After fitting a linear mixed effect model with lme, I run a posthoc analysis with glht and get the following results:
Simultaneous Tests for General Linear Hypotheses Fit: lme.formula(fixed = data ~ des_days * muscle, data = data_emg_trf, random = ~des_days | ratID/cycle, method = "ML", na.action = na.omit, control = lCtr) Linear Hypotheses: Estimate Std. Error z value Pr(<z) muscleVM + des_days1:muscleVM = 0 -0.152947 0.003203 -47.752 < 2e-16 *** muscleVM + des_days9:muscleVM = 0 -0.100683 0.003531 -28.511 < 2e-16 *** muscleVM + des_days45:muscleVM = 0 -0.026425 0.003311 -7.981 2.22e-15 ***
Estimations and standard errors make sense if I compare them with a plot of the data. However, I am worried about the very small p-values, close to eps. Is it suspicious or it could be real? What could the problem be? Thanks!