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Daniel McFadden
Researcher at University of California, Berkeley
Publications - 248
Citations - 63965
Daniel McFadden is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Medicare Part D & Estimator. The author has an hindex of 74, co-authored 243 publications receiving 60638 citations. Previous affiliations of Daniel McFadden include Cambridge Systematics & University of California.
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Observational Studies: Outcome-Based Sampling
TL;DR: This article outlines some practical methods for consistent estimation of population conditional response probabilities and discusses issues of robustness and inference that arise because procedures that ignore the selection induced by the sample frame may be statistically inconsistent.
On selecting regressors to maximize their significance
TL;DR: In this paper, it is shown that PLS is equivalent to direct estimation by non-linear least squares, and thus statistically consistent under mild regularity conditions, when explanatory variables are smooth in the parameters that index the selection alternatives, and that covariance matrix estimates obtained by kernel-smoothing or bootstrap methods appear to be reasonably accurate for samples of moderate size.
Posted Content
Understanding the SES Gradient in Health Among the Elderly: The Role of Childhood Circumstances
TL;DR: It is confirmed that childhood health has lasting predictive power for adult health and strong gender differences in the intertemporal transmission of SES and health are uncovered.