Real-Time Regression Analysis of Streaming Clustered Data With Possible Abnormal Data Batches.

ABSTRACT: This paper develops an incremental learning algorithm based on quadratic inference function (QIF) to analyze streaming datasets with correlated outcomes such as longitudinal data and clustered data. We propose a renewable QIF (RenewQIF) method within a paradigm of renewable estimation and incremental inference, in which parameter estimates are recursively renewed with current data and summary statistics of historical data, but with no use of any historical subject-level raw data. We compare our renewable estimation method with both offline QIF and offline generalized estimating equations (GEE) approach that process the entire cumulative subject-level data all together, and show theoretically and numerically that our renewable procedure enjoys statistical and computational efficiency. We al

SUBMITTER: Luo L 

PROVIDER: S-EPMC10530766 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature