Browsing by Author "Singh, Ajeet Kumar"

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    A Comparative Study on Calibration Approach Based Estimators for Domain Estimation Utilizing Power Function: Revisited
    (Springer Science and Business Media Deutschland GmbH, 2023) Ashutosh; Rai, Piyush Kant; Singh, Ajeet Kumar
    The calibration approach based estimators of the domain mean have growing demand during past couple of decades. Estimation of domains is another challenging task for surveyors and several efforts have been made to produce the reliable estimators for this purpose. Prominently the power function based estimators in the sample surveys are having dual advantages for the selection and their application to produce an improved estimation at any stage in the terms of efficiency without much complexity. In the domain estimation utilization of the power function in the development of calibration based estimators are also very promising and provide considerable results. A simulation study has examined for the comparison of several calibration estimators along with the proposed estimator in terms of the absolute relative bias and simulated relative standard error. � 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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    A Family of Estimators for Population Mean Under Model Approach in Presence of Non-Response
    (River Publishers, 2022) Singh, Ajeet Kumar; Singh, V.K.
    We have defined a class of estimators for population mean under nonresponse error based upon the concept of sub-sampling of non-respondents utilizing an auxiliary variable. The class is a one-parameter class of estimators which is based on the idea of exponential type estimators (ETE). The model biasness and model-mean square error of the class and some of its important members have been derived under polynomial regression model (PRM). The effect of variations in PRM specifications on the efficiency of the estimators has been discussed based upon the empirical results. � 2022 River Publishers.
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    Investigating the performance of a family of exponential-type estimators in presence of measurement error
    (Bellwether Publishing, Ltd., 2021) Kumar, Abhishek; Singh, Ajeet Kumar; Singh, V.K.
    The measurement error (ME), one of the serious kinds of non sampling errors, is the difference between the value of a characteristic provided by the respondent and the true value of it. Generally, in practice it is almost impossible to get the true value due to non availability of an appropriate and feasible method of measuring it. In fact, the assumption of getting information from a unit without any biases or measuring a unit correctly is very unrealistic. ME may give rise to serious bias and variable errors both in an estimator obtained through a survey. This work is mainly concentrated on the study of variations that may occur in certain components of ME models considered and their impact on some existing usual estimators of population mean along with a proposed family of exponential-type estimators which might be considered as an alternative to classical ratio/product estimators in some sense. Some important features of these estimators in presence of ME have been dealt with. Results discussed have been highlighted with the help of an empirical data which reflects the extent of consequences of changes in model parameters on the performance of estimators. � 2019 Taylor & Francis Group, LLC.
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    Potential impact of rotavirus vaccination on reduction of childhood diarrheal disease in India: An analysis of National Family Health Survey-5
    (Elsevier Ltd, 2023) Dhalaria, Pritu; Kapur, Sanjay; Singh, Ajeet Kumar; Verma, Ajay; Priyadarshini, Pretty; Taneja, Gunjan
    Rotavirus is one of the leading causes of diarrhea in infants and young children worldwide. In this study, we investigated the impact of rotavirus vaccination on the prevalence of diarrheal disease among children under five years of age in India. Research on the impact of the rotavirus vaccine on reducing diarrheal disease is therefore important in contributing to the growing body of evidence on the effectiveness of this intervention in improving child health outcomes. We adopted multivariate logistic regression and propensity score matching analysis to examine the association between diarrhea and the rotavirus vaccine. The bivariate analysis finding shows that the prevalence of diarrhea was remarkably higher (9.1%) among children who had not received rotavirus and the prevalence was 7.5%, 7.5%, and 7.2% among children who received one dose, two doses, and three rotavirus doses (all) respectively. The result of multivariate logistic regression shows that children who received all three doses of the rotavirus vaccine were 16% less likely to experience diarrhea compared to those who did not receive any rotavirus vaccine. Our analysis also found that the prevalence of diarrhea decreased significantly in the years following the introduction of the vaccine. The results of this study suggest that the rotavirus vaccine has a significant impact on reducing childhood diarrheal disease in India. These results have the potential to inform policy decisions and enable healthcare professionals to concert their efforts in reducing the diarrheal disease burden and its timely prevention in children. The study will also contribute to the existing literature on the impact of rotavirus vaccination in reducing the prevalence of diarrhea among children in India. � 2023 The Author(s)