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Using the calibration approach, the Hanson and Hurwitz (1946) technique-based estimator is developed for the situation where the information on auxiliary variable is assumed known for the entire sample units. Expressions for the estimator of population mean/total, its variance, and variance estimator were developed. The theoretical results are illustrated with the help of empirical studies. Empirical results showed that proposed calibration approach-based estimator outperforms the Hansen and Hurwitz technique.

We propose a new modified ratio estimator of population mean of the main variable using the linear combination of known values of Co-efficient of Kurtosis and Tri-Mean of the auxiliary variable. Mean Square Error (MSE) and bias of the proposed estimator is calculated and compared with the existing estimator. The comparison is demonstrated numerically which shows that the proposed estimator performs better than the existing estimators.

A percentile is one of the measures of location used by statisticians showing the value below which a given percentage of observations in a group of observations fall. A family of ratio-cum-product estimators for estimating the finite population mean of the study variable when the finite population mean of two auxiliary variables are known in simple random sampling without replacement (SRSWOR) have been proposed. The main purpose of this study is to develop new ratio-cum-product estimators in order to improve the precision of estimation of population mean in sample random sampling without replacement using information of percentiles with two auxiliary variables. The expressions of the bias and mean square error (MSE) of the proposed estimators were derived by Taylor series method up to first degree of approximation. The efficiency conditions under which the proposed ratio-cum-product estimators are better than sample man, ratio estimator, product estimator and other estimators considered in this study have been established. The numerical and empirical results show that the proposed estimators are more efficient than the sample mean, ratio estimator, product estimator and other existing estimators.

In this paper, we have proposed three classes of almost unbiased estimators for population mean under simultaneous presence of measurement and non-response error. Asymptotic properties such as Bias...

Recently Pal et al. introduced a mean estimator which generalized most of the known mean estimators. We introduce a class of estimators that performs better than Pal et al. estimator. Expressions f...

This paper introduces an innovative and optimal randomized response model by making use of correlated scrambling variables for estimating the population mean of a sensitive variable. The resultant ...

The use of auxiliary variable is common at estimation stage in the form of ratio and product type estimators. All such estimators use the current sample information to estimate the population chara...

Researchers always appreciates estimators of finite population quantities, especially mean, with maximum efficiency for reaching to valid statistical inference. Apart from ratio, product and regression estimators, exponential estimators are widely considered by survey statisticians. Motivated from the idea of exponential type estimators, in this article, we propose some new estimators utilizing known median of the study variable with mean of auxiliary variable. Theoretical properties of the suggested estimators are studied up to first order of approximation. In addition, an empirical and simulation study the comparison of median based proposed class of estimators with sample mean, ratio and linear regression estimators are discussed. The results expose that the proposed estimators are more efficient than the existing estimators.

In this paper we propose a class of estimators for the estimation of finitepopulation mean using the auxiliary information when SRS scheme is used. Theexpressions for the Bias and mean square error (MSE) of the existing andsuggested class of estimators are derived up to first degree of approximation andthe efficiency comparison of suggested class of estimators is made with otherexisting estimators, using both theoretically and numerically based on realpopulation sets.

This study is designed for predictive estimation of finite population mean in two phase sampling using two auxiliary variables. Two phase exponential ratio type estimator and exponential chain ratio type estimator are proposed under predictive approach suggested by Bahl & Tuteja (1991). The expressions of bias and mean square error of both suggested estimators have been carried out for theoretical comparison. The numerical study on real life data sets as well as simulation study has been conducted to examine the performance of suggested estimators. Finally, it is demonstrated that the suggested exponential ratio estimators are more efficient than competitive estimators in support of numerical and simulation study as well.

In this study, the hypothesis test for the population mean of inverse Gaussian distribution using ranked set sampling is considered when the scale parameter is both known and unknown. In order to o...

This paper considers the problem of estimating the population mean under double sampling. We have suggested the generalized class of estimators under Lahiri (1951) to Midzuno (1952) and Sen (1952) type sampling scheme and its properties are studied up to the first order of approximation. Further, we compare the proposed sampling strategy with some conventional estimators under the simple random sampling without replacement. On the basis of suitable range information, we give some concluding remarks related to propose sampling strategy. An empirical study is given in support of the present study.

In this article, modified difference-type estimator for the population mean in two-phase sampling scheme using two auxiliary variables has been proposed. The mean squared error of the proposed estimator has also been derived using large sample approximation. The efficiency comparison conditions for the proposed estimator in comparison with other existing estimators in which the proposed estimator performed better than the other relevant existing estimators have been given.

In this article, we propose an exponential estimator in the stratified random sampling taking an auxiliary attribute. Expressions for MSE of the proposed estimators are derived up to first order of...

The present paper provides a remedy for improved estimation of population mean of a study variable, using the information related to an auxiliary variable in the situations under Simple Random Sampling Scheme. We suggest a new class of estimators of population mean and the Bias and MSE of the class are derived upto the first order of approximation. The least value of the MSE for the suggested class of estimators is also obtained for the optimum value of the characterizing scaler. The MSE has also been compared with the considered existing competing estimators both theoretically and empirically. The theoretical conditions for the increased efficiency of the proposed class, compared to the competing estimators, is verified using a natural population.

Background Extended hospital length of stay (LOS) is widely associated with significant healthcare costs. Since LOS is a known surrogate for cost, we sought to evaluate outliers. We hypothesized that particular characteristics are likely predictive of trauma high resource consumers (THRC) and can be used to more effectively manage care of this population. Methods The Pennsylvania Trauma Outcome Study database was retrospectively queried from 2003-2017 for all adult (age ≥15) trauma patients admitted to accredited trauma centers in Pennsylvania. THRC were defined as patients with hospital LOS two standard deviations above the population mean or ≥22 days (pResults A total of 465,601 patients met inclusion criteria [THRC: 16,818 (3.6%); non-THRC 448,783 (96.4%)]. Compared to non-THRC counterparts, THRC patients were significantly more severely injured (median ISS: 9 vs. 22, pConclusions Reintubation, major surgery, gunshot wound to abdomen, along with injury to the spine, upper or lower extremities are all strongly predictive of THRC. Understanding the profile of the THRC will allow clinicians and case management to proactively put processes in place to streamline care and potentially reduce costs and LOS.

Ranked Set Sampling is an efficient technique when it is difficult to measure sampling units in respect to cost or time. Although this technique can be used for every sample sizes, the small sample sizes are preferred for better ranking. However, when the sample sizes are small, it is very difficult to obtain distribution of the statistic for the statistical inference such as hypothesis test. In this case, resampling techniques like bootstrap can be used to construct pseudo distribution of the statistics. In this study, the bootstrap methods for hypothesis test about population mean under ranked set sampling is given. A simulation study is also performed to examine the performance of these methods., Sıralı küme örneklemesi, örnekleme birimlerini ölçmenin maliyet ve zaman bakımından zor olduğu durumda kullanılan etkin bir örnekleme tekniğidir. Bu teknik, her çapta örnek için kullanılabilir olmasına rağmen sıralama hatasını minimuma indirmek için küçük örnek çaplarında daha çok tercih edilir. Ancak, hipotez testi gibi istatistiksel çıkarsama yaparken küçük örnek çapı durumunda, istatistiğin kesin ya da asimptotik dağılımını elde etmek oldukça zordur. Bu durumda, istatistiğin yapay dağılımını elde etmek için Bootstrap gibi yeniden örnekleme teknikleri kullanılabilir. Bu çalışmada, sıralı küme örneklemesi altında yığın ortalamasına ilişkin hipotez testi için Bootstrap metotları verilmiştir. Ayrıca, verilen metotların performansını değerlendirmek için simülasyon çalışması yapılmıştır.

In this article, we propose a parent-generalized family of chain exponential ratio type estimators in stratified random sampling to estimate the finite population mean using known information on tw...

In this paper, three robust confidence intervals are proposed as alternatives to the Student t confidence interval. The performance of these intervals was compared through a simulation study shows that Qn-t confidence interval performs the best and it is as good as Student’s t confidence interval. Real-life data was used for illustration and performing a comparison that support the findings obtained from the simulation study.

In this paper, we have proposed a family of combined-type estimators of the population mean in stratified random sampling using the information on an auxiliary variable under the situation in which...

Intervening when bird nestlings are performing poorly relative to the population mean may be a management priority if individuals are of high-conservation value. Assessing body condition may enable...

In this paper, we present an efficient quartile paired double ranked set sampling (QPDRSS) scheme to estimate the population mean. QPDRSS provides an unbiased improved population mean estimator when the distribution is symmetric and bears negligible biasness for non-symmetric distribution. The performance of the proposed mean estimator is compared to its competitors in simple random sampling, double ranked set sampling, extreme paired double ranked set sampling and paired double ranked set sampling by manipulating simulation process for various (symmetric and non-symmetric) distributions. A real dataset is also studied to exemplify the achievement of the proposal.

In this article, a new estimator for population mean in two-phase stratified sampling in the presence of nonresponse using single auxiliary variable has been proposed. The bias and Mean Squared Error (MSE) of the proposed estimator has been given using large sample approximation. The empirical study shows that the MSE of the proposed estimator is more efficient than existing estimators. The optimum values of first and second phase sample have been determined.

In this article, we show that the log empirical likelihood ratio statistic for the population mean vector converges in distribution to χ(q)2 as n→∞ when the population is in the domain of attractio...

It is a common approach to adopt the statistical measures of the auxiliary variable such as correlation, coefficient of variation etc. for estimating the population mean. In this paper we propose novel estimators by adding an exponential parameter on the auxiliary variable. Theoretically, we obtain the mean square error (MSE) for all proposed estimators and we compare MSE equations of our proposed estimators and classical estimators. As a result of these comparisons, we observe that proposed estimators are always more efficient than classical estimators. These theoretical results are supported with the aid of a numerical and simulation examples.

This study proposes a new class of exponential-type estimators in simple random sampling for the estimation of the population mean of the study variable using information of the population proportion possessing certain attributes. Theoretically, mean squared error (MSE) equations of the suggested ratio exponential estimators are obtained and compared with the Naik and Gupta (1996) ratio and product estimators, the ratio and product exponential estimator presented in Singh et al. (2007) and the ratio exponential estimators presented in Zaman and Kadilar (2019a). As a result of these comparisons, it is observed that the proposed estimators always produce more efficient results than the others. In addition, these theoretical results are supported by the application of original datasets.

Estimation of sensitive issues is an adversely challenging task as it is highly influenced by social desirability bias leading to untrue response many times. Hence, the possible way out for these p...

Recently, Irfan et al. developed ratio-type estimators for population mean estimation with simple random sampling (SRS) scheme, based on known median of a study variable and an auxiliary (supplemen...

Prompted by a cluster of observations concerning ascending aortic pathology in elite rugby players, we assessed over 150 asymptomatic predominantly retired players with echocardiography, aiming to document the prevalence and severity of ascending aortic dilatation and/or anterior aortic effacement, both 'risk factors' for potentially catastrophic aortic complications.Rugby players (at least 5 years of high level competitive rugby) were classified as elite (national, state or first grade representatives) or non-elite. A total of 152 asymptomatic players with a mean age of 45 ± 13 years (range 21-65) underwent transthoracic echocardiography. Z-scores (number of standard deviations from a population mean) were calculated for aortic root and ascending aortic size.Regarding the aortic root, a Z-score of2 was seen in 24% (expected prevalence 2.3%, p 0.001) and a Z-score3 was seen in 4% (expected prevalence 0..1%, p 0.001). Sixty-two (62) players (41%) had an aortic root greater than 40 mm diameter. Ascending aortic Z-scores were2 in 53% of players and3 in 22% (p 0.001). Abnormal anterior aortic effacement at the sinotubular junction (STJ) was seen in 88 players (58%). Abnormal aortic dilatation and effacement were associated with a longer duration of competitive rugby participation and elite status, respectively.Ascending aortic dilatation with abnormal anterior effacement is exceedingly common in asymptomatic retired elite rugby players. This warrants increased surveillance in retired players until the clinical significance of these findings can be further investigated.

The crux of this study is to propose some modified and improved compromised imputation methods and their corresponding point estimators to estimate the population mean using information on an auxil...

In this paper, single-phase mixture regression cum ratio estimators are presented by utilizing auxiliary variables and auxiliary attributes simultaneously under stratified random sampling. Special ...

This article studies interval estimation of the population mean in ranked set sampling. Eight types of confidence intervals are considered which are based on asymptotic theory, resampling methods, ...

Recently, Haq et al. [A new estimator of finite population mean based on the dual use of the auxiliary information. Commun Stat Theory Methods. 2017;46(9):4425–4436] utilized the dual auxiliary information under simple random sampling only. Motivated by their idea, we initiated the dual use of auxiliary variable under a stratified random sampling scheme. Dual use of auxiliary variable consists: (1) the original auxiliary information and (2) the ranked auxiliary information. We proposed new optimal exponential-type estimators for the estimation of the finite population mean. Mathematical properties such as bias and mean squared error of the proposed estimators are derived. Monte Carlo simulation studies are included to successfully validate the theoretical results. Moreover, the applicability of the proposed estimators is highlighted through empirical interpretation with the help of a real-life data set. It is clearly identified from the numerical results that our proposed estimators are more efficient over the competitors.

Journal of Applied Research on Science and Technology (JARST), 21, 1, 55-64

In this chapter, the authors develop stratified ranked set sampling (RSS) under missing observations. Imputation based of ratio rules is used for completing the information for estimating the mean. They introduce the needed elements on imputation and on the sample selection procedures. They extend RSS models to imputation in stratified populations. A theory on ratio-based imputation rules for estimating the mean is presented. Some numerical studies, based on real-world problems, are developed for illustrating the behaviour of the accuracy of the estimators due to their proposals.

Improved chain-ratio estimators for the population mean based on two-phase sampling are proposed when the study variable and two auxiliary variables comprise non-response. Auxiliary information is ...

Author(s): Schnapp, Benjamin H.; Fleming, Emily; Kraut, Aaron; Westergaard, Mary; Batt, Robert J.; Patterson, Brian W. | Abstract: Introduction: Emergency physicians encounter scenarios daily that many would consider “disgusting,” including exposure to blood, pus, and stool. Physicians in procedural specialties such as surgery and emergency medicine (EM) have lower disgust sensitivity overall, but the role this plays in clinical practice is unclear. The objective of this study was to determine whether emergency physicians with higher disgust sensitivity see fewer “disgusting” cases during training.Methods: All EM residents at a midsize urban EM program were eligible to complete the Disgust Scale Revised (DS-R). We preidentified cases as “disgust elicitors” based on diagnoses likely to induce disgust due to physician exposure to bodily fluids, anogenital anatomy, or gross deformity. The “disgust elicitor” case percent was determined by “disgust elicitor” cases seen as the primary resident divided by the number of cases seen thus far in residency. We calculated Pearson’s r, t-tests and descriptive statistics on resident and population DS-R scores and “disgust elicitor” casesper month.Results: Mean DS-R for EM residents (n = 40) was 1.20 (standard deviation [SD] 1.24), significantly less than the population mean of 1.67 (SD 0.61, pl0.05). There was no correlation (r = -0.04) between “disgust elicitor” case (n = 2191) percent and DS-R scores. There was no significant difference between DS-R scores for junior residents (31.1, 95% confidence interval [CI], 26.8-35.4) and for senior residents (29.0, 95% CI, 23.4-34.6).Conclusion: Higher disgust sensitivity does not appear to be correlated with a lower percentage of “disgust elicitor” cases seen during EM residency.

BULUT, Hasan/0000-0002-6924-9651 WOS: 000501104500001 In this article, ratio estimators for the population mean have suggested using the robust covariance estimation under the simple random scheme. Zaman and Bulut have developed a class of ratio-type estimators for the mean estimation by utilizing robust regression coefficients. In this paper, we extend the estimators presented in Zaman and Bulut by using minimum covariance determinant (MCD) robust covariance estimation. The mean square error (MSE) equation for the new estimators is obtained. These theoretical results are supported with the aid of numerical example and simulation based on dataset that include outliers.

In this scripture, we ponder the problem of efficient estimation of population mean of study variable utilizing information on highly correlated auxiliary variables under the presence of non-response on either of the variables. For this purpose, we suggest, an improved estimator under three different situations of non-response. Under the first situation, estimation of population mean is done with the problem of non-response on both the study and the auxiliary variables with the additional condition that the population means of the auxiliary variables are known. The second situation is to estimate the population mean of primary variable when the problem of non-response is only on the primary variable but the population means of the auxiliary variables are known while under the third situation estimation is performed with the problem of non-response on both the study and the auxiliary variables but population mean of one of the auxiliary variables is unknown. We study the sampling properties of the suggested estimator under above three different situations of non-response. We compare the proposed estimator with the competing estimators of population mean, under three different situations of non-response. The efficiency conditions are obtained for all three situations. A numerical study is also carried out to verify the efficiency conditions.