SmileDomain <enthumelon@[EMAIL PROTECTED]
> wrote:
> I will take an example to explain what have prevented me from doing
> an estimate.
> the form of data I receive can be described as the following table:
> GENE I GENE II
> study Type AA AG GG TT TG GG
> 1 case c11 c12 c13 k11 k12 k13
> control t11 t12 t13 l11 l12 l13
> 2 case...
> cnotrol...
> First of all, HWE(Hardy-Weinberg Equilibrium) should be checked. But
> in this case, the Chi-2 statistic of study 2(GENE I control ONLY) is
> 7.3, almost 3 times of chi-2(90%)=2.7. This is rather strange. (Maybe
> the missing data do effects the result greatly.)
> Besides, as most researchers do, I use Q-statistic to do a test about
> the heterogeneity of the two study in my work. But Q-statistic is not
> a good choice when the numer of study is too small.
> These days I am trying to use Random Effects Model to finish my
> thesis. I hope it can work. Can someone give a sugguestion?
Are the two study samples from greatly different populations ethnically?
Are
allele frequencies in controls in the two studies comparable? You
test HWE because it may i) reflect laboratory error ii) population
substructure etc.
If you are happy that i) is not the case, "statistically significant"
disequilibrium
may not be large enough to prevent valid inferences about gene-disease
association and interstudy differences ie go ahead and fit a log-linear
model
to the 2x3x2 table.
David Duffy.
--
| David Duffy (MBBS PhD) ,-_|\
| email: davidD@[EMAIL PROTECTED]
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
|
