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Search Results: 1 - 10 of 236 matches for " Romanus Otieno Odhiambo "
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Estimation of Population Variance Using the Coefficient of Kurtosis and Median of an Auxiliary Variable under Simple Random Sampling  [PDF]
Tonui Kiplangat Milton, Romanus Otieno Odhiambo, George Otieno Orwa
Open Journal of Statistics (OJS) , 2017, DOI: 10.4236/ojs.2017.76066

In this study we have proposed a modified ratio type estimator for population variance of the study variable y under simple random sampling without replacement making use of coefficient of kurtosis and median of an auxiliary variable x. The estimator’s properties have been derived up to first order of Taylor’s series expansion. The efficiency conditions derived theoretically under which the proposed estimator performs better than existing estimators. Empirical studies have been done using real populations to demonstrate the performance of the developed estimator in comparison with the existing estimators. The proposed estimator as illustrated by the empirical studies performs better than the existing estimators under some specified conditions i.e. it has the smallest Mean Squared Error and the highest Percentage Relative Efficiency. The developed estimator therefore is suitable to be applied to situations in which the variable of interest has a positive correlation with the auxiliary variable.

A Multiplicative Bias Correction for Nonparametric Approach and the Two Sample Problem in Sample Survey  [PDF]
Kemtim Tamboun Stephane, Romanus Odhiambo Otieno, Thomas Mageto
Open Journal of Statistics (OJS) , 2017, DOI: 10.4236/ojs.2017.76073
Abstract: Let two separate surveys collect related information on a single population U. Consider situation where we want to best combine data from the two surveys to yield a single set of estimates of a population quantity (population parameter) of interest. This Article presents a multiplicative bias reduction estimator for nonparametric regression to two sample problem in sample survey. The approach consists to apply a multiplicative bias correction to an estimator. The multiplicative bias correction method which was proposed, by Linton & Nielsen, 1994, assures a positive estimate and reduces the bias of the estimate with negligible increase in variance. Even as we apply this method to the two sample problem in sample survey, we found out through the study of it asymptotic properties that it was asymptotically unbiased, and statistically consistent. Furthermore an empirical study was carried out to compare the performance of the developed estimator with the existing ones.
George Otieno Orwa,Romanus Odhiambo Otieno,Peter Nyamuhanga Mwita
Pakistan Journal of Statistics and Operation Research , 2010, DOI: 10.1234/pjsor.v6i1.149
Abstract: We propose a nonparametric regression approach to the estimation of a finite population total in model based frameworks in the case of stratified sampling. Similar work has been done, by Nadaraya and Watson (1964), Hansen et al (1983), and Breidt and Opsomer (2000). Our point of departure from these works is at selection of the sampling weights within every stratum, where we treat the individual strata as compact Abelian groups and demonstrate that the resulting proposed estimator is easier to compute. We also make use of mixed ratios but this time not in the contexts of simple random sampling or two stage cluster sampling, but in stratified sampling schemes, where a void still exists.
Christopher Ouma Onyango,Romanus Odhiambo Otieno,George Otieno Orwa
Pakistan Journal of Statistics and Operation Research , 2010, DOI: 10.1234/pjsor.v6i2.128
Abstract: Chambers and Dorfman (2002) constructed bootstrap confidence intervals in model based estimation for finite population totals assuming that auxiliary values are available throughout a target population and that the auxiliary values are independent. They also assumed that the cluster sizes are known throughout the target population. We now extend to two stage sampling in which the cluster sizes are known only for the sampled clusters, and we therefore predict the unobserved part of the population total. Jan and Elinor (2008) have done similar work, but unlike them, we use a general model, in which the auxiliary values are not necessarily independent. We demonstrate that the asymptotic properties of our proposed estimator and its coverage rates are better than those constructed under the model assisted local polynomial regression model.
Robust estimation of variance in the presence of nearest neighbour imputation
Charles Wafula, Romanus Odhiambo Otieno, Mugo Maxwell Mwenda
African Journal of Science and Technology , 2003,
Abstract: The problem of estimating the variance of an estimator of the population total when missing values have been filled using a Nearest Neighbour (NN) imputation method is considered. The estimator is developed assuming a more general model than those considered in earlier studies. In an empirical study involving two artificial populations, the proposed estimator is found to perform better or as well as other two estimators in the current use. African Journal of Science and Technology Vol.4(2) 2003: 5-11
Peter Nyamuhanga Mwita,Romanus Odhiambo Otieno,Verdiana Grace Masanja,Charles Muyanja
Pakistan Journal of Statistics and Operation Research , 2011, DOI: 10.1234/pjsor.v7i2.241
Abstract: This paper considers the modeling and prediction of households food security status using a sample of households in the Lake Victoria region of Kenya. A priori expected food security factors and their measurements are given. A binary logistic regression model derived was fitted to thirteen priori expected factors. Analysis of the marginal effects revealed that effecting the use of the seven significant determinants: farmland size, per capita aggregate production, household size, gender of household head, use of fertilizer, use of pesticide/herbicide and education of household head, increase the likelihood of a household being food secure. Finally, interpretations of predicted conditional probabilities, following improvement of significant determinants, are given.
Local Polynomial Regression Estimator of the Finite Population Total under Stratified Random Sampling: A Model-Based Approach  [PDF]
Charles K. Syengo, Sarah Pyeye, George O. Orwa, Romanus O. Odhiambo
Open Journal of Statistics (OJS) , 2016, DOI: 10.4236/ojs.2016.66088
Abstract: In this paper, auxiliary information is used to determine an estimator of finite population total using nonparametric regression under stratified random sampling. To achieve this, a model-based approach is adopted by making use of the local polynomial regression estimation to predict the nonsampled values of the survey variable y. The performance of the proposed estimator is investigated against some design-based and model-based regression estimators. The simulation experiments show that the resulting estimator exhibits good properties. Generally, good confidence intervals are seen for the nonparametric regression estimators, and use of the proposed estimator leads to relatively smaller values of RE compared to other estimators.
Longitudinal Survey, Nonmonotone, Nonresponse, Imputation, Nonparametric Regression  [PDF]
Sarah Pyeye, Charles K. Syengo, Leo Odongo, George O. Orwa, Romanus O. Odhiambo
Open Journal of Statistics (OJS) , 2016, DOI: 10.4236/ojs.2016.66092
Abstract: The study focuses on the imputation for the longitudinal survey data which often has nonignorable nonrespondents. Local linear regression is used to impute the missing values and then the estimation of the time-dependent finite populations means. The asymptotic properties (unbiasedness and consistency) of the proposed estimator are investigated. Comparisons between different parametric and nonparametric estimators are performed based on the bootstrap standard deviation, mean square error and percentage relative bias. A simulation study is carried out to determine the best performing estimator of the time-dependent finite population means. The simulation results show that local linear regression estimator yields good properties.
Evaluation criteria for the district health management information systems: lessons from the Ministry of Health, Kenya
George W. Odhiambo-Otieno, Wilson WO Odero
African Health Sciences , 2005,
Abstract: Background: The District Health Management Information Systems (DHMISs) were established by the Ministry of Health (MoH) in Kenya more than two decades ago. Since then, no comprehensive evaluation has been undertaken. This can partly be attributed to lack of defined criteria for evaluating them. Objective: To propose evaluation criteria for assessing the design, implementation and impact of DHMIS in the management of the District Health System (DHS) in Kenya. Methods: A descriptive cross-sectional study conducted in three DHSs in Kenya: Bungoma, Murang'a and Uasin Gishu districts. Data was collected through focus group discussions, key informant interviews, and documents' review. The respondents, purposely selected from the Ministry of Health headquarters and the three DHS districts, included designers, managers and end-users of the systems. Results: A set of evaluation criteria for DHMISs was identified for each of the three phases of implementation: pre-implemen-tation evaluation criteria (categorised as policy and objectives, technical feasibility, financial viability, political viability and administrative operability) to be applied at the design stage; concurrent implementation evaluation criteria to be applied during implementation of the new system; and post-implementation evaluation criteria (classified as internal – quality of information; external – resources and managerial support; ultimate – systems impact) to be applied after implementation of the system for at least three years. Conclusions: In designing a DHMIS model there is need to have built-in these three sets of evaluation criteria which should be used in a phased manner. Pre-implementation evaluation criteria should be used to evaluate the system's viability before more resources are committed to it; concurrent (operational) – implementation evaluation criteria should be used to monitor the process; and post-implementation evaluation criteria should be applied to assess the system's effectiveness
Increased deposition of C3b on red cells with low CR1 and CD55 in a malaria-endemic region of western Kenya: Implications for the development of severe anemia
Collins O Odhiambo, Walter Otieno, Christine Adhiambo, Michael M Odera, José A Stoute
BMC Medicine , 2008, DOI: 10.1186/1741-7015-6-23
Abstract: Three hundred and forty-two life-long residents of a malaria-holoendemic region of western Kenya were enrolled in a cross-sectional study and stratified by age. We measured red cell C3b, CR1, CD55, and immune complex binding capacity by flow cytometry. Individuals who were positive for malaria were treated and blood was collected when they were free of parasitemia. Analysis of variance was used to identify independent variables associated with the %C3b-positive red cells and the hemoglobin level.Individuals between the ages of 6 and 36 months had the lowest red cell CR1, highest %C3b-positive red cells, and highest parasite density. Malaria prevalence also reached its peak within this age group. Among children ≤ 24 months of age the %C3b-positive red cells was usually higher in individuals who were treated for malaria than in uninfected individuals with similarly low red cell CR1 and CD55. The variables that most strongly influenced the %C3b-positive red cells were age, malaria status, and red cell CD55 level. Although it did not reach statistical significance, red cell CR1 was more important than red cell CD55 among individuals treated for malaria. The variables that most strongly influenced the hemoglobin level were age, the %C3b-positive red cells, red cell CR1, and red cell CD55.Increasing malaria prevalence among children >6 to ≤ 36 months of age in western Kenya, together with low red cell CR1 and CD55 levels, results in increased C3b deposition on red cells and low hemoglobin. The strong contribution of age to C3b deposition suggests that there are still additional unidentified age-related factors that increase the susceptibility of red cells to C3b deposition and destruction.Plasmodium falciparum malaria is responsible for 1 to 2 million deaths per year, with most in sub-Saharan Africa [1]. One unexplained but consistent feature of the epidemiology of clinical malaria is the age distribution of syndromes of severe disease. Severe anemia is most common in are
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