Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

This article proposes a data-driven method to identify parsimony in the covariance matrix of longitudinal data and to exploit any such parsimony to produce a statistically efficient estimator of the ...

This paper presents a smooth regression model for ordinal data with longitudinal dependence structure. A marginal model with cumulative logit link is applied to cope with the ordinal scale and the ...

Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

The 2021 International Prize in Statistics has been awarded to US biostatistician Nan Laird, Harvey V. Fineberg Professor of Biostatistics (Emerita) at Harvard T.H. Chan School of Public Health, in ...

In their recent article in Journal of Clinical Oncology, Bonnetain et al 1 have shared a concise, informative review of statistical challenges in the analysis of health-related quality of life (HRQOL) ...

This course is available on the MPA in Data Science for Public Policy, MRes in Management (Marketing), MSc in Health Data Science, MSc in Social Research Methods, MSc in Statistics, MSc in Statistics ...

Over the past 15 years, the World Bank’s premier longitudinal household survey project, the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA), supported national ...

Statistics is the science of learning from data. The theoretical foundation of statistics lies in probability theory, which is applied to decision-making under uncertainty. Data science consists of ...

When researchers require some statistical expertise or data analysis know-how, The Methodology Center at Purdue (MCAP) is there. A collaboration between the Purdue University College of Health and ...