Bayesian and non-bayesian inference for logistic-exponential distribution using improved adaptive type-II progressively censored data.

Improved adaptive type-II progressive censoring schemes (IAT-II PCS) are increasingly being used to estimate parameters and reliability characteristics of lifetime distributions, leading to more accurate and reliable estimates. The logistic exponential distribution (LED), a flexible distribution with five hazard rate forms, is employed in several fields, including lifetime, financial, and environmental data. This research aims to enhance the accuracy and reliability estimation capabilities for the logistic exponential distribution under IAT-II PCS. By developing novel statistical inference methods, we can better understand the behavior of failure times, allow for more accurate decision-making, and improve the overall reliability of the model. In this research, we consider both classical and Bayesian techniques. The classical technique involves constructing maximum likelihood estimators of the model parameters and their asymptotic covariance matrix, followed by estimating the distribution's reliability using survival and hazard functions. The delta approach is used to create estimated confidence intervals for the model parameters. In the Bayesian technique, prior information about the LED parameters is used to estimate the posterior distribution of the parameters, which is derived using Bayes' theorem. The model's reliability is determined by computing the posterior predictive distribution of the survival or hazard functions. Extensive simulation studies and real-data applications assess the effectiveness of the proposed methods and evaluate their performance against existing methods.

A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries.

The COVID-19 pandemic has expanded fast over the world, affecting millions of people and generating serious health, social, and economic consequences. All South East Asian countries have experienced the pandemic, with various degrees of intensity and response. As the pandemic progresses, it is important to track and analyse disease trends and patterns to guide public health policy and treatments. In this paper, we carry out a sequential cross-sectional study to produce reliable weekly COVID-19 death (out of cases) rates for South East Asian countries for the calendar years 2020, 2021, and 2022. The main objectives of this study are to characterise the trends and patterns of COVID-19 death rates in South East Asian countries through time, as well as compare COVID-19 rates among countries and regions in South East Asia. Our raw data are (daily) case and death counts acquired from "Our World in Data", which, however, for some countries and time periods, suffer from sparsity (zero or small counts), and therefore require a modelling approach where information is adaptively borrowed from the overall dataset where required. Therefore, a sequential cross-sectional design will be utilised, that will involve examining the data week by week, across all countries. Methodologically, this is achieved through a two-stage random effect shrinkage approach, with estimation facilitated by nonparametric maximum likelihood.

The association between female newborn and placental malaria infection: A case-control study.

INTRODUCTION: There are few published data on the influence of the sex of the fetus or the newborn on the rate of malaria infection. Moreover, the results of these studies are not conclusive. This study was conducted to investigate the association between sex of the newborn and placental malaria infection. METHODS: A case-control study was conducted at Al Jabalian maternity hospital in central Sudan during the rainy and post rainy seasons from May to December 2020. The cases were women who had placental malaria, while the controls were subsequent women who had no placental malaria. A questionnaire was filled out by each woman in the case and control groups in order to gather demographic data as well as medical and obstetric history. Malaria was diagnosed using blood films. Logistic regression analyses were performed. RESULTS: There were 678 women in each arm of the study. Compared with the women without placental malaria (controls), women with placental malaria had a significantly lower age and parity. A significantly higher number of the cases had delivered female newborns, 453 (66.8%) vs. 208 (30.7%), P < 0.001. In logistic regression, women with placental malaria: lived in rural areas, had low antenatal attendance, did not use bed nets, and had more female newborns (adjusted odds ratio, AOR = 2.90, 95% CI = 2.08-4.04). DISCUSSION: Women who delivered female were more likely to have placental malaria. Further research into the immunologic and biochemical parameters is warranted.

Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data.

Tracking the progress of an infectious disease is critical during a pandemic. However, the incubation period, diagnosis, and treatment most often cause uncertainties in the reporting of both cases and deaths, leading in turn to unreliable death rates. Moreover, even if the reported counts were accurate, the "crude" estimates of death rates which simply divide country-wise reported deaths by case numbers may still be poor or even non-computable in the presence of small (or zero) counts. We present a novel methodological contribution which describes the problem of analyzing COVID-19 data by two nested Poisson models: (i) an "upper model" for the cases infected by COVID-19 with an offset of population size, and (ii) a "lower" model for deaths of COVID-19 with the cases infected by COVID-19 as an offset, each equipped with their own random effect. This approach generates robustness in both the numerator as well as the denominator of the estimated death rates to the presence of small or zero counts, by "borrowing" information from other countries in the overall dataset, and guarantees positivity of both the numerator and denominator. The estimation will be carried out through non-parametric maximum likelihood which approximates the random effect distribution through a discrete mixture. An added advantage of this approach is that it allows for the detection of latent subpopulations or subgroups of countries sharing similar behavior in terms of their death rates.

Calcium hydroxide as an intracanal medication for postoperative pain during primary root canal therapy: A systematic review and meta-analysis with trial sequential analysis of randomised controlled trials.

OBJECTIVE: To evaluate the effectiveness of CH as an intracanal medicament compared to no dressing and / or other intracanal medicaments to control postoperative pain in patients with apical periodontitis requiring primary root canal therapy. MATERIALS AND METHODS: We conducted electronic searches in PubMed, EMBASE, Scopus and Cochrane Library, Open Gray, and Google Scholar. A structured Population-Intervention-Comparison-Outcome of the review was as follows: Population: adults who presented with apical periodontitis requiring primary root canal therapy; Intervention: CH intracanal medicament; Comparison: no dressing/other intracanal medicaments; Main Outcome: Postoperative pain. We assessed the risk of bias using Cochrane criteria. Our outcome measures were intensity of pain on a validated scale reported as mean and standard deviation. We performed meta-analysis using the random-effects model. We rated the quality of evidence using GRADE. RESULTS: We included 18 studies with 1192 participants. The overall risk of bias was moderate. We found a significant improvement in postoperative pain at 24 hours in favor of CH over no intracanal medication (4 trials, n = 226: standardised mean difference: -0.71; [95% confidence interval: -1.38, -0.03]; P = .04; I2= 78%; moderate certainty evidence). Ledermix (Lederle Germany) (steroid-antibiotic) and chlorhexidine were significantly more effective than CH for controlling pain at 72 hours postprocedure (low certainty evidence). Silver nanoparticles were more effective than CH at 6 and 24 hours and combinations of CH with dexamethasone or lidocaine HCl were significantly more effective than CH alone at improving postoperative pain. Substantial heterogeneity limits the robustness of findings. CONCLUSION: Limited evidence suggests that CH may be an effective intracanal medicament for controlling interappointment pain. Combination therapies appear to be more effective than using CH alone. Further research assessing the comparative effectiveness of interventions for managing postoperative pain following root canal therapy is warranted.

Some new findings on the survival Rényi entropy and application of COVID-19 data.

Motivated by the connotation of survival Rényi entropy and its related dynamic version, we introduce them in terms of their lower bounds and mean residual life function. Moreover, we illustrate the relation between survival Rényi entropy and some of measures of information. Furthermore, the hazard rate order implies ordering of dynamic survival Rényi entropy. Our models are considered a more comprehensive version of generalized order statistics and give some properties and characterization results. Finally, a non-parametric estimation of survival Rényi entropy is included based on real COVID-19 data and simulated data.