8 papers
Cohen's f or Mean Standardized Differences? Assessing Covariate Balance with Multivalued Treatments
Ariel Linden
Assessing covariate balance across more than two treatment groups has no established omnibus standard: the prevailing practice averages, or takes the maximum of, pairwise standardi…
Weighted k-Sample Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling Tests for Assessing Covariate Balance
Ariel Linden
Weighted distributional tests for covariate balance are currently limited to two-group comparisons. We extend the Kolmogorov-Smirnov, Anderson-Darling, and Cramer-von Mises tests t…
Weighted Extensions of the Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling Tests for Assessing Covariate Balance
Ariel Linden
Assessing covariate balance is a core diagnostic step in causal inference, but commonly used summary measures can miss meaningful distributional differences they are not designed t…
Beta Regression with Autoregressive Errors for Interrupted Time Series Analysis of Proportion and Rate Outcomes: A Simulation Study
Ariel Linden
Interrupted time series analyses (ITSA) of proportion and rate outcomes are frequently estimated using ordinary least squares regression despite the bounded nature of these outcome…
Extending Prais-Winsten Regression to Panel Data with Higher-Order Autoregressive Errors: A Simulation Study
Ariel Linden
We extend the Prais-Winsten AR(k) generalized least squares (GLS) transformation to panel data within the Beck-Katz panel-corrected standard error (PCSE) framework and implement th…
Multiple-group (Controlled) Interrupted Time Series Analysis with Higher-Order Autoregressive Errors: A Simulation Study Comparing Newey-West and Prais-Winsten Methods
Ariel Linden
Previous comparisons of ordinary least squares with Newey-West standard errors (OLS-NW) and Prais-Winsten (PW) regression in multiple-group interrupted time series analysis have be…