I would like some feed back on an analyis I have been running in R. Its the first time I have run such a model in R and just wonder if its the correct choice.

My study involves bugs collected at three sites (6 replicates at each site) up and downstream of an impact.

I believe that the sites are considered a random effect and location (up or downstream) is a fixed effect, thus a mixed effect model. The sites, because not located in each location are therefore nested in location.

My R code is below.

The summary provides a responable output, but I dont think its nesting site with location.

Can any one offer some advice regarding the model? and still I struggle with the interpretation of the intercept in the output - shed some light some one?

ResLmeriff<-lme(OE50~Location,random=~1|Site/Location,data=riff)

summary(ResLmeriff)

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OUTPUT

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inear mixed-effects model fit by REML

Data: riff

AIC BIC logLik

-33.46531 -25.83350 21.73265

Random effects:

Formula: ~1 | Site

(Intercept)

StdDev: 0.08016658

Formula: ~1 | Location %in% Site

(Intercept) Residual

StdDev: 0.08016658 0.03006247

Fixed effects: OE50 ~ Location

Value Std.Error DF t-value p-value

(Intercept) 0.8205263 0.02690834 34 30.493388 0.000

Locationu 0.0177090 0.03915738 34 0.452251 0.654

Correlation:

(Intr)

Locationu -0.687

Standardized Within-Group Residuals:

Min Q1 Med Q3 Max

-0.60800837 -0.12725757 -0.08855936 0.15181604 0.39219145

Number of Observations: 36

Number of Groups:

Site Location %in% Site

36 36

Thansk for any help

Phil