R中线性回归的截距的置信区间

Question

Let's say that i have two variables weight and age , i have to find the confidence interval with level 99% by this case:

1. By the ordinate (Y-Axis), if we did a linear regression a=lm(weight~age)

I know that the ordinate is directly the intercept but why this won't work:

predict(a, newdata=data.frame(age=intercept), interval='confidence',
level=0.99)

Why this is incorrect? I would like to know the correct commands for these cases.

Answer 1

The broom package can return confidence intervals for regression model estimates.

require(broom)
A <- c(12,11,12,15,13,16,13,18,11,14)
B <- c(50,51,62,45,63,76,53,68,51,74)

model <- lm(A~B)

tidy(model, conf.int = TRUE, conf.level = 0.99)
         term  estimate  std.error statistic   p.value    conf.low conf.high
1 (Intercept) 6.8153948 3.75608761  1.814493 0.1071515 -5.78773401 19.418524
2           B 0.1127252 0.06240674  1.806299 0.1085031 -0.09667358  0.322124

EDIT: I forgot that one can get confidence intervals for regression models in base R.

confint(model, level = .99)
                  0.5 %    99.5 %
(Intercept) -5.78773401 19.418524
B           -0.09667358  0.322124