Regression adjustment in completely randomized experiments with a diverging number of covariates

Gee Analysis of Clustered Binary Data with Diverging Number of Covariates

Clustered binary data with a large number of covariates have become increasingly more common in many scientific disciplines. This paper develops an asymptotic theory for generalized estimating equations (GEE) analysis of clustered binary data when the number of covariates grows to infinity with the number of clusters. In this “large n, diverging p” framework, we provide appropriate regularity c...

Supplement to “gee Analysis of Clustered Binary Data with Diverging Number of Covariates”’

Generalized Additive Partial Linear Models for Clustered Data with Diverging Number of Covariates Using Gee

We study flexible modeling of clustered data using marginal generalized additive partial linear models with a diverging number of covariates. Generalized estimating equations are used to fit the model with the nonparametric functions being approximated by polynomial splines. We investigate the asymptotic properties in a “large n, diverging p” framework. More specifically, we establish the consi...

Evaluation of Imputation of Covariates in an Impact Analysis With Regression Adjustment

In an impact analysis using random assignment, researchers often deal with missing values in both the covariates and the outcome variables of regression models. Clearly rigorous methods are needed to impute missing values in the outcome variables to minimize the potential bias in impact assessments. When imputation is applied to covariates of the regression analyses, the effect of imputation is...

Regression Discontinuity Design with Covariates

Regression Discontinuity Design with Covariates In this paper, the regression discontinuity design (RDD) is generalized to account for differences in observed covariates X in a fully nonparametric way. It is shown that the treatment effect can be estimated at the rate for one-dimensional nonparametric regression irrespective of the dimension of X. It thus extends the analysis of Hahn, Todd, and...