Figure 4
Correlation between prevalence of infection and response rate. There was a significant positive correlation between the 2 variables (simple Pearson coefficient r = 0.3510, P = .018). The equation of the line relating response rate (y) and prevalence of infection (x) is estimated as: y = (7.2148) + (0.6744) x. The slope (r correlation coefficient), that is, the estimated change in response rate per unit change in the prevalence of infection, is 0.6744 with a standard error of 0.3058. The value of R2, the proportion of the variation in the response rate that can be accounted for by variation in the prevalence of infection, is 0.2038. The lower limit of the 95% CI for the slope is 0.0343 and the upper limit is 1.3144. The estimated intercept is 7.2148. The lower limit of the 95% CI for the intercept is −36.2226 and the upper limit is 50.6521 (curved dotted lines).

Correlation between prevalence of infection and response rate. There was a significant positive correlation between the 2 variables (simple Pearson coefficient r = 0.3510, P = .018). The equation of the line relating response rate (y) and prevalence of infection (x) is estimated as: y = (7.2148) + (0.6744) x. The slope (r correlation coefficient), that is, the estimated change in response rate per unit change in the prevalence of infection, is 0.6744 with a standard error of 0.3058. The value of R2, the proportion of the variation in the response rate that can be accounted for by variation in the prevalence of infection, is 0.2038. The lower limit of the 95% CI for the slope is 0.0343 and the upper limit is 1.3144. The estimated intercept is 7.2148. The lower limit of the 95% CI for the intercept is −36.2226 and the upper limit is 50.6521 (curved dotted lines).

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