I am working on a project to convert some SAS code to R code as an on-line addendum to a published book (http://www.montana.edu/mtcfru/Guy/AIFFD.html).  For the most part this has been fairly straightforward.  However, I do not have much experience, and I am currently struggling to learn, with mixed-effects models.  As a hope to create a conversion from SAS to R that I can learn from, I have been attempting to work with the following situation.

Numbers of fish in two size categories were captured on one lake, over a nine year period (variable YEAR), at 12 fixed sites (variable SITE) each year.  A management regulation was implemented during the nine-year sampling period such that the years have been categorized as either "APRE" (before the regulation) or "BPOST" (after the regulation) (variable PERIOD).  The total number of fish in both size categories have been summed (variable TOTAL) and the log ratio of the number of fish in each size category has been created (variable LOGIT).  PERIOD, YEAR, and SITE are factor variables, LOGIT is a continuous quantitative variable, and TOTAL is a discrete quantitative variable.  The ultimate goal is to determine if mean LOGIT differed between periods (i.e., does the "ratio" of the two size categories differ from before to after the implementation of the regulation).

I would consider PERIOD to be a fixed effect, YEAR to be random, and there to be a lack of independence from year-to-year of LOGIT and TOTAL at each SITE.

The SAS PROC MIXED code that I am trying to convert is

PROC MIXED;
CLASS PERIOD YEAR SITE;
MODEL LOGIT=PERIOD;
WEIGHT TOTAL;
RANDOM YEAR(PERIOD);
REPEATED YEAR/SUBJECT=SITE TYPE=AR(1);
RUN;

I have tried various "things" in lme() from the nlme package but to no real success (defined as either re-creating something close to the SAS output or convincing myself that I knew what I was doing).

If someone has the time and inclination to help me set up lme() code (I assume that that is the most appropriate function) for this situation I would be very thankful.  Thank you in advance for any help you can offer.

	[[alternative HTML version deleted]]


