R help - Apr 2005 - A question on the library lme4

Hi,

I ran the following model using nlme:

model2<-lme(log(malrat1)~I(year-1982),random=~1|Continent/Country,data=wbmal10)

I'm trying to run a Poisson GlMM to avoid the above transformation but I 
don't know how to specify the model using lmer in the lme4 library:

model3<-lmer((malrat1)~I(year-1982) + ??,data=wbmal10,family=poisson)

How can I introduce a random factor of the form= ~1|Continent/Country?

Thanks;

-- 
Luis Fernando Chaves

Luis Fernando Chaves asks:

: -----Original Message-----
: From: r-help-bounces at stat.math.ethz.ch 
: [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Luis 
: Fernando Chaves
: Sent: Sunday, 24 April 2005 11:29 AM
: To: R-help at R-project.org
: Subject: [R] A question on the library lme4
: 
: 
: Hi,
: 
: I ran the following model using nlme:
: 
: model2 <- lme(log(malrat1) ~ I(year-1982), 
: random = ~1|Continent/Country, data=wbmal10)
: 
: I'm trying to run a Poisson GlMM to avoid the above 
: transformation but I 
: don't know how to specify the model using lmer in the lme4 library:
: 
: model3 <- lmer((malrat1) ~ I(year-1982) + ??, 
: data=wbmal10, family=poisson)

(I asked the same question of Doug Bates, as it happens.)

Try the following:

wbmal10 <- transform(wbmal10, Cont_Country = Continent:Country)
require(lme4)
model3 <- lmer(malrat1 ~ I(year - 1982) + (1|Continent)
		+ (1|Cont_Country), family = poisson, data = wbmal10)

: 
: How can I introduce a random factor of the form= ~1|Continent/Country?
: 
: Thanks;
: 
: -- 
: Luis Fernando Chaves
: 
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:

Luis Fernando Chaves wrote:
> Hi,
> 
> I ran the following model using nlme:
> 
>
model2<-lme(log(malrat1)~I(year-1982),random=~1|Continent/Country,data=wbmal10)
> 
> I'm trying to run a Poisson GlMM to avoid the above transformation but
I
> don't know how to specify the model using lmer in the lme4 library:
> 
> model3<-lmer((malrat1)~I(year-1982) + ??,data=wbmal10,family=poisson)
> 
> How can I introduce a random factor of the form= ~1|Continent/Country?
It depends on whether each Country has a unique label or not.  If they 
have unique labels then you simply use

model3 <- lmer(malrat1 ~ I(year-1982)+(1|Country)+(1|Continent), 
wbmal10, poisson)

If the Country factor is implicitly nested within Continent (e.g. the 
Country labels are "1", "2", ... and on each Continent they
start with
"1") then you must create a factor with unique levels by forming the 
interaction of Country and Continent as Bill Venables described in his 
reply.

In lmer there is no need, and indeed no way, to distinguish between 
nested and non-nested grouping factors for random effects.  Because of 
this you cannot use implicit nesting.