On the Efficiency of Imputation Estimators using Auxiliary Attribute

Audu, Ahmed; Ishaq, O. O.; Muili, Jamiu Olasunkanmi; Zakari, Yahaya; Ndatsu, A. M.; Muhammed, Shah

doi:10.5281/zenodo.3721046

Cited by 5 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…conducted by human are often characterized by non-response. [20] first discussed the issue of non-response and imputation methods to deal with non-response issues were suggested by several scholars like [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], Prasad [33], [34], [35], [36], [37], [38], are some of the most recent imputation methods. However, all the estimators of the schemes proposed by aforementioned authors are functions of population mean of auxiliary variable ( X ) and if X is unknown, the schemes can not be applied to real life situations.…”

Section: Caliphate Journal Of Science and Technology (Cajost)mentioning

confidence: 99%

On the efficiency of modified regression-type mean imputation scheme under two-phase sampling

Musa,

Audu,

Joseph

et al. 2023

CaJoST

View full text Add to dashboard Cite

Human-based surveys such as medical and social science surveys are often characterized by non-response or missing observations. In this study, a new class of regression-type mean imputation method that uses X̄n as an estimate of X̄ was suggested. Using partial derivative approach, the MSEs of the class of estimators presented were derived up to first order approximation under two cases. Case I: when the secondary sample S2 of size n(n<n1) is a subset of preliminary sample S1[S2 ⸦ S1] , and Case II: is when secondary sample S2 is a subset of universal set ΩN . Conditions for which the new estimator was more efficient than the other estimators studied were derived. The results of numerical examples through simulations revealed that the suggested class of estimators is more efficient.

show abstract

Section: Caliphate Journal Of Science and Technology (Cajost)mentioning

confidence: 99%

On the efficiency of modified regression-type mean imputation scheme under two-phase sampling

Musa,

Audu,

Joseph

et al. 2023

CaJoST

View full text Add to dashboard Cite

show abstract

“…Many authors have proposed estimators based on auxiliary attribute. Naik and Gupta [39], Singh et al, [40], Zaman and Kadilar [41], Zaman [42] Audu et al [43], Audu et al [44] suggested estimators by using auxiliary attributes. All the above-mentioned authors assumed known population attribute (P).…”

Section: Introductionmentioning

confidence: 99%

Modified Classes of Regression-Type Estimators of Population Mean in the Presences of Auxiliary Attribute

Audu

Abdulazeez

Danbaba

et al. 2022

ARJOM

View full text Add to dashboard Cite

The use of relevant information from auxiliary variable at the estimation stage and design stage to obtain reliable and efficient estimate is a common practice is a sample survey. But situations arise when the available auxiliary information are attribute in nature. There are some existing estimators based on auxiliary attribute in literature, however, they are less efficient when the bi-serial correlation between the study variable and auxiliary attribute is negative. Also, some depend on an unknown parameter of the study variable (Cy) which makes their applicability of the estimators in real life situations not possible unless if the value is estimated using a large sample which requires additional resources. In this work, the concept of regression base estimator was used to obtain estimators that are independent of unknown population parameter of the study variable and applicable for both negative and positive correlations. The properties (Biases and MSEs) of the modified estimators were derived up to the first order of approximation using Taylor series approach. The efficiency conditions of the proposed estimation over the existing estimator considered in the study were established. The empirical studies were conducted using both existing population parameters and stimulation to investigate the efficiency of the proposed estimators over the efficiency of the existing estimators. The results revealed that the proposed estimators have minimum MSEs and higher PREs among all the competing estimators. These imply that the proposed estimators are more efficient and can produce better estimate of the population mean compared to other existing estimators considered in the study.

show abstract

“…In survey sampling, the use of auxiliary characters is frequently recognized to increase the accuracy or precision of the population characteristics estimation procedures. Many researchers have considered the use of auxiliary characters in different forms to construct efficient estimators for population parameters (See Sisodia and Dwivedi [1], Murthy [2], Yadav and Kadilar [3], Singh and Tailor [4], Bahl and Tuteja [5], Singh et al [6], Singh et al [7], Kadilar and Cingi [8], Singh and Solanki [9], Sahai and Ray [10], Srivastava and Jhajj [11], Ahmed et al [12], Audu and Adewara [13], Audu et al [14], Muili et al [15], Khoshnevisan et al [16], Singh and Audu [17], Ahmed et al [18] and Audu and Singh [19], Das and Tripathi [20], Das and Tripathi [21], Patel and Rina [22], Rajyaguru and Gupta [23], Rajyaguru and Gupta [24], Archana and Rao [25], Singh et al [26], Audu et al [27][28][29][30][31][32], Singh et al [33], Muili et al [34], Ishaq et al [35], Audu et al [36], Zakari et al [37]. The issue of estimating variance of populations' characters is of great interest and as received attentions of researchers due to difficulties in controlling variabilities in application.…”

Section: Introductionmentioning

confidence: 99%

Generalized Estimators for Finite Population Variance Using Measurable and Affordable Auxiliary Character

Muhammad

Zakari

Audu

2022

ARJOM

View full text Add to dashboard Cite

In this paper, a generalized exponential-type estimator for estimating the population variance using measurable and affordable auxiliary character in single phase sampling has been proposed. Some special cases of the proposed generalized estimator with a = 1 and a = 2 have also been discussed. The expressions for the mean square error and bias of the proposed generalized estimator have been derived. The efficiency of the proposed generalized estimator has been compared theoretically with the existing estimators and the conditions under which the proposed estimators are better than some existing estimators have also been given. Numerical examples with five real data sets to compute MSEs and PREs were conducted to ascertain the efficiency of the proposed estimators over others and the results showed that both of the proposed estimators were more efficient than the estimators considered in literature. Thus, the estimator with perform better than the estimator with a = 1.

show abstract

On the Efficiency of Imputation Estimators using Auxiliary Attribute

Cited by 5 publications

References 0 publications

On the efficiency of modified regression-type mean imputation scheme under two-phase sampling

On the efficiency of modified regression-type mean imputation scheme under two-phase sampling

Modified Classes of Regression-Type Estimators of Population Mean in the Presences of Auxiliary Attribute

Generalized Estimators for Finite Population Variance Using Measurable and Affordable Auxiliary Character

Contact Info

Product

Resources

About