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Table 1 reports the matches of two-stage versions with and without heterogeneous decision rules (latent classes) and models that allow for conventional representation of continuous covariates (i.e., no splines). Based on standard fit metrics, the proposed model with five latent classes for both men and women fits the data better than all nested models (e.g., homogeneous and linear utility) and nonnested ones with polynomial representation of continuous covariates, and these differences are statistically significant. To safeguard against overfitting, we evaluate goodness of fit using a sample consisting of 318 women who joined the website right after the estimation interval and 181 men. These out of sample quotes reaffirm that a model outperforms other conventional specifications. In addition to superior fit, our model captures features of decision processes that are distorted by traditional approaches. Additional details are in SI Appendix, Section S4.
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