Achieving equal probability of selection under various random sampling strategies.

The purpose of writing this book is to suggest some improved estimators using auxiliary information in sampling schemes like simple random sampling, systematic sampling and stratified random sampling. This volume is a collection of five papers, written by nine co-authors (listed in the order of the papers): Rajesh Singh, Mukesh Kumar, Manoj Kr. Chaudhary, Cem Kadilar, Prayas Sharma, Florentin Smarandache, Anil Prajapati, Hemant Verma, and Viplav Kr. Singh. In first paper dual to ratio-cum-product estimator is suggested and its properties are studied. In second paper an exponential ratio-product type estimator in stratified random sampling is proposed and its properties are studied under second order approximation. In third paper some estimators are proposed in two-phase sampling and their properties are studied in the presence of non-response. In fourth chapter a family of median based estimator is proposed in simple random sampling. In fifth paper some difference type estimators are suggested in simple random sampling and stratified random sampling and their properties are studied in presence of measurement error.

This study aimed to examine the relationship between dimensions of corporate social responsibility (CSR) practices and intrinsic job motivation of employees in one of the banking companies in Malaysia. The study utilised CSR framework by Bursa Malaysia with localised CSR best practices dimensions developed by Mohd Hasan (2013). Multistage sampling was employed in this study, whereby simple random sampling and cluster sampling were employed. A survey method was used in this study, whereby questionnaires were distributed to 110 bank staff (managerial and non-managerial), but with 37 valid responses received. A set of self-administered questionnaires was used as the instrument for the data collection. The data was then analysed using Spearman’s rho correlation test through the SPSS version 22.0. Based on the findings, all the dimensions namely; workplace, environment, community, and marketplace have a positive and moderate relationship with internal job motivation. Limitations of the study, implications of the findings, and suggestions for future study are also discussed.

This article proposes two improved family of estimators for estimating the finite population mean in simple random sampling (SRS) and stratified random sampling (S t RS). The proposed estimators always perform better than a family of ratio estimators suggested by Khoshnevisan et al. (2007) in SRS and Koyuncu and Kadilar (2009a) in S t RS. They also perform better than the ratio estimator given by Gupta and Shabbir (2008) in SRS and Koyuncu and Kadilar (2010) and Shabbir and Gupta (2011) in S t RS. The expressions for bias and mean squared error (MSE) of considered estimators are obtained. The results are illustrated by real data sets.

This paper modifies the Bahl and Tuteja exponential ratio-type estimator for population median under simple random and stratified sampling schemes using calibration weight adjustment technique with supplementary information to vary the stratum weights. The bias and mean square error of the modified estimator were obtained up to the second-order approximation, which satisfies the necessary conditions for efficiency. The findings show that the new estimator surpasses existing estimators in efficiency gain. This suggests the appropriateness of calibration weight modification in boosting the efficiency of a population parameter estimator under stratified random sampling especially where the population parameter of the auxiliary variable is known and correlate with the variable of interest.

Objective To estimate the prevalence of psoriasis in resident population in Hainan province through a large-scale,multi-center epidemiological survey.Methods Ten small towns or communities were selected from each of 18 cities or counties in Hainan province as survey sites.Multi-stage sampling strategies (including stratified sampling,simple random sampling and cluster sampling) were used in this study.After respondents signed an informed consent form,investigators completed a registration form containing information regarding clinical features of psoriasis,environmental factors,character trait,aggravating factors,trauma history,infection history,etc.Statistical analysis was carried out by the EpiData 3.1 and SPSS 17.0 software.Results This study recruited 35 314 subjects,and 30 935 responded with a return rate of 87.60％.The ratio of man to women was 1.2 ∶ 1,with an average age of (33.86 ± 17.78) years.Forty-six cases of psoriasis were confirmed in these respondents.The overall and standardized prevalence rate of psoriasis was 1.49‰ and 1.42‰ respectively.A significant increase was observed in the standardized prevalence rate of psoriasis in males compared with females (1.85‰ vs.0.84‰,x2 =6.86,P ＜ 0.01).The average age of onset was (33.49 ± 14.61) years,and the most common clinical type was psoriasis vulgaris (82.60％,38/46).Anxiety was the risk factor of psoriasis.The impact of psoriasis on the quality of life included barriers to social (89.13％) and physical activity (73.91％) as well as psychological disorders (86.97％).Conclusions The prevalence rate of psoriasis in resident population in Hainan province is lower than the national average level in China.It seems that multiple factors are implicated in the initiation and progression of psoriasis. Key words: Psoriasis; Epidemiology; Hainan

Random sampling and reconstruction of concentrated signals in a reproducing kernel space

Introduction: Infrastructure is critical to healthcare delivery, and while financing via the National Health Insurance Authority (NHIA) advances UHC through better service access, its underfunding- marked by high out-of-pocket expenses, low capitation, quarterly deficits, and HMO inefficiencies yields minimal perceived infrastructural progress in FCT facilities. Objectives: This study intends to investigate the perceived impact of the National Health Insurance Authority on infrastructural development in selected healthcare facilities in Federal Capital Territory. Method: A cluster sampling technique was employed to select 30 healthcare facilities from the 152 NHIA- accredited facilities in the FCT. The selection of facilities was conducted through simple random procedures, thereby giving all accredited facilities—public, private, and public-private—an equal probability of selection. This process resulted in a sample comprising 4 public, 25 private, and 1 public-private facility. Following the selection of clusters (facilities), proportionate sampling was applied to choose the respondent. Cochran’s formula was used to determine the required sample size, and an equal allocation of 12 respondents per facility was adopted to ensure consistency across clusters. This produced a total sample size of 360 respondents across the 30 selected healthcare facilities. Data was collected from healthcare workers in the facilities using a structured questionnaire. The five-section questionnaire included two self-developed sections capturing healthcare workers’ demographics and facility infrastructure, while sections adapted from Hassan (2022) assessed the NHIA’s impact on service delivery, enrollee access, and infrastructure, as well as barriers to fund use and implementation. Responses were measured using a four-point Likert scale ranging from strongly agree to strongly disagree. The questionnaires were analyzed using Statistical Package for Social Science (SPSS), and descriptive statistics was used to summarize the qualitative data using proportions and frequencies, ordinal regression analysis was employed to test the hypotheses Result: The study found that 58.6% of health workers perceive that the NHIA has no impact on infrastructure development in healthcare facilities, while 68.6% believe it positively influences healthcare delivery services. Despite this, 84.1% of participants report deficits after quarterly payments. Additionally, 75.6% of healthcare workers face barriers in utilizing funds, and 76.4% report challenges in implementing NHIA. Major obstacles include low capitation, fee-for-service issues, and HMO inefficiencies, as reported by 63.4% and 56.3% of healthcare workers. Conclusion: The study shows that while the National Health Insurance Authority (NHIA) has improved access to basic healthcare services and increased enrollee participation, due to an extensive implementation of the Basic Minimum Package of Health Services, including a robust benefit package, its impact on facility infrastructure and operational efficiency remains limited because providers barely have any funds left to maintain or upgrade infrastructure. Variability in model fit suggests that barriers to implementation differ across facility types, with public and private providers both constrained by delayed payments, low tariffs, and administrative inefficiencies.

ABSTRACTIn this paper, single-phase mixture regression cum ratio estimators are presented by utilizing auxiliary variables and auxiliary attributes simultaneously under stratified random sampling. Special cases of these estimators are discussed and further mean square errors are extracted mathematically. Also, to observe the properties of proposed estimators, simulation technique is used which shows that the distribution of the proposed estimators is approximately normal. To differentiate the performance of the proposed estimators, an empirical study has been conducted by incorporating quantitative and qualitative characteristics in the form of auxiliary attributes and variables simultaneously. Comparisons are made with single-phase mixture regression cum ratio estimators under simple random sampling. It has been found that the mixture regression cum ratio estimators employing multiple auxiliary variables and attributes, simultaneously, under stratified random sampling are more efficient than mixture regression cum ratio estimator under simple random sampling.

This paper deals with estimation of population median in simple and stratified random samplings by using auxiliary information. Auxiliary information is rarely used in estimating population median, although there have been many studies to estimate population mean using auxiliary information. In this study, we suggest some estimators using auxiliary information such as mode and range of an auxiliary variable and correlation coefficient. We also expand these estimators to stratified random sampling for combined and separate estimators. We obtain mean square error equations for all proposed estimators and find theoretical conditions. These conditions are also supported by using numerical examples.

Even though chemistry is the foundation and gatekeeper of other science courses, high school students across continue to score poorly in the subject overall. The purpose of the study was to determine how the performance of learners in chemistry was related to the availability of chemistry lab materials. Kilifi North Constituency was the site of the study. Six mixed schools were chosen using simple random sampling, one school for girls and boys were chosen using purposive method. Eighty students were chosen using simple random selection and stratified random sampling. Eight chemistry teachers were sampled using basic random sampling and purposeful sampling. The Chemistry Teacher Questionnaire (CTQ), Student Questionnaire (SQ), Observation Checklist (OC), and document and mark sheet analysis were used to gather data. Ten students and two teachers participated in the pilot project which was conducted at two schools in the Kilifi North Constituency. Data analysis was made simplified with the use of the Statistical Package for Social Sciences (SPSS). The study variables were presented using descriptive statistics such as frequency tables, mean, and percentages. Hypotheses at .05. were tested using inferential statistics (Spearman's Rank order correlation and Pearson product moment of correlation coefficient). The study revealed that 75% of schools had laboratories, with a significant correlation (r = 0.819, p = 0.013) between the availability of laboratory materials and students' academic performance in chemistry practical’s, accounting for 67.08% of the variability in scores. Additionally, the majority of chemistry apparatus and chemicals were deemed sufficiently available, indicating overall adequacy in laboratory resources for effective teaching and learning. The study recommended that Schools should improve laboratory facilities by assuring the availability of necessary equipment and chemicals, as well as offering teacher training, in order to maximize resource efficiency and increase student chemistry performance.

This chapter describes the ideas that are needed to devise an intelligent sampling plan. Topics include: defining the objectives, identifying the sampling units, sample size determination and stratification. Concepts of good sampling practice are described in detail. Some of the common sampling methods are discussed, which include: simple random sampling, stratified random sampling, cluster sampling, and adaptive sampling.

In this article, we propose an exponential ratio type estimator for estimating the finite population mean in simple and stratified random sampling. The properties of the proposed estimator are obtained and comparison is made with some of the existing estimators. The proposed estimator is found to perform better than the usual mean, ratio, exponential ratio, traditional regression and Pandy (1980) estimators in simple and stratified random sampling. We use six data sets for simple random sampling case and two data sets for stratified random sampling case to compare the performances of all of the estimators considered here.

The birth-death process is widely used in phylogenetics to model speciation and extinction. Recent studies have shown that the inferred rates are sensitive to assumptions about the sampling probability of lineages. Here, we examine the effect of the method used to sample lineages. Whereas previous studies have assumed random sampling (RS), we consider two extreme cases of biased sampling: "diversified sampling" (DS), where tips are selected to maximize diversity and "cluster sampling (CS)," where sample diversity is minimized. DS appears to be standard practice, for example, in analyses of higher taxa, whereas CS may occur under special circumstances, for example, in studies of geographically defined floras or faunas. Using both simulations and analyses of empirical data, we show that inferred rates may be heavily biased if the sampling strategy is not modeled correctly. In particular, when a diversified sample is treated as if it were a random or complete sample, the extinction rate is severely underestimated, often close to 0. Such dramatic errors may lead to serious consequences, for example, if estimated rates are used in assessing the vulnerability of threatened species to extinction. Using Bayesian model testing across 18 empirical data sets, we show that DS is commonly a better fit to the data than complete, random, or cluster sampling (CS). Inappropriate modeling of the sampling method may at least partly explain anomalous results that have previously been attributed to variation over time in birth and death rates.

The study determined the impact of dress code on the academic performance of Undergraduate students in Federal University of Agriculture, Makurdi. Two research questions and one hypothesis respectively guided the study. The study adopts survey research design and was conducted in Federal University of Agriculture, Makurdi. The population of this study was 7,261 respondents made up of 5,661 undergraduate students, 430 academic and 1170 non-academic staff of Federal University of Agriculture, Makurdi. A sample of 379 respondents made up of 295 undergraduate students and 84 staff of Federal University of Agriculture, Makurdi was determined using Taro Yamane formular for a finite population and used in the study. Multistage sampling technique of proportionate stratified and simple random sampling techniques was employed for sample selection. The instrument used for data collection was a structured questionnaire titled: Impact of Dress Code on Academic Performance Questionnaire (IDCAPQ) developed by the researchers from literature reviewed. The IDCAPQ was subjected to face and content validity by three experts and trial tested on 30 respondents from federal university Lafia, Nasarawa State. Cronbach Alpha method of reliability was used to determine the internal consistency of the IDCAPQ which yielded a reliability coefficient of .71. The instrument (IDCAPQ) was used for data collection and data collected for the study was analyzed using mean to answer research questions and chi-square statistics to test the null hypothesis at 0.05 level of significance. The findings of the study revealed that there are eight causes of indecent dressing amongst undergraduate students of Federal University of Agriculture, Makurdi, there are six ways in which indecent dressing affects the academic performance of undergraduate students in Federal University of Agriculture, Makurdi and that indecent dressing significantly impact academic performance of undergraduate students in University of Agriculture, Makurdi. Based on the findings it was recommended amongst others that the Guidance and Counseling Unit of the school should educate students on the dangers of indecent dressing and its possible effects on their students. Article visualizations:

<p>Although not as efficient as simple random sampling, cluster sampling has been regarded as a<br /> valid sampling technique when the researcher is attempting to save cost. In order to do so, it is<br /> necessary that random selection occurs in all stages of sampling. This simulation study<br /> examines purposeful selection of cluster sampling in the second stage of a two stage cluster<br /> design.</p>