让我们拟合模型:

> library(ISwR)
> fit <- lm(metabolic.rate ~ body.weight, rmr)
> summary(fit)

Call:
lm(formula = metabolic.rate ~ body.weight, data = rmr)

Residuals:
    Min      1Q  Median      3Q     Max 
-245.74 -113.99  -32.05  104.96  484.81 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 811.2267    76.9755  10.539 2.29e-13 ***
body.weight   7.0595     0.9776   7.221 7.03e-09 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 157.9 on 42 degrees of freedom
Multiple R-squared: 0.5539, Adjusted R-squared: 0.5433 
F-statistic: 52.15 on 1 and 42 DF,  p-value: 7.025e-09 

斜率的95％置信区间是估计系数(7.0595)±两个标准误差(0.9776).

The 95% confidence interval for the slope is the estimated coefficient (7.0595) ± two standard errors (0.9776).

这可以使用 confint 计算:

This can be computed using confint:

> confint(fit, 'body.weight', level=0.95)
               2.5 % 97.5 %
body.weight 5.086656 9.0324