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*To*: yzhang@metz.une.edu.au*Subject*: Re: fixed effects*From*: Arthur Gilmour <gilmoua@ornsun.agric.nsw.gov.au>*Date*: Fri, 10 Jul 1998 15:59:58 +1000 (EST)*Cc*: asreml@ram.chiswick.anprod.csiro.au*Reply-To*: Arthur Gilmour <gilmoua@ornsun.agric.nsw.gov.au>*Sender*: owner-asreml@chiswick.anprod.csiro.au

> > Dear ASREML user, > I am estimating sheep weaning weight data. Being curious, before getting a > final model, I tried fixed effects. Now my problem is how to fit birth > rank(brank), rearing rank(rrank) and the combined term birth/rear > rank(brrank). Following is the output for various order of these three > terms, model excluding random effects. > please explain to me: > why df of brrank changed cross models? > why f_inc and F_all of all three terms varied among models? > How these tree terms should be fitted as fixed effects? This is the classic effect of incomlete factorial classification. Evidently you have 5 Birth classes and 3 rearing classes giving a table with 15 cells. However, at least 3 are probably empty and you have not defined how brrank relates to brank and rrank so I can't give a complete explanation. Anyway, write down the 3 x 5 table and write down how amny in each cell. It may look like X X X X 0 0 X X X X 0 0 X X 0 where only 10 of the cells have values giving a total of 9 DF In every case where the 3 effects are fitted, you have a total of 9 df. Now, if BRANK fitted first, or after RRANK, it will have 4 df Also, if RRANK fitted first or after BRANK, it will have 2 df. Fitted after BRANK and RRANK, BRRANK can have only 3 df because that is all that is left. When BRRANK is fitted first, it takes 6 df ( 4 of which were previously allocated to BRANK) BRANK now only has 1 df. If you identify into which of the 7 BRRABK classes the 10 cells form, you will be able to see that they have picked out some of the BRANK classes. Furthermore, after fitting BRANK, either RRANK or BRRANK will explain most of whats left. However, RRANK does it best so you should probably fit just BRANK and RRANK. What is sometimes done is to define BRRANK as say 1 Born Single, Raised Single 2 Born Twin , Raised Single 3 Born Twin , Raised Twin 4 Born Triple+ ,Raised Single 5 Born Triple+ ,Raised Twin 6 Born Triple+ ,Triple+ and this then picks up most of the variation such that, as in your case, neither BRANK or RRANK explain any more. Grouping is based on numbers in a cell as well as expectation of similarirty. Applying this to the pattern above, X X X X 0 0 X X X X 0 0 X X 0 BRRANK picks up the difference between BORN SINGLE and BORN TWIN so For the pattern above, DF would be (In ASREML order with bottom term fitted first) RR 2 RR 2 BR 3 BR 2 BRR 3 BRR 3 BR 2 BRR 3 RR 2 BRR 5 RR 2 BR 4 BRR 5 BR 4 BRR 5 RR 2 BR 4 RR 2 It is aloso much easier to interpret one set of means rather than the combined effects of 3 nonorthogonal factors across a set of means. > > Thanks > Yuandan > Following is the digest of output > term DF F_inc F_all > model wwt= mu ... brrank brank rrank > 11 rrank 2 2.61 2.61 > 10 brank 1 0.08 0.38 > 9 brrank 6 73.78 8.39 > > 31 mu 1 59191.67 169.91 > > > model wwt= mu ... brank brrank rrank > 11 rrank 2 2.61 2.61 > 9 brrank 3 34.78 0.45 > 10 brank 4 84.60 9.76 > > 31 mu 1 59191.67 169.91 > > model wwt= mu ... brank rrank brrank > 9 brrank 3 0.45 0.45 > 11 rrank 2 54.09 2.61 > 10 brank 4 84.60 9.76 > 34 > 31 mu 1 59191.67 169.91 > > model wwt= mu ... rrank brank brrank > 9 brrank 3 0.45 0.45 > 10 brank 4 12.61 9.76 > 11 rrank 2 198.08 2.61 > > 31 mu 1 59191.67 169.91 > > model wwt= mu ... brrank > 9 brrank 6 73.65 73.65 > > 31 mu 1 59092.26 169.84 > > model wwt= mu ... brank > 10 brank 4 78.58 78.58 > > 31 mu 1 54977.57 157.48 > > model wwt= mu ... rrank > 11 rrank 2 191.79 191.79 > > 31 mu 1 57312.05 157.45 > > > > ************************************************************************ > Yuandan Zhang > > Department of Animal Science > University of New England > Armidale, NSW 2351, Australia > > Phone +61 + 2 + 6773 2756(Lab) > > > Fax +61 + 2 + 6773 3275 > E-mail yzhang@metz.une.edu.au > homepage http://metz.une.edu.au/~yzhang/ > ************************************************************************ > <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> Arthur Gilmour PhD email: Arthur.Gilmour@agric.nsw.gov.au Senior Research Scientist (Biometrics) fax: <61> 2 6391 3899 NSW Agriculture <61> 2 6391 3922 Orange Agricultural Institute telephone work: <61> 2 6391 3815 Forest Rd, ORANGE, 2800, AUSTRALIA home: <61> 2 6362 0046 ASREML is currently free by anonymous ftp from pub/aar on ftp.res.bbsrc.ac.uk Point your web browser at ftp://ftp.res.bbsrc.ac.uk/pub/aar/ in the IACR-Rothamsted information system http://www.res.bbsrc.ac.uk/ To join the asreml discussion list, send the message subscribe to asreml-request@chiswick.anprod.CSIRO.au The address for messages to the list is asreml@chiswick.anprod.CSIRO.au <> <> <> <> <> <> <> "The men marveled, saying 'Who can this be, that even the winds and the sea obey Him?'" Matthew 8:27 <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

**Follow-Ups**:**true BLUP***From:*Uilson V Lopes <wilsonvl@grove.ufl.edu>

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