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Neymanian inference in randomized experiments
Ambarish Chattopadhyay, Guido W. Imbens
In his seminal 1923 work, Neyman studied the variance estimation problem for the difference-in-means estimator of the average treatment effect in completely randomized experiments.…
Computationally Efficient Estimation of Large Probit Models
Patrick Ding, Guido Imbens, Zhaonan Qu +1
Probit models are useful for modeling correlated discrete responses in many disciplines, including consumer choice data in economics and marketing. However, the Gaussian latent var…
Comparing Experimental and Nonexperimental Methods: What Lessons Have We Learned Four Decades After LaLonde (1986)?
Guido Imbens, Yiqing Xu
In 1986, Robert LaLonde published an article comparing nonexperimental estimates to experimental benchmarks (LaLonde 1986). He concluded that the nonexperimental methods at the tim…
Multiple Randomization Designs: Estimation and Inference with Interference
Lorenzo Masoero, Suhas Vijaykumar, Thomas Richardson +5
Classical designs of randomized experiments, going back to Fisher and Neyman in the 1930s still dominate practice even in online experimentation. However, such designs are of limit…