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You are here		gregoryfaletto.com Estimating treatment effects with a linear model in a randomized experiment-insights from the Double/Debiased ML framework - Gregory Faletto
|	|	fharrell.com Violation of Proportional Odds is Not Fatal - Statistical Thinking	3.7 parsecs away Travel
|	|	Many researchers worry about violations of the proportional hazards assumption when comparing treatments in a randomized study. Besides the fact that this frequently makes them turn to a much worse approach, the harm done by violations of the proportional odds assumption usually do not prevent the proportional odds model from providing a reasonable treatment effect assessment.
|	|	hbiostat.org Incorrect Covariate Adjustment May Be More Correct than Adjusted Marginal Estimates - Statistical Thinking	4.1 parsecs away Travel
|	|	This article provides a demonstration that the perceived non-robustness of nonlinear models for covariate adjustment in randomized trials may be less of an issue than the non-transportability of marginal so-called robust estimators.
|	|	mc-stan.org Estimating Generalized (Non-)Linear Models with Group-Specific Terms with rstanarm rstanarm	4.9 parsecs away Travel
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|	|	aria42.com Numerical Optimization: Understanding L-BFGS - aria42	24.8 parsecs away Travel
|		Numerical optimization is at the core of much of machine learning. In this post, we derive the L-BFGS algorithm, commonly used in batch machine learning applications.

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