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dc.contributor.authorOyeyemi, G.M.-
dc.contributor.authorAdewara, A.A.-
dc.contributor.authorAdeyemi, R. A.-
dc.date.accessioned2021-06-20T21:38:57Z-
dc.date.available2021-06-20T21:38:57Z-
dc.date.issued2010-
dc.identifier.citationOyeyemi, G.M., Adewara, A.A. and Adeyemi, R.A. (2010). Complex Survey Data Analysis: A Comparison of SAS, SPSS and STATA. Asian Journal of Mathematics & Statistics, 3: 33-39.en_US
dc.identifier.issn1994-5418-
dc.identifier.uriURL: https://ansinet.com/abstract.php?doi=ajms.2010.33.39-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/4167-
dc.descriptionAnalyzing Complex Survey data Using three statistical packages (SAS, SPSS and STATA)en_US
dc.description.abstractWe 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 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 endogenous.en_US
dc.description.sponsorshipSelf Sponsoreden_US
dc.language.isoenen_US
dc.publisherAsian Journal of Mathematics and Statistics (ANSI)en_US
dc.subjectClusteringen_US
dc.subjectcomplex surveyen_US
dc.subjectSampling weightsen_US
dc.subjectStandard erroren_US
dc.titleComplex Survey Data Analysis: A Comparison of SAS, SPSS and STATAen_US
dc.typeJournal Articleen_US
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