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Incorrect F-statistic to test nonhomogeneous hypothesis in bivariate regression analysis

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dc.contributor.author Rahman, Mohammad Lutfur
dc.date.accessioned 2010-10-18T05:46:07Z
dc.date.available 2010-10-18T05:46:07Z
dc.date.issued 2005
dc.identifier.uri http://hdl.handle.net/10361/540
dc.description.abstract In Regression analysis, an F test can be viewed as a comparison between a full and a restricted model. The most general F formula compares the error sums of squares (SSE’s) of these two models. This F formula is always correct because the SSE comparison is meaningful in all tests. Other formulas use the corrected model sum of squares (SSM) or the coefficient of determination (R2) to compare the full and restricted models. This article gives several examples where the SSM’s or R2’s of the two models cannot be compared, and hence where the use of F formulas based on SSM or R2 would be incorrect. This problem usually arises in tests of nonhomogeneous hypotheses, although it may also appear in other situation. en_US
dc.language.iso en en_US
dc.publisher BRAC University en_US
dc.relation.ispartofseries BRAC University Journal, BRAC University;Vol.2, No.2,pp. 35-38
dc.subject Coefficient of determination en_US
dc.subject Full model en_US
dc.subject Linear model en_US
dc.subject Reparametrization en_US
dc.subject Restricted model. en_US
dc.title Incorrect F-statistic to test nonhomogeneous hypothesis in bivariate regression analysis en_US
dc.type Article en_US


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