Abstract:
A problem of the ratio
-
type estimators in Stratified Sampling is the use of non
-
attribute
auxiliary information. In this study, some ratio
-
type e
stimators in stratified random
sampling using attribute as auxiliary information are proposed. The sample mean of study
variable and proportion of auxiliary attribute were transformed linearly and using
auxiliary parameters respectively. Biases and mean sq
uare errors (MSE) for these
estimators were derived. The MSE of these estimators were compared with the MSE of
the traditional combined ratio estimator. The results show that the proposed estimators
are more efficient and less bias than the combined ratio
estimate in all conditions. An
empirical study was also conducted using students height data from each faculty of the
Usmanu
Danfodiyo University, Sokoto. The results also show that the proposed
estimators are more efficient and less bias than the combined
ratio estimator. In addition,
formulae for determination of sample sizes when the proposed estimators are adopted
under various allocations (Optimum, Neyman and Proportional) for fixed cost and
desired precision were obtained
