Browsing by Author "Adewara, A. A."
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Item Alternative Ratio - Regression Tpe Estimator in Simple Random Sampling(Faculty of Physical Sciences, University of Ilorin, 2015) Adewara, A. A.In this study, an alternative ratio-regression type estimator was proposed which was compared with Kadilar and Cingi (2004), and Ekaete et al. (2014) estimators. This proposed estimator combined classical ratio estimator with our usual regression estimator. The same data set used by Kadilar and Cingi (2004), and Ekaete et al. (2014) were also used to determine the efficiency of this alterative ratio-regression type estimator.Item ALTERNATIVE TO FACTOR-TYPE ESTIMATOR UNDER SINGLE-PHASE SAMPLING(Katsina Journal of Natural and Applied Sciences, 2016) Audu, A.; Adewara, A. A.In this paper alternative estimator to factor-type estimator for estimating population mean has been proposed using information on population units yet to be drawn from both study and auxiliary variables. The expressions for bias and MSE for the proposed estimator in the form of population parameters using the concept of large sample approximation have been derived and the conditions for its efficiency over the conventional estimators have been established. Also empirical study to demonstrate the efficiencies of the proposed estimator over traditional estimators have been performed and the results show that the proposed estimator is less biased and performed better.Item Bayesian Analysis of Kim and Warde Randomized Response Technique Using Alternative Priors(American Journal of Computational and Applied Mathematics, 2014) Adepetun, A. O.; Adewara, A. A.In this paper, we developed the Bayesian estimators of the population proportion of a stigmatized attribute using Kumaraswamy and Generalised Beta prior distributions when data were obtained through the Randomized Response Technique (RRT) proposed by Kim and Warde [15]. We validated our newly developed Bayesian estimators for a wide range of the designed values of the population proportion at varying sample sizes. It was observed that our newly developed Bayesian estimators performed significantly better than the Bayesian estimator developed by Hussain and Shabbir [12] for relatively small as well as moderate sample sizes. However, the reverse was the case for very large sample sizes.Item BAYESIAN ESTIMATION OF POPULATION PROPORTION OF A STIGMATIZED ATTRIBUTE USING A FAMILY OF ALTERNATIVE BETA PRIORS(International Journal of Scientific & Engineering Research, 2015) Adepetun, A. O.; Adewara, A. A.In this study, we have developed the Bayes estimators of the population proportion of a stigmatized attribute when data were gathered through the randomized response technique (RRT) put forward by Hussain and Shabbir [9]. Using both the Kumaraswamy (KUMA) and the Generalised (GLS) beta distributions as a family of alternative beta priors, superiority of the derived Bayes estimators was established for a large interval of the values of the population proportion. We observed that for small, moderate as well as large sample sizes, the alternative Bayes estimators were better than the Bayes estimator proposed by Hussain and Shabbir [10] when a simple beta prior was usedItem CAPTURE – RECAPTURE METHOD TO FISH CATCHMENT FOR ESTIMATING THE SIZE OF A CLOSED POPULATION USING OTIS SCHEME(Faculty of Physical Sciences and Faculty of Life Sciences, Univ. of Ilorin, Nigeria, 2016) Adewara, A. A.; Ogunsanya, B. H.Capture-recaputre method was used to estimate fish abundance at Remto Farms, Eyenkorin Lasoju Ilorin, kwara state, Nigeria using Otis scheme. The fieldwork was aimed at estimating the fish abundance in ponds 1 and 2 based on varying probability affecting them. The models considered in this study are: Lincoln-Peterson model, Equal catchability model, the Heterogeneity model, Trap Response model, Heterogeneity and Trap response Model, the Schnabel and other time Dependent models. R-capture package was used to obtain the estimate of each of the models considered and to determine the best model. We observed that the Trap Response and the Schnabel-Heterogeneity models that vary with time gives the best models for the fieldwork.Item CLASS OF RATIO ESTIMATORS WITH KNOWN FUNCTIONS OF AUXILIARY VARIABLE FOR ESTIMATING FINITE POPULATION VARIANCE(Asian Journal of Mathematics and Computer Research, 2016) Audu, A.; Adewara, A. A.; Singh, R. V. K.In this paper, we have suggested a class of improved ratio estimators for finite population variance. The proposed class of estimators is obtained by using unknown weight on some existing estimators. The MSE of the proposed estimators have been obtained and the conditions for their efficiency over some existing variance estimators have been established. The present proposed family of finite variance estimators, having obtaining the optimal values of the constants, exhibit significant improvement over the existing estimators. The empirical study is also conducted to corroborate the theoretical results and the results show that the proposed class of estimators is more efficient.Item Comparison of Some Sample Selection Procedures In Probability Proportional to Size(ICASTOR Journal of Engineering, 2016) Dawodu, O. O.; Adewara, A. A.The importance of probability proportional to size sampling cannot be over emphasized. In recent times, Statisticians often work on complex survey data which involve weighting, as a result of the unequal probability nature of units. There is need to work on design weights, which is defined as the inverse of the probability of inclusion of single unit in the sample. Two simulated data sets are generated using ܴin order to obtain the probability of inclusion of single unit and also the joint probability of inclusion of units in the sample. Auxiliary variables and variables of interest were generated in such a way that there exists reasonable correlation between both. A procedure for selecting samples with probability proportional to size nature without replacement was proposed. This procedure could be used with Horvitz and Thompson estimator of variance. The variance estimates are obtained using the modified sample selection procedure and an existing procedure, and results obtained. For the two data sets, it is observed that the modified procedure is more efficient than the existing one.Item Complex Survey Data Analysis: A Comparison of SAS, SPSS and STATA(Asian Network for Scientific Information, Pakistan., 2010) OYEYEMI, G. M.; Adewara, A. A.; Adeyemi, R. A.We compared three statistical packages (SAS, SPSS and STATA) in analyzing complex survey data in the context of multiple regression analysis using concrete examples from two national healthcare databases (MEPS and NDHS). The three packages are found to be efficient and flexible in analyzing complex survey data, but SAS in some cases seems to overestimate the variances of the sample statistics. Adjustment for stratification (incorporating stratification) is very important in complex survey analysis, especially if the stratification variable is endogenousItem Complex Survey Data Analysis: A Comparison of SAS, SPSS and STATA(Asian Network for Scientific Information, 2010) Oyeyemi, G. M.; Adewara, A. A.; Adeyemi, R. A.We compared three statistical packages (SAS, SPSS and STATA) in analzing complex survey data in the context of multiple regression analysis using concrete examples from two national healthcare database (MEPS and NDHS). The three packages are found to be efficient and flexible in analyzing complex survey data, but SAS in some cases seems to over estimate the variances of the sample statistics. Adjustment for stratification (incorporating stratification) is very important in complex survey analysis, especially if the stratification variable is endogenousItem Efficiency in Double Sampling under a Particular Linear Regression Model(Faculty of Physical Sciences, University of Ilorin, 2015) Adewara, A. A.In this study, three regression and mean per unit estimators in double sampling under a particular linear regression were proposed using Monte Carlo Method through simulation and from the estimated mean square errors obtained on these estimators, we observed that one of the newly proposed regression estimator, performed better and hence, preferred.Item Efficiency of Alodat Sample Selection Procedure over Sen - Midzuno and Yates - Grundy Draw by Draw under Unequal Probability Sampling without Replacement Sample Size 2(Journal of Mathematics Research, 2011) Dawodu, O. O.; Adewara, A. A.; Olayiwola, O. M.This paper compare the efficiency of Alodat sample selection procedure over Sen - Midzuno and Yates - Grundy draw by draw using Yates - Grundy estimator under unequal probability sampling without replacement sample size 2, carried out using the data from the 2008 Demographic and health survey in Nigeria. We studied the distribution of pregnant women age 15 - 49, and children under age five in Nigeria, who use mosquito nets as a means of preventing malaria. These data sets are: (1) the number of pregnant women age 15 - 49 who slept under mosquito nets the night before the survey, and (2) the number of children under age five who slept under mosquito nets the night before the survey. (1) and (2) above are the variables of interest. The data were collected based on the six geo-political zones in Nigeria [i.e. South South, South West, South East, North West, North East, North Central]. The auxiliary variable is the number of Local Government in each geo-political zone in Nigeria. The Yates - Grundy estimate obtained using Alodat sample selection is more efficient than using Sen - Midzuno and Yates - Grundy selection procedures.Item EFFICIENCY OF AUDU & ADEWARA ((2017)) TWO--PHASE FACTOR--TYPE ESTIMATORS WITH TWO AUXILIARY VARIABLES IN SAMPLE SURVEY(Anale. Seria Informatică, 2017) Ahmed, A.; Adewara, A. A.In this paper, efficiency of Audu & Adewara ([AA17]) two-phase factor-type estimators with two auxiliary variables for estimating finite population mean were examined using simulation. These estimators were obtained by incorporating some known functions of auxiliary variables X and Z in some existing factor-type estimators. Bias and Mean square error (MSE) of these estimators, yb1(d)FTAA and yb2(d)FTAA were obtained using tailor’s series expansion. Audu & Adewara ([AA17]) revealed that although yb1(d)FTAA and yb2(d)FTAA, have minimum MSE and high PRE than all other related existing factor-type estimators considered using three life dataset but of these two, which is more efficient and most preferred. The simulation results obtained in this study revealed that yb2(d)FTAA is more efficient than yb1(d)FTAA and hence, most preferred.Item EFFICIENCY OF SOME MODIFIED RATIO TYPE ESTIMATORS USING PRODUCT OF SAMPLE SIZE AND PARAMETERS OF AUXILIARY VARIABLE FOR ESTIMATING POPULATION MEAN(Anale. Seria Informatica., 2019) Suleiman, S. A.; Adewara, A. A.In this paper, we modified twenty-eight ratio type estimators for estimation of population mean of the study variable earlier suggested by Gupta and Yadav ([GY17]) using product of sample size and population parameter of auxiliary variable. The expressions for the bias and mean square errors of the newly modified ratio type estimators have been obtained up to the first order of approximation. A comparison has been made with the mentioned existing ratio estimators of population mean using the same data set used by Gupta and Yadav ([GY17]) for easy justification. The results obtained on the Mean Square Errors shows that the newly modified ratio type estimators perform better vis-à-vis the earlier suggested Gupta and Yadav ([GY17]) existing ratio type estimators but the newly modified ratio type Estimator, t*27, perform better, hence, recommended for usage in SamplingItem ESTIMATION OF ABRIDGED WORK-LIFE EXPECTANCY IN KWARA STATE NIGERIA USING KPEDEKPO’S WORKING LIFE SCHEME(Faculty of Physical Sciences and Faculty of Life Sciences, Univ. of Ilorin, Nigeria, 2016) Adewara, A. A.; Kolawole, A. A.; Job, O.This study was aimed at estimating life and working life expectancies of Kwara State, Nigeria from the construction of life tables using 2006 Nigerian population census figures in line with Kpedekpo’s working life table in Ghana with particular reference to the female working population and also for males. It is imperative to note here that working life table makes do with the working population and survivors at different age groups. The Nigerian 2006 population data was considered for this study due to its comprehensiveness in terms of data gathering where information about labour force was well collated. This study was carried out to estimate the work-life expectancy and expected retirement of Kwara State by Nigeria abridged work-life table. It highlighted the average years and until when a person stay in active service in Kwara State, Nigeria. Also, aimed to predict the working life expectancy and expected retirement age and providing information on length of remaining years at exact age x. It was observed that both the average years lived and average years in working life followed the same trend, starting at high values and decreased as the ages advanced. They both started at high values of 38.03 and 40.49 for the average years lived and average years in working life respectively and eventually decreased as the ages advanced. The average years lived and average years in working life began to synchronize at 30.38 years value down to 2.50 years value for age group 85 and above. The life and working life expectancies in Kwara State, Nigeria started from 55.03 and 57.49 respectively.Item ESTIMATION OF POPULATION PROPORTION OF STIGMATIZED ATTRIBUTE USING BAYESIAN APPROACH(Bulgarian Journal of Science and Education Policy, 2019) Adepetun, A. O.; Adewara, A. A.. Bayesian Approach to Randomized Response Technique has been a technique for estimating the population proportion, especially of respondents possessing stigmatized attributes such as induced abortion, use of drugs and tax evasion. In this paper, we propose Bayesian estimators of population proportion of a stigmatized attribute assuming Kumaraswamy and the generalised beta prior using life data on induced abortion. The newly proposed Bayesian estimators were validated numerically for a large interval of the designed values of the population proportion at different sample sizes. It was observed that the newly developed Bayesian estimators were more sensitive in capturing stigmatized attribute than the Bayesian estimator developed by Hussain & Shabbir (2012) for relatively small, moderate as well as large sample sizes.Item Extension of Mangat Randomized Response Technique Using Alternative Beta Priors(Punjab University, 2016) Adepetun, A. O.; Adewara, A. A.In this study, an extension of Mangat Randomized Response Technique using alternative beta priors has been considered and new Bayes estimators of population proportion of respondents possessing stigmatized attribute were developed when data were gathered through administration of survey questionnaire on induced abortion on 300 matured women in the metropolis. Dominance picture of the proposed Bayes estimators has been portrayed for a wide range of values of population proportion assuming alternative Beta distributions as Prior information. It is observed that the proposed Bayes estimators performed better than the Bayes estimator proposed by Hussain et al [15] when a simple Beta prior was used for small, medium as well as large sample sizes respectively. This is evident as our proposed Bayes estimators have least mean squared errors (MSEs) as π approaches one.Item GENERALISED LYNCH MULTIVARIATE REGRESSION ESTIMATORS WITH ft.PARAMETERS OF ORDER 1/n(ICASTOR, India, 2008) Adewara, A. A.; Job, O.; Abidoye, A. O.; Oyeyemi, G.M.In this paper, several authors have proposed ratio type estimators which utilized data from several auxiliary variates that involves the use of unknown weights which have to be estimated but Lynch proposed a multivariate regression estimator when there are two auxiliary variates (x-varaiates) which was found to be better and preferred, even to the conventional mean estimate. In this paper, we proposed multivariate regession estimators with k-parameters of order 1/n as used by Lynch. Two data sets called Populations l and 2 were used to justify this research work. While Population I is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 86 occupants of Kubwa Federal Housing Authority, Phase lV Estate, Abuja, Nigeria, Population 2 is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 95 occupants of Gwarinpa Il Estate, Abuja ,Nigeria and it was observed that as ,k-parameters increases, our * multivariate regression estimate becomes smaller and better which makes the highest k-parameter multivariate regression estimator to be preferredItem Generalized Lynch Multivariate Regression Estimators with k-Parameters of Order 1/n(International Center for Advance Studies, India, 2008) Adewara, A. A.; Job, O.; Abidoye, A. O.; Oyeyemi, G. M.; Gali, M. O.; Alabi, O. O.In this paper several authors have proposed ratio type estimator which utilized data from several auxiliary variates that involves the use of unknown weights which have to be estimated but Lynch proposed a multivariate regression estimator when there are two auxiliary variates (x-varaiates) which was found to be better and preferred, even to the conventional mean estimate. In this paper, we proposed multivariate regression estimators with k -parameters of order 1/n as used by Lynch. Two data sets called Populations 1 and 2 were used to justify this research work. While Population I is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 86 occupants of Kubwa Federal Housing Authority, Phase lV Estate Abuja, Nigeria, Population 2 is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 95 occupants of Gwarinpa II Estate, Abuja Nigeria and it was observed that as, K-parameters increases, our k multivariate regression estimate becomes smaller and better which makes the highest k -parameter multivariate regression estimator to be preferredItem IMPROVED MODIFIED RATIO ESTIMATOR FOR ESTIMATING POPULATION MEAN IN DOUBLE SAMPLING USING INFORMATION ON AUXILIARY ATTRIBUTE(Anale. Seria Informatică, 2019) Amoyedo, F. E.; Adewara, A. A.This paper proposes a modified family of ratio estimator of population mean using information on auxiliary attribute and the estimation of population mean in double sampling in ratio form. The proposed modified ratio estimator is a family of estimator which results to different estimators at different value of alpha. For the proposed estimator, when 𝛼 = 0, 0.5 and 1, the estimators of Naik and Gupta (1996), Nirmala Sawan (2010) and Sample mean were recovered respectively. When the auxiliary attribute is a variable, the estimator result to that of Subhash et al. (2016). When α = 0 and the auxiliary attribute is a variable, it results to conventional double sampling. The expression for the Bias, and Mean Square Error of the proposed modified estimator were obtained up to the first order of approximation. An efficiency comparison of both the theoretical and empirical was carried out with some related existing estimators in double sampling. It has been established that the proposed modified ratio estimator is more efficient when compared with the existing ones at optimum value of alphaItem MODIFICATION OF RATIO ESTIMATOR UNDER TWO PHASE SAMPLING(FUW Trends in Science & Technology Journa, 2018) Kamba, A. I.; Adewara, A. A.; Audu, A.In this paper, modification of Adebola and Adegoke’s report on ratio estimator was suggested. The modified estimator was obtained through transformation in two cases using sample mean of auxiliary variables. Case one was when the second sample was drawn from the first sample why case two was when the second sample was drawn from the population. The bias and mean square error (MSE) of the modified ratio estimator in the two cases were obtained. The theoretical and numerical validity of the modified ratio estimator under the two cases were determined to show its superiority over some considered existing related ratio estimators. Numerical results shows that the modified ratio estimator under the two cases were more efficient than the considered existing related estimators