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Lecture 13 Estimation and hypothesis testing for logistic ...
parameter p. We can use the the inverse of the information evaluated at the MLE to estimate the variance of pˆ as varc(ˆp) = I(ˆp)−1 = pˆ(1−pˆ) n. For large n, pˆ is approximately normally distributed with mean p and variance p(1 − p)/n. Therefore, we can construct a 100×(1−α)% confidence interval for p as pˆ±Z 1−α/2[ˆp(1 ...
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