In the previous post, we introduced the Accelerated Failure Time (AFT) model.

(1)

We’d now like to estimate the weights . We will use a well-known technique in statistics called Maximum Likelihood Estimation (MLE):

Principle of Maximum Likelihood Estimation. Given a set of observations, the choice of parameter value that maximizes the likelihood of the observations is chosen as the “best” estimate for the parameter .

Whew! That’s a mouthful of words! In the remainder of the post, we’ll take some time to unpack this definition. Then in a subsequent post we’ll use MLE to estimate the weights in the AFT model (1).

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