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Table 3 The generalised estimating equation analysis of reimbursement ratio

From: Medical expenditure for patients with hemophilia in urban China: data from medical insurance information system from 2013 to 2015

Parameter B Std.Error 95% wald confidence Internal hypothesis test
Lower Upper wald chi-square df p-value
intercept 11.876 8.858 −5.486 29.238 1.797 1 0.180
[region = 1] 21.074 3.556 14.104 28.043 35.124 1 0.000
[region = 2] 10.397 3.511 3.516 17.278 8.770 1 0.003
[region = 3] 0a       
[gender = 1] 38.345 7.054 24.519 52.170 29.549 1 0.000
[gender = 2] 0a       
age −2.587 2.046 −6.598 1.424 1.598 1 0.206
[types of BMI = 1] 15.129 3.252 8.756 21.503 21.649 1 0.000
[types of BMII = 2] 0a       
[grades of medical institution = 0] 7.901 3.409 1.219 14.583 5.371 1 0.020
[grades of medica linstitution = 1] 15.348 3.952 7.602 23.093 15.083 1 0.000
[grades of medica linstitution = 2] −0.060 3.004 −5.948 5.828 0.000 1 0.984
[grades of medical institution = 3] 0a       
[types of medical service = 1] −3.431 2.951 −9.214 2.353 1.352 1 0.245
[types of medical service = 2] 0a       
medical expenses 0.000 0.000 0.000 0.001 2.844 1 0.092
scale 687.056