On Improving Precision of  A Repeated Measures Analysis of Variance

Adetutu, O. M.; Umar, A. E.; Lanlege, D. I.

Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/16360

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DC Field	Value	Language
dc.contributor.author	Adetutu, O. M.	-
dc.contributor.author	Umar, A. E.	-
dc.contributor.author	Lanlege, D. I.	-
dc.date.accessioned	2022-12-31T10:08:02Z	-
dc.date.available	2022-12-31T10:08:02Z	-
dc.date.issued	2014-06-06	-
dc.identifier.citation	ARPN Journal of Science and Technology, 4(6) pp.365-370.	en_US
dc.identifier.issn	2225-7217	-
dc.identifier.uri	http://repository.futminna.edu.ng:8080/jspui/handle/123456789/16360	-
dc.description.abstract	This paper investigates the use of repeated measures analysis of variance (RMANOVA) in analyzing repeated measurements. We focus on how serial auto correlation of repeated measures data can be removed in order to improve the validity of decision on repeated measures since this is widely used tool of applied statistician because its users are confronted with what seems to be a myriad of decisions, even in its simple application. In this study, the higher order interactions are used as error1 and error2 in order to improve the precision of our result. Ten (10) data sets were used to justify this paper and the computation was done with the aid of Statistical Package for Social Sciences (SPSS). The test on the overall estimates was significant at 95%	en_US
dc.language.iso	en	en_US
dc.subject	autocorrelation	en_US
dc.subject	between-subject	en_US
dc.subject	covariance	en_US
dc.subject	interaction	en_US
dc.subject	measures	en_US
dc.subject	within-subject	en_US
dc.title	On Improving Precision of A Repeated Measures Analysis of Variance	en_US
dc.type	Article	en_US
Appears in Collections:	Statistics

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