TITLE:
Ratio-Cum-Product Estimator Using Multiple Auxiliary Attributes in Two-Phase Sampling
AUTHORS:
John Kung’u, Leo Odongo
KEYWORDS:
Ratio-Cum-Product Estimator, Multiple Auxiliary Attributes, Two-Phase Sampling and Bi-Serial Correlation Coefficient
JOURNAL NAME:
Open Journal of Statistics,
Vol.4 No.4,
June
20,
2014
ABSTRACT: In this paper, we
have proposed three classes of ratio-cum-product estimators for estimating population mean of study variable for two-phase sampling using multi-auxiliary
attributes for full information, partial information and no information cases.
The expressions for mean square errors are derived. An empirical study is given
to compare the performance of the estimator with the existing estimator that
utilizes auxiliary attribute or multiple auxiliary attributes. The ratio-cum-product
estimator in two-phase sampling for full information case has been found to be
more efficient than existing estimators and also ratio-cum-product estimator in
two-phase sampling for both partial and no information case. Finally, ratio-cum-product
estimator in two-phase sampling for partial information case has been found to
be more efficient than ratio-cum-product estimator in two-phase sampling for no
information case.