening since it has substantially low false negative results

A new updated version of the Weibull model with an application to re-injury rate data

Probability distributions play useful and meaningful roles in sports sciences and biomedical sectors. Probability distributions can be used to model and predict the chances of injuries and recovery time after the injuries. We propose and implement a new method to introduce new probability distributions. The new method is named a new updated-V family, as it can be used to increase/update the flexibility of the modified and traditional probability models. Based on the new updated-V method, a new extension of the Weibull model, namely, a new updated Weibull model is proposed. Statistical properties of the new updated-Weibull model, such as (i) quantile function, (ii) heavy-tailed properties (iii) rth moment, (iv) probability weighted moments, and (i) moment generating functions are presented. For the new updated-V distributions, the estimators are derived. The assessment of the new updated-V distribution estimators is done via a simulation study. A practical application related to the re-injury rate data is considered for the establishment of the applicability of the new updated Weibull distribution

On modeling the log-returns of Bitcoin and Ethereum prices against the USA Dollar

The study and investigation of the behavior of monetary phenomena is an interesting subject for actuaries and practitioners. In the recent age and development in the monetary and financial phenomena, cryptocurrency has gained much attention from actuaries. Over the past decade, several research studies have emerged on modeling and forecasting cryptocurrency exchange rates. This paper also contributes to the modeling of cryptocurrency exchange rates using a new version of the Logistic distribution, namely, a new cotangent-Logistic distribution. The mathematical properties and estimators of the new cotangent-logistic distribution's parameters are obtained. We illustrate the new cotangent-Logistic distribution using two financial data sets representing the log-returns of the Bitcoin and Ethereum prices. We compare the new cotangent-Logistic distribution with the baseline Logistic distribution and its modified version. Using the p-value and three other statistical tests, we show that the new cotangent-Logistic distribution repeatedly provides the optimal fit to cryptocurrency exchange rates