5 papers · 1 filter
TS-Neyman: Posterior Sampling for Adaptive Stratified Estimation
Kosuke Morikawa, Mst Moushumi Pervin, Jae Kwang Kim
Many model evaluation tasks reduce to estimating an average loss, error rate, or subgroup metric on a stratified pool when each label, human rating, or simulator call is costly. Th…
Semiparametric Efficient Data Integration Using the Dual-Frame Sampling Framework
Kosuke Morikawa, Jae Kwang Kim
Integrating probability and non-probability samples is increasingly important, yet unknown non-probability inclusion mechanisms complicate identification and efficient estimation.…
Efficient Multiple-Robust Estimation for Nonresponse Data Under Informative Sampling
Kosuke Morikawa, Kenji Beppu, Wataru Aida
Nonresponse after probability sampling is a universal challenge in survey sampling, often necessitating adjustments to mitigate sampling and selection bias simultaneously. This stu…
Identification enhanced generalised linear model estimation with nonignorable missing outcomes
Kenji Beppu, Jinung Choi, Kosuke Morikawa +1
Missing data often result in undesirable bias and loss of efficiency. These issues become substantial when the response mechanism is nonignorable, meaning that the response model d…
Robust Estimation and Model Selection for the Controlled Directed Effect with Unmeasured Mediator-Outcome Confounders
Shunichiro Orihara, Shinpei Imori, Kosuke Morikawa +2
Controlled Direct Effect (CDE) is one of the causal estimands used to evaluate both exposure and mediation effects on an outcome. When there are unmeasured confounders existing bet…