Dear all,
I have a dataset of fish collected in different rivers over different years each of them sampled a different number of times during different projects . This different number of observations among rivers in some cases can be important: e.g.
River X = 1 project (1 observation=1 sampling x 1 year);
River Y = 5 projects (15 observations= 1 sampling x 3 years x 5 projects);
River Z= 15 projects (105 observations=1 sampling x 7 years x 15 projects);
I want to calculate in the all region (so not interested in specific rivers) how the abundance is related to Years, Latitude, Altitude and Anthopic pressures (APindex). I thought to use the following model:
lme: Abu~Years+Latitude+Altitude+APindex + (1|river/project) + corrARMA (form = time|River/project).
-What is the influence of RiverZ with its 105 observation compared to the other rivers which have less number of observations?
-Am I accounting for this unbalanced observations in the random structure (1|river/project)?
-Do I have to account in the model for the different number of observations with (weight=1/n observation for each project?)
Thank you
Pure ANOVA is not good for an unbalanced study, but GLM (regression) is okay. Or the Brown-Forsyth test for skewed data. See: Analysis of Unbalanced Data by Mixed Linear Models using the mixed Procedure of the SAS System, DOI: 10.1111/j.1439-037X.2004.00120.x
- Badges
- Science method
- Similar topics
- Biological Science
- Ecology