9 papers · 1 filter
Regression to the Mean-Adjusted Sample-Size Determination for Cutoff-Selected Single-Arm Pre-Post Studies
Ariel Linden
Studies enrolling participants on the basis of an extreme baseline value are susceptible to regression to the mean (RTM), such that some observed pre-post change is expected even w…
Beyond the Mean: A Weighted k-Sample Omnibus Variance-Ratio Statistic for Covariate Balance Diagnostics
Ariel Linden
Rubin's variance ratio (VR) complements the standardized mean difference by detecting covariate imbalance in spread, but no purpose-built omnibus extension exists for more than two…
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…
Joint Conditional Maximum Likelihood Estimation of Beta Regression for Panel Data with Higher-Order Autoregressive Errors
Ariel Linden
Existing panel beta regression estimators do not accommodate higher-order autoregressive dependence within a joint likelihood framework. We develop such an estimator: a joint condi…
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 central to causal inference, but commonly used summary measures may miss distributional differences. I develop weighted extensions of the Kolmogorov-…
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…
A Goodness-of-Fit Test for Mixed-Effects Logistic Regression
Ariel Linden
Mixed-effects logistic regression is widely used for binary outcomes in hierarchical data, yet formal goodness-of-fit tests remain limited to random-intercept models and do not add…