Cost-Effective Study Designs
Most statistical tools improve efficiency after obtaining data through sophisticated techniques, but if costs can be substantially reduced and at the data-collection step, then scientists and industry leaders will afford and even welcome a straightforward and scalable statistical tool in analyzing the data.
In the industry, I research practical data collection and design methods to improve representativeness and efficiency in sampling, especially leveraging the “auxiliary information” from new sensing technologies. I have worked with field scientists, sensor engineers, and software engineers to implement these methods in the real world.
In academia, to accompany my research in study designs, I am developing statistical analysis tools, guidance materials, and software to ease the use of complex but efficient study designs, and I am developing theoretical tools to facilitate the extension of methods developed for simple random sampling data to such designs.
My current research interest is practical and adaptive study design for building environmental monitoring networks.
Sampling designs with new sensing technologies
Hu, J, Jerkins, J, Goebel, N.
Routing Method for Mobile Monitoring Platforms — A scalable sampling method that dispatches a fleet of vehicles to collect environmental data unbiasedly
(U. S. Application Serial No.17/332789)
Hu, J & Ladoni, M.
Location Selection for Treatment Sampling — A field Study Design Tool to Optimize Treatment Assignment and Soil Sampling Locations for Model Calibration.
(U.S. Patent No. #10,963,606)
Hu, J
Location Selection for Model Assessment
(U.S. Patent No. #10,990,716)
Zheng, ZS, Hu, J, Malone, M, Vogel N
A Time-Series Clustering approach for Soil Moisture Probes Placement *
The Climate Corporation, 2017
Hu, J
A Model-Assisted Probability Sampling Design for Representative Locations *
The Climate Corporation, 2017
Hu, J, Evaluation of the 2015 Climatology Field Experiments*
The Climate Corporation, 2015
* Internal Peer-Reviewed Technical Reports @ The Climate Corporation, A subsidary of Bayer Crop Science
## Analysis methods for efficient study designs
Jie Hu, Norman E. Breslow, Chan Gary, Couper David
“Estimating Disease Hazard Differences from Case-Cohort Studies”
European Journal of Epidemiology, Jun, 1-14 (2021).
Jie Kate Hu, Gary Chan
“Weights Determination in Generalized Case-Cohort Study”
To be submitted
Norman Breslow and Jie Kate Hu
“Survival Analysis of Case-Control Data: A Sample Survey Approach”
Handbook of Statistical Methods for Case-Control Studies, Chapman and Hall/CRC, (2018).
Software
Theoretical tools for methods development with complex sampling designs
Hu, J
“A Z-estimation system for two-phase sampling with applications to additive hazards models and epidemiologic studies”
PhD Diss.University of Washington ResearchWorks Archive (2014).
Chapter 2 provides theoretical tools to develop semiparametric models with two-phase sampling, including both Bernoulli sampling and finite population sampling