[R-sig-ME] R-sig-mixed-models Digest, Vol 32, Issue 24
David.Duffy at qimr.edu.au
Tue Aug 25 10:06:19 CEST 2009
On Sun, 23 Aug 2009, David Evans wrote:
> David, would it be possible to help me with some references on using
> Gaussian errors for binary data which you mention below. I've read the
> Paper by Cheung, A modified least-squares regression approach to the
> estimation of risk difference, AJE 2007, 166:1337-1344 but was hoping to
> find some more on this. In particular, any references which say
> Gaussian errors are acceptable in mixed models would be most appreciated
> (I have an outcome prevalence in the 0.2's).
A couple of reviews defending the general idea ;):
Harvey WR (1982). Least-squares analysis of discrete data. J Anim Sci
Ch 17 in Gianola and Hammond Advances in Statistical Methods for
Genetic Improvement of Livestock.
The latter suggests:
V. Guiard, G. Herrend Ãrfer, A. Tuchscherer (1985). Variance Component
Estimation for Dichotomous Characters and Its Use for Estimating
Heritability. Biometric J 27: 653-658.
The heritability is the proportion of variance due to genetic random
A couple of genetics example I am aware of, where simulation finds that
the linear model gives similar answers to a GLMM or similar:
Visscher PM, Haley CS, Knott SA (1996). Mapping QTLs for binary traits
in backcross and F2 populations. Genetical Research 68(1):55-63.
Zeegers MP, Rice JP, Rijsdijk FV, Abecasis GR and Sham PC (2003).
Regression-based sib pair linkage analysis for binary traits.
Hum Hered 55:125-31
There are many other applications of the approach in the animal
breeding literature for heritability estimation.
But I'm afraid these merely support the approach in general - they
haven't usually applied a standard program like lme()/lmer(), but I
think one can argue that the same analysis of variance machinery is
being used. The literature on binary intraclass/interclass correlations
in cluster sampling etc (Landis and Koch onwards) is also relevant.
Lunney GH (2005). Using analysis of variance with a dichotomous
dependent variable: an empirical study. J Educ Meas 7:263-269.
Cheers, David Duffy.
| David Duffy (MBBS PhD) ,-_|\
| email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v
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