I am beginner in using the linear mixed-effect model (lme4). I tried the following to fit three factors (fixed effect)and one factor (farm) as random. I got the output but failed to interpret it specially the estimates. Can you help? for what parameters the estimates belongs?
fit1 <- lmer(GY ~ fertseasden+(1|farm) , data = cr)
summary(fit1) Linear mixed model fit by REML. t-tests use Satterthwaite's method [ lmerModLmerTest] Formula: GY ~ fert * seas * den + (1 | farm) Data: cr
REML criterion at convergence: 407.9
Scaled residuals: Min 1Q Median 3Q Max -1.8708 -0.7313 -0.2015 0.5301 2.9092
Random effects:
Groups Name Variance Std.Dev.
farm (Intercept) 0.135 0.3674
Residual 1.595 1.2628
Number of obs: 126, groups: farm, 3
Fixed effects: Estimate Std. Error df t value Pr(>|t|) (Intercept) 4.4256 0.4360 20.2216 10.149 2.2e-09 *** fertRDFU 0.4909 0.5385 112.0677 0.912 0.36390 fertWOF -0.8364 0.5385 112.0677 -1.553 0.12319 seas2018 -1.6264 0.5531 112.3667 -2.941 0.00398 ** den53,333 1.6909 0.5385 112.0677 3.140 0.00216 ** fertRDFU:seas2018 -0.8209 0.7803 112.0677 -1.052 0.29506 fertWOF:seas2018 -0.3336 0.7803 112.0677 -0.428 0.66979 fertRDFU:den53,333 -0.2273 0.7615 112.0677 -0.298 0.76591 fertWOF:den53,333 -0.6909 0.7615 112.0677 -0.907 0.36621 seas2018:den53,333 -1.6109 0.7803 112.0677 -2.064 0.04129 * fertRDFU:seas2018:den53,333 0.3899 1.1038 112.0990 0.353 0.72461 fertWOF:seas2018:den53,333 0.8609 1.1035 112.0677 0.780 0.43696
Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1
