Pub Date : 2019-01-01DOI: 10.16929/ajas/2019.589.232
M. Somda, Do Edmond Sanou, A. Soubeiga, J. Sawadogo
{"title":"Developing an area-based sampling system in the urban district of Bobo Dioulasso, Burkina Faso","authors":"M. Somda, Do Edmond Sanou, A. Soubeiga, J. Sawadogo","doi":"10.16929/ajas/2019.589.232","DOIUrl":"https://doi.org/10.16929/ajas/2019.589.232","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121025551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.16929/AJAS/2019.649.236
A. Lawal, O. O. Alaba
{"title":"Exploratory Analysis of Some Sectors of the Economy : A Seemingly Unrelated Regression Approach","authors":"A. Lawal, O. O. Alaba","doi":"10.16929/AJAS/2019.649.236","DOIUrl":"https://doi.org/10.16929/AJAS/2019.649.236","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126848359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.16929/AJAS/2019.519.228
O. Oladuti, B. Oyejola
{"title":"Modelling Clustered Survival Data with Competing Risk","authors":"O. Oladuti, B. Oyejola","doi":"10.16929/AJAS/2019.519.228","DOIUrl":"https://doi.org/10.16929/AJAS/2019.519.228","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.16929/AJAS/2019.635.235
Michael J. Adjabui, E. D. Kpeglo, Christian Hesse Akrongh
{"title":"Identifying maximum safe dose( MSD) in a (k+2)-arm trial under unequal variances","authors":"Michael J. Adjabui, E. D. Kpeglo, Christian Hesse Akrongh","doi":"10.16929/AJAS/2019.635.235","DOIUrl":"https://doi.org/10.16929/AJAS/2019.635.235","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134066296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gbénakpon Aubin Yamonwan Guénolé Amagnide, R. G. Kakaï
{"title":"Fitting an optimal variance-covariance structure for longitudinal data under linear mixed effects models framework: simulation based analysis","authors":"Gbénakpon Aubin Yamonwan Guénolé Amagnide, R. G. Kakaï","doi":"10.16929/ajas/489.226","DOIUrl":"https://doi.org/10.16929/ajas/489.226","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117106579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayesian inference approach in modeling and forecasting maize production in Rwanda","authors":"D. Ndanguza, Denise Uwamariya","doi":"10.16929/AJAS/503.227","DOIUrl":"https://doi.org/10.16929/AJAS/503.227","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123157234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the levels and determinants of desired and actual number of children, and the risk of having more than two children in Ghana and Nigeria using 2013 and 2014 Demographic Health Survey (DHS) conducted in the two countries, respectively. The question is whether the rate of childbearing in sub-Saharan African countries can be slowed down by changes in fertility demand-driven factors such as economic, socio-cultural and family planning programs. Our analysis results showed that these two countries are yet to adopt replacement level policy. Thus, putting every socio-demographic conditions that support fertility in place, these sub-Saharan African countries will continue to increase average childbearing per household, particularly in the case of Nigeria. Thus, government could intervene in the area of education of mothers since this will delay the age at first birth and serve as avenue to orientate women on family planning measures.
{"title":"Determinants of Desired and Actual Number of Children and the Risk of having more than Two Children in Ghana and Nigeria","authors":"O. S. Yaya, Olawale D. Osanyintupin","doi":"10.16929/AJAS/403.222","DOIUrl":"https://doi.org/10.16929/AJAS/403.222","url":null,"abstract":"This paper investigates the levels and determinants of desired and actual number of children, and the risk of having more than two children in Ghana and Nigeria using 2013 and 2014 Demographic Health Survey (DHS) conducted in the two countries, respectively. The question is whether the rate of childbearing in sub-Saharan African countries can be slowed down by changes in fertility demand-driven factors such as economic, socio-cultural and family planning programs. Our analysis results showed that these two countries are yet to adopt replacement level policy. Thus, putting every socio-demographic conditions that support fertility in place, these sub-Saharan African countries will continue to increase average childbearing per household, particularly in the case of Nigeria. Thus, government could intervene in the area of education of mothers since this will delay the age at first birth and serve as avenue to orientate women on family planning measures.","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"414 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115994850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling of nonstationarity and long memory with RS-ARFIMA-GARCH model","authors":"S. Fofana, A. Diop, O. Hili","doi":"10.16929/ajas/469.225","DOIUrl":"https://doi.org/10.16929/ajas/469.225","url":null,"abstract":"","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127484848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extreme value analysis in the presence of censoring is receiving much attention as it has applications in many disciplines, including survival and reliability studies. Estimation of extreme value index (EVI) is of primary importance as it is a critical parameter needed in estimating extreme events such as quantiles and exceedance probabilities. In this paper, we review several estimators of the extreme value index when data is subject to random censoring. In addition, four estimators are proposed, one based on the exponential regression approximation of log spacings, one based on a Zipf estimator and two based on variants of the moment estimator. The proposed estimators and the existing ones are compared under the same simulation conditions. The performance measures for the estimators include confidence interval length and coverage probability. The simulation results show that no estimator is universally the best as the estimators depend on the size of the EVI parameter, percentage of censoring in the right tail and the underlying distribution. However, certain estimators such as the proposed reduced-bias estimator and the adapted moment estimator are found to perform well across most scenarios. Moreover, we present a bootstrap algorithm for obtaining samples for extreme value analysis in the context of censoring. Some of the estimators that performed well in the simulation study are illustrated using a practical dataset from medical research
{"title":"On Extreme Value Index Estimation under Random Censoring","authors":"R. Minkah, T. Wet, K. Doku-Amponsah","doi":"10.16929/ajas/419.223","DOIUrl":"https://doi.org/10.16929/ajas/419.223","url":null,"abstract":"Extreme value analysis in the presence of censoring is receiving much attention as it has applications in many disciplines, including survival and reliability studies. Estimation of extreme value index (EVI) is of primary importance as it is a critical parameter needed in estimating extreme events such as quantiles and exceedance probabilities. In this paper, we review several estimators of the extreme value index when data is subject to random censoring. In addition, four estimators are proposed, one based on the exponential regression approximation of log spacings, one based on a Zipf estimator and two based on variants of the moment estimator. The proposed estimators and the existing ones are compared under the same simulation conditions. The performance measures for the estimators include confidence interval length and coverage probability. The simulation results show that no estimator is universally the best as the estimators depend on the size of the EVI parameter, percentage of censoring in the right tail and the underlying distribution. However, certain estimators such as the proposed reduced-bias estimator and the adapted moment estimator are found to perform well across most scenarios. Moreover, we present a bootstrap algorithm for obtaining samples for extreme value analysis in the context of censoring. Some of the estimators that performed well in the simulation study are illustrated using a practical dataset from medical research","PeriodicalId":332314,"journal":{"name":"African Journal of Applied Statistics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129303939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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