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*To*: gilmoua@ornsun.agric.nsw.gov.au*Subject*: Re: And now what?*From*: "Haja Kadarmideen" <h.kadarmideen@ed.sac.ac.uk>*Date*: Mon, 30 Nov 1998 16:12:55 GMT*CC*: asreml@ram.chiswick.anprod.csiro.au*In-reply-to*: <199811270309.OAA29950@ornsun.agric.nsw.gov.au>*Organization*: Scottish Agricultural College*Priority*: normal*Sender*: owner-asreml@chiswick.anprod.csiro.au

Dear Arthur and ASREML members, I am new to this list so my apologies if the following questions have been already discussed. I have two questions: One about transformation and other about convergence problem. 1. Since Hugo used logit (default) link function, I wonder if zz/pq transformation is still correct. Isn't this formula used for converting estimates on the underlying Normal scale to the observed probability scales or vice versa? Please correct me if I am wrong or if I missed something in the earlier discussions. Factor, pi / sqrt(3), seems to approximate logistic and normal distributions. Do we use this factor to convert estimates on logit scale to normal scale first (both on the underlying scale) and then use zz/pq to transform Normal estimates (transformed) to observed prob.scale ? If the later was the right approach, how to transform parameter estimates (h2, rg or rp ), on logit scale to Normal scale first ? Do we just multiply estimates (h2,rg,rp) by pi/sqrt(3) ? 2. My second question relates to convergence problem on the binomial data (coded as 0 or 1) analysis using univariate animal model. I first checked and removed fixed effect sub-classes that had 0 % or 100% incidence for the 0/1 trait, as likelihood in these cases is not defined (infinity on the underlying scale and therefore it keeps diverging ?). I could have changed the model though, to avoid too many "all" or "zero" sub-classes, but is neccessary/preferable to keep the existing model in my analysis. Is it neccessary to do the "above" data editing in ASREML to meet convergence ? - After removing observations that fall under "uninformative" fixed effect sub-classes, I used logit and probit link functions. Convergence was acheived for the logit link (in iteration 10 or so) but not for the Probit link function (until iteration 20). Why ? It is due to the fact that numerical integration is easeir on logitic scale than on Normal scale or is it due to something else I didn't do properly ? I used !GU - "unconstrained" option in both cases as default, !GP did not work on both logit and probit link functions. I did not examine solutions but tried with a few different starting values for variance ratio. I am still tring to acheive convergence with probit link. I'd appreciate your help and/or suggestions. Many Thanks Haja The normal nexty step would be to transform from the underlying scale to the p scale using zz/pq where p is the average incidence, q=(1-p) and zz is z-squared where z is the ordinate of the Normal curve corresponding to the proportion. So if p=0.5, z=..399 and the factor is .64 H2 on the underlying scale is .499917/1.499917 = .3333 so h2 on the p scale is 0.21 You can get the variance of h2 from asreml (.pin file) and scale it similarly. Arthur <nofill> -------------------------------------------------- Dr. Haja Kadarmideen Animal Biology Division SAC Bush Estates Penicuik, Midlothian EH26 0PH Scotland, UK Telephone: +44 0131 535 3246 Fax : +44 0131 535 3121 e-mail : h.kadarmideen@ed.sac.ac.uk --------------------------------------------------

**References**:**Re: And now what?***From:*Arthur Gilmour <gilmoua@ornsun.agric.nsw.gov.au>

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