Jasjeet S. Sekhon

Jasjeet S. Sekhon
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Jasjeet S. Sekhon

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Statistics - Methodology (3)
Statistics - Theory (1)
Statistics - Applications (1)
Mathematics - Statistics (1)

Publications Authored By Jasjeet S. Sekhon

The popularity of online surveys has increased the prominence of sampling weights in claims of representativeness. Yet, much uncertainty remains regarding how these weights should be employed in the analysis of survey experiments: Should they be used or ignored? If they are used, which estimators are preferred? We offer practical advice, rooted in the Neyman-Rubin model, for researchers producing and working with survey experimental data. We examine simple, efficient estimators (Horvitz-Thompson, H\`ajek, "double-H\`ajek", and post-stratification) for analyzing these data, along with formulae for biases and variances. Read More

Matching methods are used to make units comparable on observed characteristics. Full matching can be used to derive optimal matches. However, the method has only been defined in the case of two treatment categories, it places unnecessary restrictions on the matched groups, and existing implementations are computationally intractable in large samples. Read More

We derive the variances of estimators for sample average treatment effects under the Neyman-Rubin potential outcomes model for arbitrary blocking assignments and an arbitrary number of treatments. Read More

We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large. Investigators often use linear multivariate regression to analyze randomized experiments instead of simply reporting the difference of means between treatment and control groups. Their aim is to reduce the variance of the estimated treatment effect by adjusting for covariates. Read More