Narendra Singh Thakur

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This paper presents an imputation based factor-type class of estimation strategy for estimating population mean in presence of missing values of auxiliary variable. The non-sampled part of population is used as an imputation technique in the form of a proposed class of estimators. The bias and mean squared error of this class is obtained. Some special cases(More)
BACKGROUND Private Practitioners (PP) are the primary source of health care for patients in India. Limited representative information is available on TB management practices of Indian PP or on the efficacy of India's Revised National Tuberculosis Control Programme (RNTCP) to improve the quality of TB management through training of PP. METHODS We conducted(More)
To estimate the population mean using auxiliary variable there are many estimators available in literature like-ratio, product, regression, dual-to-ratio estimator and so on. Suppose that all the information of the main variable is present in the sample but only a part of data of the auxiliary variable is available. Then, in this case none of the above(More)
To estimate the population mean with imputation, i.e. the technique of substituting missing data, there are a number of techniques available in literature like Ratio method of imputation, Compromised method of imputation, Mean method of imputation, Ahmed's methods of imputation, F-T methods of imputation and so on. If population mean of auxiliary(More)
To estimate the population mean with imputation i.e. the technique of substituting missing data, there are a number of techniques available in literature like Ratio method of imputation, Compromised method of imputation, Mean method of imputation, Ahmed method of imputation, F-T method of imputation, and so on. If population mean of auxiliary information is(More)
Missing data is a problem encountered in almost every data collection activity but particularly in sample survey. The missing data naturally occurs in sample surveys when some, not all sampling units refuse or unable to participate in the survey or when data for specific items on a questionnaire completed for an otherwise cooperating unit are missing.(More)
Introduction: In human heart, right atrio-ventricular orifice is guarded by tricuspid valve, which lies at the junction of right atrium and right ventricle of the heart controlling and directing unidirectional blood flow during ventricular diastole. Irreparable damage to tricuspid valve calls for its replacement using prosthetic valves. Prosthesis of these(More)
The objective of this paper is to study the linear combination of factor-type (F-T) estimator to estimate population mean and its properties like bias, mean squared error (m.s.e.) etc. along with numerical study over different populations. The expressions of bias and mean squared error (m.s.e.) of the estimator are derived in the form of population(More)
Main Objective is to investigate clinical decision support software systems. To find problems with manual clinical diagnosis process and impact of current clinical decision support systems on healthcare and medics. To use Genetic algorithm that can improve the clinical decision support systems, and future of clinical decision support systems. In this paper,(More)
This paper presents the estimation of mean in presence of missing data under two-phase sampling design using regression estimators as a tool for imputation while the size of responding () 1 R and non-responding () 2 R group is considered as a random variable. The bias and mean squared error of suggested estimators are derived in the form of population(More)