[R-sig-ME] Rules of thumb for model complexity with small sample size in lme()
jludlam at fitchburgstate.edu
Wed Apr 4 15:55:05 CEST 2018
I have an experiment with six streams in two groups (regulated and control). At each stream there were five sites (Transect). At each site there were unreplicated nutrient treatments (N, P, N+P, C). Light was measured at each site.
Stream Regulated Transect Nitrogen Phosphorus R Light
Cranberry Regulated 30 C C -0.102512563 2042.266667
Cranberry Regulated 30 C P -0.08877551 2042.266667
Cranberry Regulated 50 C C -0.107142857 1283.3
Cranberry Regulated 50 N C -0.059375 1283.3
Cranberry Regulated 70 C C -0.067346939 1336.6
Cranberry Regulated 70 N C -0.063636364 1336.6
I would like to know if the response differs among groups (regulated vs control) or is related to light or nutrient treatment. I have two separate analyses, N = 107 and N = 66 with different numbers of missing values (N = 120 before missing values).
I think the appropriate model structure is:
lme(Response ~ Regulated + Light + Nitrogen + Phosphorus + Nitrogen:Phosphorus), random=~1|Stream/Transect, data=data, method="ML"))
However, I'm concerned that the model is far too complex for my sample size. Any advice would be appreciated!
John P. Ludlam, Ph.D. - Fitchburg State University
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