I am doing a study that I would like to analyze data with a mixed effect model. I have three fixed effects and one random effect. My code output is seems a bit off and I am unsure if it is a structural problem with the code, or multicoliniarity in my data. I have tried testing fpr coliniarity, but haven't gotten the code to work (I think because I have mostly catagorical data)
Fixed Effects:
soil_type - 2 groups ("Medium" and "Fine")
treatment - 4 groups ("L", "S", "K", "C")
days - 3 sampling points (day 4, 11, 18)
Random Effect:
replicates - 3 groups (1,2,3)
My code is as followed:
cl.mod <- lmer(weighted_cl ~ soil_type + treatment + days + (1|rep),
data = leach.conc, REML = FALSE)
I believe I have the correct code, but when I look at the output I am unsure if I am missing values:
Fixed effects:
Estimate Std. Error t value
(Intercept) 7.01992 1.65258 4.248
soil_typeMedium -4.81518 1.05431 -4.567
treatmentKCl 10.48391 1.49103 7.031
treatmentLiquid 25.25578 1.49103 16.939
treatmentSolid 8.31138 1.49103 5.574
days -0.32534 0.09223 -3.527
Correlation of Fixed Effects:
(Intr) sl_tyM trtmKC trtmnL trtmnS
soil_typMdm -0.319
treatmntKCl -0.451 0.000
treatmntLqd -0.451 0.000 0.500
treatmntSld -0.451 0.000 0.500 0.500
days -0.614 0.000 0.000 0.000 0.000*
I am unsure if this is because I have multicoliniarity in my data or if I have my code incorrect (or both). Because this is catagorical data, I am unsure about testing for coliniarity. Also, I have no missing values in my data. Any guidance or things to look at would be greatly appreciated!