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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