Abstract
This article suggests a chain ratio-type estimator of population total based on calibration that takes into account auxiliary variables present on both occasions, and information on the study variable is not available on the first occasion. The optimal composite weights to choose, together with their performance range, are presented along with the bias expression. An empirical and simulation-based study is used to evaluate the effectiveness of the suggested estimator. The studies demonstrate that the proposed estimator outperforms the other estimators for various composite weight selections with varying matched and unmatched sample sizes.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alka, Rai PK, Qasim M (2019) Two-step calibration of design weights under two auxiliary variables in sample survey. J Stat Comput Simul 89:2316–2327
Alka, Emmanuel EJ, Rai PK, Tiwari S (2021) Calibration estimator of population mean under stratified systematic sampling design. Int J Agric Stat Sci 17:2353–2361
Alka, Rai PK, Qasim M (2023) Two-step calibration estimator with double use of auxiliary variable: method and application. J Iran Stat Soc 21(1):47–63
Deville J-C, Särndal CE (1992) Calibration estimators in survey sampling. J Am Stat Assoc 87(418):376–382
Enang EI, Clement EP (2019) An efficient class of calibration ratio estimators of domain mean in survey sampling. Commun Math Stat 5:1–15
Estevao VM, Särndal CE (2000) A functional form approach to calibration. J Off Stat 16(4):379–399
Kim JM, Sungur EA, Heo TY (2007) Calibration approach estimators in stratified sampling. Stat Probab Lett 77:99–103
Narain RD (1953) On the recurrence formula in sampling on successive occasions. J Indian Soc Agric Stat 5:96–99
Priyanka K, Kumar A, Trisandhya P (2021) Calibration estimators for quantitative sensitive mean estimation under successive sampling. Commun Stat Theory Methods 50(6):1341–1361
Rai PK, Alka, Qasim M (2021) Calibration-based estimators using different distance measures under two auxiliary variables: a comparative study. J Modern Appl Stat Methods 19(1):15
Rai PK, Tikkiwal GC, Alka. (2020) A joint calibration estimator of population total under minimum entropy distance function based on dual frame surveys. Statistical methods and applications in forestry and environmental sciences. Springer, Singapore, pp 125–150
Rueda M, Martinez S, Arcos A, Munoz JF (2009) Mean estimation under successive sampling with calibration estimators. Commun Stat Theory Methods 38(6):808–827
Salinas VI, Sedory SA, Singh S (2018) Calibration using power transformation. Commun Stat Simul Comput 5:1–31
Salinas VI, Sedory SA, Singh S (2022) Higher order calibrated estimator in two-stage sampling. Commun Stat Theory Methods 51(10):3164–3180
Singh GN, Bhattacharyya D, Bandyopadhyay A (2021) Calibration estimation of population variance under stratified successive sampling in presence of random non response. Commun Stat Theory Methods 50(19):4487–4509
Singh S, Arnab R (2006) A bridge between the GREG and linear regression estimators. In: Proceedings of ASA section on survey research methods, Seattle, pp 3689–3693
Singh S (2003) Advanced sampling theory with applications: how michael “selected” amy. Kluwer Academic Publisher, The Netherlands
Singh S (2012) On the calibration of design weights using a displacement function. Metrika 75:85–107
Singh S (2013) A dual Problem of calibration of design weights. Statistics 47:566–574
Singh S, Arnab R (2011) On calibration of design weights. Metron Int J Stat 2:185–205
Singh HP, Singh HP, Singh VP (1992) A generalized efficient class of estimators of population mean in two phase and successive sampling. Int J Manag Syst 8(2):173–183
Singh S, Sedory SA (2016) Two-step calibration of design weights in survey sampling. Commun Stat Theory Methods 45(12):3510–3523
Singh P, Yadav RJ (1992) Generalized estimation under successive sampling. J Indian Soc Agric Stat 44:27–36
Tracy DS, Singh S, Arnab R (2003) Note on calibration in stratified and double sampling. Surv Methodol 29(1):99–104
Acknowledgements
The authors are thankful to Banasthali Vidyapith, Banaras Hindu University and GITAM university for providing the infrastructure facilities. We would also like to thank the reviewers for their valuable suggestions that helped bring this paper to its current state.
Funding
No specific grant was given to this research by funding organizations in the public, private, or not-for-profit sectors.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Human Participants and/or Animals
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent
All authors have seen the manuscript and approved to submit to your journal. We confirm that the content of the manuscript has not been published or submitted for publication elsewhere.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Tiwari, S., Alka & Rai, P.K. Calibration based chain ratio-type estimator of population total under successive sampling. Int J Syst Assur Eng Manag (2024). https://doi.org/10.1007/s13198-024-02321-y
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s13198-024-02321-y