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Table 3 Estimates of the generalized linear mixed models on the probability of generic and branded substitution

From: Analyzing generic and branded substitution patterns in the Netherlands using prescription data

  Generic substitution Branded substitution
  Log Odds (β) P-value Log Odds (β) P-value
Fixed effects estimates     
Intercept 4.262 < 0.001 -6.978 < 0.001
Prescriptions to female patients -0.163 0.284 0.095 0.391
First prescription in the drug class -2.582 < 0.001 2.752 < 0.001
Prescription history 0.076 < 0.001 0.016 0.361
Branded ratio     
Branded ratio [0 - 0.33) baseline
Branded ratio [0.33 - 0.66) -3.210 < 0.001 2.960 < 0.001
Branded ratio [0.66 - 1] -5.952 < 0.001 5.809 < 0.001
Pharmacy property status     
Individually owned pharmacy baseline
Pharmacy in a partnership 0.954 0.046 -1.752 < 0.001
Pharmacy in a chain 0.687 < 0.001 -0.605 < 0.001
Duration after patent expiry (months) -0.011 0.002 -0.046 < 0.001
Age     
Age [16-31] baseline
Age (31-46] 0.568 < 0.007 -0.399 0.038
Age (46-52] 0.546 0.012 -0.146 0.307
Age (52-88] 0.474 0.028 -0.153 0.262
Drug group     
   ACE Inhibitors baseline
   Antidepressants -0.579 0.004 1.846 < 0.001
   PPIs -1.085 < 0.001 0.986 < 0.001
   Statins 0.574 0.001 -0.634 < 0.001
Random effects estimates     
Pharmacy-level residual variance 1.915 0.350
Patient- level residual variance 2.346 1.879
Somers D xy criterion 0.985 0.981