Normally approximated Bayesian credible interval of binomial proportion

2019 ◽  
Vol 30 (1) ◽  
pp. 233-244
Author(s):  
Lionel Sahabo ◽  
Seongbaek Yi
Keyword(s):  
Credible Interval ◽  
Binomial Proportion ◽  
Bayesian Credible Interval

scholarly journals Decline towards extinction of Mexico's vaquita porpoise ( Phocoena sinus )

2019 ◽  
Vol 6 (7) ◽  
pp. 190598 ◽  
Author(s):  
Armando M. Jaramillo-Legorreta ◽  
Gustavo Cardenas-Hinojosa ◽  
Edwyna Nieto-Garcia ◽  
Lorenzo Rojas-Bracho ◽  
Len Thomas ◽  
...  
Keyword(s):  
Population Size ◽  
Total Population ◽  
Population Decline ◽  
Credible Interval ◽  
Critically Endangered ◽  
Posterior Mean ◽  
Bayesian Credible Interval ◽  
Independent Estimate ◽  
Rate Of Decline ◽  
Passive Acoustic

The vaquita ( Phocoena sinus ) is a small porpoise endemic to Mexico. It is listed by IUCN as Critically Endangered because of unsustainable levels of bycatch in gillnets. The population has been monitored with passive acoustic detectors every summer from 2011 to 2018; here we report results for 2017 and 2018. We combine the acoustic trends with an independent estimate of population size from 2015, and visual observations of at least seven animals in 2017 and six in 2018. Despite adoption of an emergency gillnet ban in May 2015, the estimated rate of decline remains extremely high: 48% decline in 2017 (95% Bayesian credible interval (CRI) 78% decline to 9% increase) and 47% in 2018 (95% CRI 80% decline to 13% increase). Estimated total population decline since 2011 is 98.6%, with greater than 99% probability the decline is greater than 33% yr −1 . We estimate fewer than 19 vaquitas remained as of summer 2018 (posterior mean 9, median 8, 95% CRI 6–19). From March 2016 to March 2019, 10 dead vaquitas killed in gillnets were found. The ongoing presence of illegal gillnets despite the emergency ban continues to drive the vaquita towards extinction. Immediate management action is required if the species is to be saved.

scholarly journals Facility and Regional Factors Associated With the New Adoption of Electronic Medical Records in Japan: Nationwide Longitudinal Observational Study (Preprint)

2019 ◽  
Author(s):  
Hideaki Kawaguchi ◽  
Soichi Koike ◽  
Kazuhiko Ohe
Keyword(s):  
Longitudinal Data ◽  
Logistic Models ◽  
Credible Interval ◽  
Fiscal Year ◽  
Multinomial Logistic Model ◽  
Factors Associated ◽  
Bayesian Credible Interval ◽  
Emr Adoption ◽  
Regional Factors ◽  
Over Time

BACKGROUND The rate of adoption of electronic medical record (EMR) systems has increased internationally, and new EMR adoption is currently a major topic in Japan. However, no study has performed a detailed analysis of longitudinal data to evaluate the changes in the EMR adoption status over time. OBJECTIVE This study aimed to evaluate the changes in the EMR adoption status over time in hospitals and clinics in Japan and to examine the facility and regional factors associated with these changes. METHODS Secondary longitudinal data were created by matching data in fiscal year (FY) 2011 and FY 2014 using reference numbers. EMR adoption status was defined as “EMR adoption,” “specified adoption schedule,” or “no adoption schedule.” Data were obtained for hospitals (n=4410) and clinics (n=67,329) that had no adoption schedule in FY 2011 and for hospitals (n=1068) and clinics (n=3132) with a specified adoption schedule in FY 2011. The EMR adoption statuses of medical institutions in FY 2014 were also examined. A multinomial logistic model was used to investigate the associations between EMR adoption status in FY 2014 and facility and regional factors in FY 2011. Considering the regional variations of these models, multilevel analyses with second levels were conducted. These models were constructed separately for hospitals and clinics, resulting in four multinomial logistic models. The odds ratio (OR) and 95% Bayesian credible interval (CI) were estimated for each variable. RESULTS A total of 6.9% of hospitals and 14.82% of clinics with no EMR adoption schedules in FY 2011 had adopted EMR by FY 2014, while 10.49% of hospitals and 33.65% of clinics with specified adoption schedules in FY 2011 had cancelled the scheduled adoption by FY 2014. For hospitals with no adoption schedules in FY 2011, EMR adoption/scheduled adoption was associated with practice size characteristics, such as number of outpatients (from quantile 4 to quantile 1: OR 1.67, 95% CI 1.005-2.84 and OR 2.40, 95% CI 1.80-3.21, respectively), and number of doctors (from quantile 4 to quantile 1: OR 4.20, 95% CI 2.39-7.31 and OR 2.02, 95% CI 1.52-2.64, respectively). For clinics with specified EMR adoption schedules in FY 2011, the factors negatively associated with EMR adoption/cancellation of scheduled EMR adoption were the presence of beds (quantile 4 to quantile 1: OR 0.57, 95% CI 0.45-0.72 and OR 0.74, 95% CI 0.58-0.96, respectively) and having a private establisher (quantile 4 to quantile 1: OR 0.27, 95% CI 0.13-0.55 and OR 0.43, 95% CI 0.19-0.91, respectively). No regional factors were significantly associated with the EMR adoption status of hospitals with no EMR adoption schedules; population density was positively associated with EMR adoption in clinics with no EMR adoption schedule (quantile 4 to quantile 1: OR 1.49, 95% CI 1.32-1.69). CONCLUSIONS Different approaches are needed to promote new adoption of EMR systems in hospitals as compared to clinics. It is important to induce decision making in small- and medium-sized hospitals, and regional postdecision technical support is important to avoid cancellation of scheduled EMR adoption in clinics.

Comparing Medical Care Costs using Bayesian Credible Intervals for the Ratio of Means of Delta-Lognormal Distributions

2020 ◽  
Vol 28 (Supp01) ◽  
pp. 51-68 ◽  
Author(s):  
Patcharee Maneerat ◽  
Sa-Aat Niwitpong
Keyword(s):  
Medical Care ◽  
Average Length ◽  
Credible Interval ◽  
Error Rates ◽  
Lognormal Distributions ◽  
Medical Care Costs ◽  
Bayesian Credible Interval ◽  
Credible Intervals ◽  
Variance Estimates ◽  
Care Costs

When considering the medical care costs data with a high proportion of zero items of two inpatient groups, comparing them can be estimated using confidence intervals for the ratio of the means of two delta-lognormal distributions. The Bayesian credible interval-based uniform-beta prior (BCIh-UB) is proposed and compared with the generalized confidence interval (GCI), fiducial GCI (FGCI), the method of variance estimates recovery (MOVER), BCIh based on Jeffreys’ rule prior (BCIh-JR), and BCIh based on the normal-gamma prior (BCIh-NG). The coverage probability (CP), average length (AL), and lower and upper error rates were the performance measures applied for assessing the methods through a Monte Carlo simulation. A numerical evaluation showed that BCIh-UB had much better CP and AL than the others even with a large difference between the variances and with a high proportion of zero. Finally, to illustrate the efficacy of BCIh-UB, the methods were applied to two sets of medical care costs data.

scholarly journals The Support Interval

2018 ◽  
Author(s):  
Eric-Jan Wagenmakers ◽  
Quentin Frederik Gronau ◽  
Fabian Dablander ◽  
Alexander Etz
Keyword(s):  
Confidence Interval ◽  
Hypothesis Test ◽  
Credible Interval ◽  
Minimum Amount ◽  
Evidence Based ◽  
Support Interval ◽  
Bayesian Credible Interval ◽  
Parameter Values ◽  
Lindley’S Paradox ◽  
Bayesian Support

A frequentist confidence interval can be constructed by inverting a hypothesis test, such that the interval contains only parameter values that would not have been rejected by the test. We show how a similar definition can be employed to construct a Bayesian support interval. Consistent with Carnap’s theory of corroboration, the support interval contains only parameter values that receive at least some minimum amount of support from the data. The support interval is not subject to Lindley’s paradox and provides an evidence-based perspective on inference that differ from the belief-based perspective that forms the basis of the standard Bayesian credible interval.

The Support Interval

2019 ◽  
Author(s):  
Eric-Jan Wagenmakers ◽  
Quentin Frederik Gronau ◽  
Fabian Dablander ◽  
Alexander Etz
Keyword(s):  
Confidence Interval ◽  
Hypothesis Test ◽  
Credible Interval ◽  
Minimum Amount ◽  
Evidence Based ◽  
Support Interval ◽  
Bayesian Credible Interval ◽  
Parameter Values ◽  
Lindley’S Paradox ◽  
Bayesian Support

A frequentist confidence interval can be constructed by inverting a hypothesis test, such that the interval contains only parameter values that would not have been rejected by the test. We show how a similar definition can be employed to construct a Bayesian support interval. Consistent with Carnap’s theory of corroboration, the support interval contains only parameter values that receive at least some minimum amount of support from the data. The support interval is not subject to Lindley's paradox and provides an evidence-based perspective on inference that differs from the belief-based perspective that forms the basis of the standard Bayesian credible interval.

Shell Egg Handling and Preparation Practices in Food Service Establishments in Finland

2007 ◽  
Vol 70 (10) ◽  
pp. 2266-2272
Author(s):  
S. LIEVONEN ◽  
J. RANTA ◽  
R. MAIJALA
Keyword(s):  
Room Temperature ◽  
Food Service ◽  
Credible Interval ◽  
Quantitative Risk Assessment ◽  
Salmonella Infection ◽  
Shell Eggs ◽  
Egg Consumption ◽  
Bayesian Credible Interval ◽  
Foodborne Outbreaks ◽  
Handling Practices

Foodborne outbreaks are often reported to be acquired at food service establishments. As a part of a quantitative risk assessment on the consumer risk of contracting Salmonella infection via shell eggs, we studied how small, medium, and large restaurants, institutional kitchens, and staff canteens (n = 171) purchase, store, and use shell eggs. In addition, we estimated the fraction of raw and undercooked risky egg dishes among all egg dishes served in food service establishments of different sizes and types. The majority of establishments used shell eggs (78%), purchased eggs once per week (39%), and stored eggs at cool temperatures (82%). The size of the food service establishment had a less significant effect on shell egg preparation and handling practices than the type of the establishment. In particular, restaurants and institutional kitchens differed from each other. Restaurants purchased shell eggs more frequently, were more likely to store them at room temperature, stored shell eggs for a shorter period, and were more likely to prepare undercooked egg dishes than institutional kitchens. It was predicted that 6 to 20% of all different egg dishes prepared in a single randomly chosen food service establishment would be risky egg dishes with a 95% Bayesian credible interval of 0 to 96%, showing uncertainty because of the variability between kitchens and uncertainty in kitchen type–specific parameters. The results indicate that although most Finnish food service establishments had safe egg handling practices, a substantial minority expressed risky behavior. Compared with the egg consumption patterns in private Finnish households, however, practices in food service establishments did not prove to be more prone to risk.

scholarly journals Simultaneous confidence intervals for all pairwise differences between the coefficients of variation of rainfall series in Thailand

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11651
Author(s):  
Noppadon Yosboonruang ◽  
Sa-Aat Niwitpong ◽  
Suparat Niwitpong
Keyword(s):  
Confidence Intervals ◽  
Credible Interval ◽  
Rainfall Series ◽  
Good Tool ◽  
Simultaneous Confidence Intervals ◽  
Lognormal Distributions ◽  
Bayesian Credible Interval ◽  
Coefficients Of Variation ◽  
Pairwise Differences ◽  
Fiducial Generalized Confidence Interval

The delta-lognormal distribution is a combination of binomial and lognormal distributions, and so rainfall series that include zero and positive values conform to this distribution. The coefficient of variation is a good tool for measuring the dispersion of rainfall. Statistical estimation can be used not only to illustrate the dispersion of rainfall but also to describe the differences between rainfall dispersions from several areas simultaneously. Therefore, the purpose of this study is to construct simultaneous confidence intervals for all pairwise differences between the coefficients of variation of delta-lognormal distributions using three methods: fiducial generalized confidence interval, Bayesian, and the method of variance estimates recovery. Their performances were gauged by measuring their coverage probabilities together with their expected lengths via Monte Carlo simulation. The results indicate that the Bayesian credible interval using the Jeffreys’ rule prior outperformed the others in virtually all cases. Rainfall series from five regions in Thailand were used to demonstrate the efficacies of the proposed methods.

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