We show with Monte-Carlo simulations and empirical choice data sets that we can quickly and simply refine choice model estimates for individuals based on methods such as ordinary least squares regression and weighted least squares regression to produce well-behaved insample and out-of-sample predictions of choices. We use well-known regression methods to estimate choice models, which should allow many more researchers to estimate choice models and be confident that they are unlikely to make serious mistakes
