1 citations · 2 across the 6 of their papers we have counts for
6 papers
Causal Small Area Estimation with Survey-only Covariates
Tsubasa Ito, Shonosuke Sugasawa
Area-specific causal inference is important in many policy and survey applications, where the goal is to evaluate treatment effects for small geographic or demographic domains. Exi…
Grouped Generalized Estimating Equations for Longitudinal Data Analysis
Tsubasa Ito, Shonosuke Sugasawa
Generalized estimating equation (GEE) is widely adopted for regression modeling for longitudinal data, taking account of potential correlations within the same subjects. Although t…
Improved Confidence Regions in Meta-analysis of Diagnostic Test Accuracy
Tsubasa Ito, Shonosuke Sugasawa
Meta-analyses of diagnostic test accuracy (DTA) studies have been gathering attention in research in clinical epidemiology and health technology development, and bivariate random-e…
Corrected Empirical Bayes Confidence Region in a Multivariate Fay-Herriot Model
Tsubasa Ito, Tatsuya Kubokawa
In the small area estimation, the empirical best linear unbiased predictor (EBLUP) in the linear mixed model is useful because it gives a stable estimate for a mean of a smallarea.…
On Measuring the Variability of Small Area Estimators in a Multivariate Fay-Herriot Model
Tsubasa Ito, Tatsuya Kubokawa
This paper is concerned with the small area estimation in the multivariate Fay-Herriot model where covariance matrix of random effects are fully unknown. The covariance matrix is e…
Empirical Best Linear Unbiased Predictors in Multivariate Nested-Error Regression Models
Tsubasa Ito, Tatsuya Kubokawa
For analyzing unit-level multivariate data in small area estimation, we consider the multivariate nested error regression model (MNER) and provide the empirical best linear unbiase…