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Table 3 Results of ordinary least squares linear regression analysis for predictors of stroke direct costs

From: Analysing and quantifying the effect of predictors of stroke direct costs in South Africa using quantile regression

Variable Coefficient (βj) 95% CI for βj P-value
Intercept 0.488 (0.450,0.490) <  0.0001
Age group 55–75 years 0.799 (0.698,0.809) <  0.0001
Age group 76–98 years 1.724 (1.700,1.735) <  0.0001
Female-gender 1.306 (1.300,1.310) <  0.0001
Indian/Asian-race 1.495 (1.417,1.505) <  0.0001
Black-race 1.837 (1.800,1.840) <  0.0001
Coloured-race 2.169 (−2.100,2.209) 0.987
Hypertension-yes 1.152 (1.100,1.202) <  0.0001
Cholesterol-yes 0.588 (0.549,0.608) <  0.0001
Heart problems-yes 1.203 (1.199,1.215) <  0.0001
Diabetes-yes 2.207 (2.204,2.210) <  0.0001
Chronic medication-cost 1.236 (1.137,1.240) <  0.0001
Hospitalisation-cost 2.999 (1.980,3.000) <  0.0001
Outpatient-cost 1.676 (1.566,1.680) <  0.0001
Physiotherapy-cost 2.090 (1.600,1.706) <  0.0001
Speech therapy-cost 0.987 (2.000,2.109 <  0.0001
  1. Note: βj= coefficient, 95%CI = 95% confidence interval