Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.

Gupta et al. suggested an improved estimator by using the Diana and Perri model in estimating the finite population variance using the single auxiliary variable. On the same lines, Saleem et al.

On the development of survey methods for novel mean imputation and its application to abalone data.

Non-response in surveys is a common problem faced by surveyors, this results in missing data. Missing values are often omitted when doing any statistical analysis, but this reduces the sample size and consequently decreases the precision of estimates. In such situations, imputation is a commonly used method to deal with missing data, this involves estimating the missing values based on the observed data.

Estimating neutrosophic finite median employing robust measures of the auxiliary variable.

Our study explores neutrosophic statistics, an extension of classical and fuzzy statistics, to address the challenges of data uncertainty. By leveraging accurate measurements of an auxiliary variable, we can derive precise estimates for the unknown population median. The estimators introduced in this research are particularly useful for analysing unclear, vague data or within the neutrosophic realm.

Ileorectal anastomosis in ulcerative colitis: what do surgeons and patients need to know? A systematic literature review.

Introduction: Ileal pouch-anal anastomosis (IPAA) is currently the gold standard for restoration of gastrointestinal continuity after colectomy for ulcerative colitis in the UK. However, with further experience of the risks relating to IPAA, the use of ileorectal anastomosis (IRA) is being revisited. Decisions regarding restorative surgery after colectomy are individual to every patient's circumstances, and this paper aims to provide a comprehensive review of the literature to guide a full discussion of the risks and benefits of IRA.

Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming.

Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers.

An improved class of estimators for estimation of population distribution functions under stratified random sampling.

The main objective of the current study is to suggest an enhanced family of log ratio-exponential type estimators for population distribution function (DF) using auxiliary information under stratified random sampling. Putting different choices in our suggested generalized class of estimators, we found some Specific estimators. The bias and MSE expressions of the estimators have been approximated up to the first order.

Adjustment of model misspecification in estimation of population total under ranked set sampling through balancing.

In the model-based approach, researchers assume that the underlying structure, which generates the population of interest, is correctly specified. However, when the working model differs from the underlying true population model, the estimation process becomes quite unreliable due to misspecification bias. Selecting a sample by applying the balancing conditions on some functions of the covariates can reduce such bias.

Gastroblastoma with a novel ACTB::GLI1 gene fusion in a 19-year-old male.

Gastroblastoma is a rare gastric biphasic tumor composed of mesenchymal and epithelial elements in variable proportions. These tumors usually arise in the gastric antrum of children and young adults and are reported to harbor a recurrent MALAT1::GLI1 fusion. Herein we report a case of gastroblastoma in a 19-year-old male who presented with intermittent epigastric abdominal discomfort.

A novel approach for estimating fertility rates in finite populations using count regression models.

Demographic health surveys (DHS) contain in-depth information about the demographic characteristics and the factors affecting them. However, fertility rates which are the important indicators of population growth have been estimated by utilizing the design-based approaches. Model-based approach, on the other hand, facilitates efficient predictive estimates for these rates by utilizing the demographic and other family planning related characters.

An enhanced estimator of finite population variance using two auxiliary variables under simple random sampling.

In this article, we have suggested a new improved estimator for estimation of finite population variance under simple random sampling. We use two auxiliary variables to improve the efficiency of estimator. The numerical expressions for the bias and mean square error are derived up to the first order approximation.

A comparative study of randomized response techniques using separate and combined metrics of efficiency and privacy.

In social surveys, the randomized response technique can be considered a popular method for collecting reliable information on sensitive variables. Over the past few decades, it has been a common practice that survey researchers develop new randomized response techniques and show their improvement over previous models. In majority of the available research studies, the authors tend to report only those findings which are favorable to their proposed models.

New generalized class of estimators for estimation of finite population mean based on probability proportional to size sampling using two auxiliary variables: A simulation study.

This article aims to suggest a new generalized class of estimators based on probability proportional to size sampling using two auxiliary variables. The numerical expressions for the bias and mean squared error (MSE) are derived up to the first order of approximation. Four actual data sets are used to examine the performances of a new improved generalized class of estimators.

Viewing of clinical cases on social media by dentists: A cause of motivation or dissatisfaction?

Objective: To evaluate the thoughts and feelings of dentists viewing posted clinical cases (PCCs) on various social media (SM) platforms.

Methods: A questionnaire was developed, validated and its reliability was established. It was distributed (in 2022) to 355 dentists who had graduated at least 2 years prior.

The optimal control chart selection for monitoring COVID-19 phases: a case study of daily deaths in the USA.

Epidemiologists frequently adopt statistical process control tools, like control charts, to detect changes in the incidence or prevalence of a specific disease in real time, thereby protecting against outbreaks and emergent health concerns. Control charts have proven essential in instantly identifying fluctuations in infection rates, spotting emerging patterns, and enabling timely reaction measures in the context of COVID-19 monitoring. This study aims to review and select an optimal control chart in epidemiology to monitor variations in COVID-19 deaths and understand pandemic mortality patterns.

A simulation study: An enhanced generalized class of estimators for estimation of population proportion using twofold auxiliary attribute.

The article introduces a novel class of estimators designed for estimating finite population proportions. These estimators utilize dual auxiliary attributes and are applicable under simple random sampling. The proposed class of estimators includes various members with distinct characteristics.

Improved family of estimators for the population mean using supplementary variables under PPS sampling.

In this article, we suggest an enhanced family of estimators for estimation of population mean employing the supplementary variables under probability proportional to size sampling. Up to the first order of approximation, numerical formulations of the bias and mean square error of estimators are obtained. From our suggested improved family of estimators, we give sixteen different members.

A new improved generalized class of estimators for population distribution function using auxiliary variable under simple random sampling.

This article aims to suggest a new improved generalized class of estimators for finite population distribution function of the study and the auxiliary variables as well as mean of the usual auxiliary variable under simple random sampling. The numerical expressions for the bias and mean squared error (MSE) are derived up to first degree of approximation. From our generalized class of estimators, we obtained two improved estimators.

Effect of Propolis on Root Dentine Microhardness When Used as an Intracanal Medicament: An In Vitro Study.

Application of intracanal medicaments may affect the physical properties of root dentine. Calcium hydroxide (CH), a gold standard intracanal medicament, has proven to decrease root dentine microhardness. A natural extract, propolis, has been shown to be superior to CH in eradicating endodontic microbes, but its effect on the microhardness of root dentine is still not known.

Antimicrobial Efficacy of Silver Diamine Fluoride against : A Systematic Review of Studies.

. has been implicated in infections of treated root canals. Current irrigants and intracanal medicaments cannot eliminate completely from the root canal.

An efficient class of estimators for finite population mean in the presence of non-response under ranked set sampling (RSS).

In this study, we address the problem of estimating the finite population mean when the non-response occurs on the characteristics under study. We propose a class of Rao-regression type estimators when ranked set sampling (RSS) procedure is used to collect the data from non-response group only and from both, the response and non-response groups. The information provided on the auxiliary variable is used at both stages i.

A simulation study: Using dual ancillary variable to estimate population mean under stratified random sampling.

In this paper, we propose an improved ratio-in-regression type estimator for the finite population mean under stratified random sampling, by using the ancillary varaible as well as rank of the ancillary varaible. Expressions of the bias and mean square error of the estimators are derived up to the first order of approximation. The present work focused on proper use of the ancillary variable, and it was discussed how ancillary variable can improve the precision of the estimates.

A simulation study: Improved ratio-in-regression type variance estimator based on dual use of auxiliary variable under simple random sampling.

In this article, we proposed an improved finite population variance estimator based on simple random sampling using dual auxiliary information. Mathematical expressions of the proposed and existing estimators are obtained up to the first order of approximation. Two real data sets are used to examine the performances of a new improved proposed estimator.