I am trying a mixed model in R (lme4). The objective is to evaluate the average glucose level of patients in a hospital is decreasing in the last four years. The model is simple that glucose values are predicted from year of glucose measurement (year1, year2, year3 and year4) (year), number diabetes education appointment taken by the patient in the year (edu_appt) and time in months between the first appointment of the patient with the clinic and date of lab test done (months). Interaction term was introduced between edu_appt and the months to find out if there is any effect of education appointments in the long run..
Following is the result
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 8.167e+00 5.692e-02 1.292e+03 143.488 < 2e-16 ***
year2second 2.390e-01 4.921e-02 7.176e+03 4.857 1.22e-06 ***
year3third 5.843e-01 8.192e-02 7.164e+03 7.133 1.08e-12 ***
year4fourth 8.654e-01 1.153e-01 7.164e+03 7.506 6.84e-14 ***
edu_appt 4.966e-02 6.616e-03 7.630e+03 7.505 6.84e-14 ***
months -2.298e-02 3.040e-03 7.168e+03 -7.560 4.51e-14 ***
edu_appt:months -1.402e-03 2.409e-04 7.304e+03 -5.819 6.16e-09 ***
Here if you notice, the estimate of edu_appt is possitve but when I add the interaction term months which is the duration between first_appt and hba1c measuremnt, It turned out to be negative. Can someone please tell me how do interpret this model.
nlme::lme, notlme4::lmer(not that it's very relevant) – Ben Bolker Jan 18 '16 at 13:26