scholarly journals Influence of Institution-Based Factors on Preoperative Blood Testing Prior to Low-Risk Surgery: A Bayesian Generalized Linear Mixed Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Kazuki Ide ◽  
Hiroshi Yonekura ◽  
Yohei Kawasaki ◽  
Koji Kawakami
Keyword(s):  
Health Care Services ◽  
Credible Interval ◽  
Low Risk ◽  
Institutional Factors ◽  
Posterior Density ◽  
Blood Testing ◽  
Blood Tests ◽  
The Difference ◽  
Mixed Approach ◽  
Highest Posterior Density

To optimize delivery of health care services in clinical practice, the use of unnecessary interventions should be reduced. Although recommendations for this reduction have been accepted worldwide, recent studies have revealed that the use of such procedures continues to increase. We conducted a retrospective cohort study using a nationwide claim-based database to evaluate factors influencing preoperative blood testing prior to low-risk surgery, via a Bayesian generalized linear mixed approach. The study period was set from April 1, 2012, to March 31, 2016, and 69,252 surgeries performed at 9,922 institutions were included in the analysis. Mean patient age was 44.3 ± 11.3 years (57% female). Preoperative blood tests were performed for 59.0% of procedures. Among institutional factors, the number of beds was strongly associated with preoperative blood testing (odds ratio [95% highest posterior density interval (HPD interval)], 2.64 [2.53 to 2.75]). The difference (95% credible interval) in the rate of preoperative blood testing between institutions with <100 beds and ≥100 beds was 0.315 [0.309 to 0.322], and the Bayesian indexθwas 1.00. This indicated that preoperative blood tests are strongly influenced by institutional factors, suggesting that specific guidelines should be developed to avoid excessive preoperative testing for low-risk surgery.

scholarly journals Bayesian Estimation for the Coefficients of Variation of Birnbaum–Saunders Distributions

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2130
Author(s):  
Wisunee Puggard ◽  
Sa-Aat Niwitpong ◽  
Suparat Niwitpong
Keyword(s):  
Confidence Interval ◽  
Simulation Study ◽  
Average Length ◽  
Credible Interval ◽  
Posterior Density ◽  
Concentration Data ◽  
Monte Carlo Simulation Study ◽  
The Difference ◽  
Highest Posterior Density ◽  
Hpd Interval

The Birnbaum–Saunders (BS) distribution, which is asymmetric with non-negative support, can be transformed to a normal distribution, which is symmetric. Therefore, the BS distribution is useful for describing data comprising values greater than zero. The coefficient of variation (CV), which is an important descriptive statistic for explaining variation within a dataset, has not previously been used for statistical inference on a BS distribution. The aim of this study is to present four methods for constructing confidence intervals for the CV, and the difference between the CVs of BS distributions. The proposed methods are based on the generalized confidence interval (GCI), a bootstrapped confidence interval (BCI), a Bayesian credible interval (BayCI), and the highest posterior density (HPD) interval. A Monte Carlo simulation study was conducted to evaluate their performances in terms of coverage probability and average length. The results indicate that the HPD interval was the best-performing method overall. PM 2.5 concentration data for Chiang Mai, Thailand, collected in March and April 2019, were used to illustrate the efficacies of the proposed methods, the results of which were in good agreement with the simulation study findings.

scholarly journals The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9662
Author(s):  
Noppadon Yosboonruang ◽  
Sa-Aat Niwitpong ◽  
Suparat Niwitpong
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Rainfall Data ◽  
Posterior Density ◽  
Lognormal Distributions ◽  
Coefficients Of Variation ◽  
Coverage Probabilities ◽  
The Difference ◽  
Fiducial Generalized Confidence Interval ◽  
Highest Posterior Density

The coefficient of variation is often used to illustrate the variability of precipitation. Moreover, the difference of two independent coefficients of variation can describe the dissimilarity of rainfall from two areas or times. Several researches reported that the rainfall data has a delta-lognormal distribution. To estimate the dynamics of precipitation, confidence interval construction is another method of effectively statistical inference for the rainfall data. In this study, we propose confidence intervals for the difference of two independent coefficients of variation for two delta-lognormal distributions using the concept that include the fiducial generalized confidence interval, the Bayesian methods, and the standard bootstrap. The performance of the proposed methods was gauged in terms of the coverage probabilities and the expected lengths via Monte Carlo simulations. Simulation studies shown that the highest posterior density Bayesian using the Jeffreys’ Rule prior outperformed other methods in virtually cases except for the cases of large variance, for which the standard bootstrap was the best. The rainfall series from Songkhla, Thailand are used to illustrate the proposed confidence intervals.

scholarly journals On Reliability in a Multicomponent Stress-Strength Model with Power Lindley Distribution

2018 ◽  
Vol 41 (2) ◽  
pp. 251-267 ◽  
Author(s):  
Abbas Pak ◽  
Arjun Kumar Gupta ◽  
Nayereh Bagheri Khoolenjani
Keyword(s):  
Interval Estimation ◽  
Parametric Bootstrap ◽  
Real Data ◽  
Credible Interval ◽  
Data Sets ◽  
Strength Model ◽  
Reliability Parameter ◽  
Posterior Density ◽  
Bayes Estimate ◽  
Highest Posterior Density

In this paper  we study the reliability of a multicomponent stress-strength model assuming that the components follow power Lindley model.  The maximum likelihood estimate of the reliability parameter and its asymptotic confidence interval are obtained. Applying the parametric Bootstrap technique, interval estimation of the reliability is presented.  Also, the Bayes estimate and highest posterior density credible interval of the reliability parameter are derived using suitable priors on the parameters. Because there is no closed form for the Bayes estimate, we use the Markov Chain Monte Carlo method to obtain approximate Bayes  estimate of the reliability. To evaluate the performances of different procedures,  simulation studies are conducted and an example of real data sets is provided.

scholarly journals Estimation of the Reliability of a Stress–Strength System from Poisson Half Logistic Distribution

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1307
Author(s):  
Isyaku Muhammad ◽  
Xingang Wang ◽  
Changyou Li ◽  
Mingming Yan ◽  
Miaoxin Chang
Keyword(s):  
Confidence Interval ◽  
Loss Function ◽  
Credible Interval ◽  
Absolute Error ◽  
Asymptotic Distributions ◽  
Logistic Distribution ◽  
Bayes Estimators ◽  
Posterior Density ◽  
Error Loss ◽  
Highest Posterior Density

This paper discussed the estimation of stress-strength reliability parameter R=P(Y<X) based on complete samples when the stress-strength are two independent Poisson half logistic random variables (PHLD). We have addressed the estimation of R in the general case and when the scale parameter is common. The classical and Bayesian estimation (BE) techniques of R are studied. The maximum likelihood estimator (MLE) and its asymptotic distributions are obtained; an approximate asymptotic confidence interval of R is computed using the asymptotic distribution. The non-parametric percentile bootstrap and student’s bootstrap confidence interval of R are discussed. The Bayes estimators of R are computed using a gamma prior and discussed under various loss functions such as the square error loss function (SEL), absolute error loss function (AEL), linear exponential error loss function (LINEX), generalized entropy error loss function (GEL) and maximum a posteriori (MAP). The Metropolis–Hastings algorithm is used to estimate the posterior distributions of the estimators of R. The highest posterior density (HPD) credible interval is constructed based on the SEL. Monte Carlo simulations are used to numerically analyze the performance of the MLE and Bayes estimators, the results were quite satisfactory based on their mean square error (MSE) and confidence interval. Finally, we used two real data studies to demonstrate the performance of the proposed estimation techniques in practice and to illustrate how PHLD is a good candidate in reliability studies.

scholarly journals Estimation of Stress Strength Reliability of Inverse Weibull Distribution under Progressive First Failure Censoring

2018 ◽  
Vol 48 (1) ◽  
pp. 14-37
Author(s):  
Hare Krishna ◽  
Madhulika Dube ◽  
Renu Garg
Keyword(s):  
Monte Carlo ◽  
Real Life ◽  
Credible Interval ◽  
Estimation Methods ◽  
Posterior Density ◽  
Monte Carlo Simulation Study ◽  
Scale Parameters ◽  
Real Life Data ◽  
Inverse Weibull Distribution ◽  
Highest Posterior Density

In this article, estimation of stress-strength reliability $\delta=P\left(Y<X\right)$ based on progressively first failure censored data from two independent inverse Weibull distributions with different shape and scale parameters is studied. Maximum likelihood estimator and asymptotic confidence interval of $\delta$ are obtained. Bayes estimator of $\delta$ under generalized entropy loss function using non-informative and gamma informative priors is derived. Also, highest posterior density credible interval of $\delta$ is constructed. Markov Chain Monte Carlo (MCMC) technique is used for Bayes computation. The performance of various estimation methods are compared by a Monte Carlo simulation study. Finally, a pair of real life data is analyzed to illustrate the proposed methods of estimation.

scholarly journals Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes

2021 ◽  
Author(s):  
Andreas Fritsche ◽  
Robert Wagner ◽  
Martin Heni ◽  
Kostantinos Kantartzis ◽  
Jürgen Machann ◽  
...  
Keyword(s):  
High Risk ◽  
Lifestyle Intervention ◽  
Low Risk ◽  
Liver Fat ◽  
Liver Fat Content ◽  
Randomized Controlled ◽  
The Difference ◽  
Prevention Of Diabetes

Lifestyle intervention (LI) can prevent type 2 diabetes, but response to LI varies depending on risk subphenotypes. We tested if prediabetic individuals with low risk benefit from conventional LI and individuals with high risk benefit from an intensification of LI in a multi-center randomized controlled intervention over 12 months with 2 years follow up. 1105 prediabetic individuals based on ADA glucose criteria were stratified into a high- and low-risk phenotype, based on previously described thresholds of insulin secretion, insulin sensitivity and liver fat content. Low-risk individuals were randomly assigned to conventional LI according to the DPP protocol or control (1:1), high-risk individuals to conventional or intensified LI with doubling of required exercise (1:1). A total of 908 (82%) participants completed the study. In high-risk individuals, the difference between conventional and intensified LI in post-challenge glucose change was -0.29 mmol/l [CI:-0.54;-0.04], p=0.025. Liver fat (-1.34 percentage points [CI:-2.17;-0.50], p=0.002) and cardiovascular risk (-1.82[CI:-3.13-0.50],p=0.007) underwent larger reductions with intensified than with conventional LI. During a follow up of 3 years, intensified compared to conventional LI had a higher probability to normalize glucose tolerance (p=0.008). In conclusion, it is possible in high-risk individuals with prediabetes to improve glycemic and cardiometabolic outcomes by intensification of LI. Individualized, risk-phenotype-based LI may be beneficial for the prevention of diabetes.

scholarly journals Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes

2021 ◽  
Author(s):  
Andreas Fritsche ◽  
Robert Wagner ◽  
Martin Heni ◽  
Kostantinos Kantartzis ◽  
Jürgen Machann ◽  
...  
Keyword(s):  
High Risk ◽  
Lifestyle Intervention ◽  
Low Risk ◽  
Liver Fat ◽  
Liver Fat Content ◽  
Randomized Controlled ◽  
The Difference ◽  
Prevention Of Diabetes

Lifestyle intervention (LI) can prevent type 2 diabetes, but response to LI varies depending on risk subphenotypes. We tested if prediabetic individuals with low risk benefit from conventional LI and individuals with high risk benefit from an intensification of LI in a multi-center randomized controlled intervention over 12 months with 2 years follow up. 1105 prediabetic individuals based on ADA glucose criteria were stratified into a high- and low-risk phenotype, based on previously described thresholds of insulin secretion, insulin sensitivity and liver fat content. Low-risk individuals were randomly assigned to conventional LI according to the DPP protocol or control (1:1), high-risk individuals to conventional or intensified LI with doubling of required exercise (1:1). A total of 908 (82%) participants completed the study. In high-risk individuals, the difference between conventional and intensified LI in post-challenge glucose change was -0.29 mmol/l [CI:-0.54;-0.04], p=0.025. Liver fat (-1.34 percentage points [CI:-2.17;-0.50], p=0.002) and cardiovascular risk (-1.82[CI:-3.13-0.50],p=0.007) underwent larger reductions with intensified than with conventional LI. During a follow up of 3 years, intensified compared to conventional LI had a higher probability to normalize glucose tolerance (p=0.008). In conclusion, it is possible in high-risk individuals with prediabetes to improve glycemic and cardiometabolic outcomes by intensification of LI. Individualized, risk-phenotype-based LI may be beneficial for the prevention of diabetes.

scholarly journals Comparing Sexual Function between Opioid Dependents Consuming Methadone or Opium Tincture

2021 ◽  
Author(s):  
Sedigheh Sadat Moeeni ◽  
Reza Rastgoo Sisakht ◽  
Nasim Vousooghi ◽  
Koorosh Kamali ◽  
Firoozeh Raisi ◽  
...  
Keyword(s):  
Sexual Function ◽  
Premature Ejaculation ◽  
Methadone Maintenance ◽  
Complex Interaction ◽  
Sex Hormone Binding Globulin ◽  
Total Testosterone ◽  
Related Factors ◽  
Blood Tests ◽  
Anxiety Levels ◽  
The Difference

Objective: Sexual dysfunction is a side effect of methadone maintenance therapy (MMT). Opium Tincture (OT) has been used as a maintenance treatment. This study aimed to determine and compare the trend of sexual function and its related factors during treatment with both drugs. Method: An observational study was designed to measure the blood tests including free and total testosterone, prolactin, and sex hormone-binding globulin and a battery of questionnaires, including demographics and drug use history, in 42 and 53 patients entering MMT and OT treatment before and 1 and 3 months after the treatment. Results: Significant changes in testosterone levels were observed in the MMT but not the OT group. The difference between the two groups was not significant. Neither between nor within changes in the sexual function and premature ejaculation scores were significant (P =0.370& 0.698). Anxiety levels were significantly different (P= 0.001) within and between groups. There was a considerable difference in the trend of depression changes in the OT group, but not different in MMT group and between the two groups. Conclusion: No difference was found between MMT and OT effects on sexual function variables. The decrease in Testosterone during the three months of MMT, was not associated with diminished sexual function. In the MMT group, anxiety levels diminished during treatment. It seems that decreased testosterone in the MMT group was compensated by improved anxiety. Gonadotropin levels may not be the sole determinant in sexual activity, and complex interaction of mood and anxiety, agonist levels, and gonadotropins are involved.

scholarly journals Efeito materno e paterno sobre as taxas de fertilização e eclosão em curimba (Prochilodus lineatus)

2012 ◽  
Vol 64 (6) ◽  
pp. 1584-1590 ◽  
Author(s):  
I.B. Allaman ◽  
R.T.F. Freitas ◽  
A.T.M. Viveiros ◽  
A.F. Nascimento ◽  
G.R. Oliveira ◽  
...  
Keyword(s):  
Posterior Density ◽  
Prochilodus Lineatus ◽  
Highest Posterior Density

Avaliou-se o quanto fêmeas e machos contribuem para a variação total das taxas de fertilização e de eclosão em curimba (Prochilodus lineatus). Utilizou-se sêmen criopreservado proveniente de cinco machos para fertilizar ovócitos de seis fêmeas em um esquema fatorial cruzado 5x6, totalizando 30 famílias. Além das características reprodutivas dos machos e fêmeas, foram avaliadas as taxas de fertilização e eclosão para cômputo dos efeitos materno e paterno. Os componentes da variância foram estimados por meio da máxima verossimilhança restrita, sendo construídos intervalos Highest Posterior Density (HPD) para cada componente. Verificou-se que as fêmeas contribuíram muito mais para a variação total em relação aos machos para as taxas de fertilização e eclosão. Para a taxa de fertilização, as fêmeas contribuíram com 26,3% da variação total e os machos com 8,9%. Em relação à taxa de eclosão, as fêmeas contribuíram com 11,9% e os machos com 1,6%. Concluiu-se que houve efeito materno sobre as taxas de fertilização e eclosão e que o efeito paterno avaliado individualmente foi pouco expressivo ou até mesmo insignificante.

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