[R] using subset command in glm and glm coefficients output

[Courtney Coon]

I am a graduate student who's just starting to use more advanced
statistics and is completely new to R.  I'm looking for whether
parasite prevalence varies with region.  I'd like to try using just a
subset of the data defined by one these covariates, sex, looking at
data only from adults, without using it as a covariate in the
analyses.  I tried using subset=sex=='A' in the following context:
malaria1<-glm(Malaria ~ X2sppclass+place+place*X2sppclass,
subset=sex=='A', na.action=na.omit, family=binomial(link="logit""))
with sex being the column name and 'A' standing for adult but R
doesn't seem to like that.  It says there is an unexpected '=' but
that's how I found it coded in other R forums.

Because I couldn't get the above code to work, I ended up running the
following model:
malaria2<-glm(Malaria ~ X2sppclass+place+place*X2sppclass,
na.action=na.omit, family=binomial(link='logit'))
but I don't understand the summary output for the coefficients:

Coefficients: (2 not defined because of singularities)
                     Estimate Std. Error z value Pr(>|z|)
(Intercept)            12.9786   624.1941   0.021   0.9834
X2sppclassH           -12.4375   624.1941  -0.020   0.9841
X2sppclassN           -12.5512   624.1940  -0.020   0.9840
placeEast               1.3304     0.5870   2.266   0.0234 *
placeWest               1.5875     0.5468   2.903   0.0037 **
X2sppclassH:placeEast   0.9532     0.7325   1.301   0.1931
X2sppclassN:placeEast       NA         NA      NA       NA
X2sppclassH:placeWest   0.2992     0.7218   0.414   0.6785
X2sppclassN:placeWest       NA         NA      NA       NA

issue 1: the error "2 not defined because of singularities" even
though I know there are multiple individuals that are 'N' and from the
East or West.
issue 2: It never gives any output for placeCentral.  Is this because
I'm using a binomial function and one of my predictors (place) is not
binomial?

Thanks for any help.
--
Courtney Coon
PhD candidate
Department of Integrative Biology
University of South Florida
4202 E. Fowler Ave., SCA 110
Tampa, FL 33620-5200
813-974-0157