jamieyap
Doing data science together with the Data Science for Dynamic Intervention Decision-making Center (d3center) https://d3c.isr.umich.edu/
University of MichiganAnn Arbor, MI
Pinned Repositories
CATIE2023_vMods
College-to-Work-Transition-Study
This repository contains code for curating data and testing hypotheses relating to the College-to-Work Transition study.
CountSMART
This repository contains code to estimate sample size needed to compare dynamic treatment regimens using longitudinal count outcomes from a Sequential Multiple Assignment Randomized Trial (SMART).
mbridge-randomized-trial
This repository contains code and documentation for curating data and testing hypotheses relating to the MBRIDGE micro-randomized trial.
PNS
Code and accompanying documentation within this repository focuses on curation of intensive longitudinal data (ILD) from EMA questionnaires from both pre- and post- quit periods; other data collected during the conduct of the study are beyond the scope of this repository and accompanying documentation.
power-calc-mars-mrt
The material in this repository is a supplement to the manuscript titled `The Mobile-Assistance for Regulating Smoking (MARS) Micro-Randomized Trial Design Protocol' (Nahum-Shani, et al., 2021), submitted for consideration to the Journal of Contemporary Clinical Trials. The material include code and documentation for the power calculation for the Primary Aim and Secondary Aim of the trial.
S2S-sMRT
Creating curated datasets for analyses and estimation of treatment effects for the Sense2Stop stratified micro-randomized trial.
SARA
This repository contains code for performing curation and analysis of SARA Micro-Randomized Trial data and documentation.
smarter-weight-loss
This repository contains code for assessing the performance of various classification rules for determining whether a participant offered only an APP-based intervention would be considered an early non-responder.
working-with-data-workshops
This repository contains code and material for the Working With Data Workshop.
jamieyap's Repositories
jamieyap/mbridge-randomized-trial
This repository contains code and documentation for curating data and testing hypotheses relating to the MBRIDGE micro-randomized trial.
jamieyap/PNS
Code and accompanying documentation within this repository focuses on curation of intensive longitudinal data (ILD) from EMA questionnaires from both pre- and post- quit periods; other data collected during the conduct of the study are beyond the scope of this repository and accompanying documentation.
jamieyap/SARA
This repository contains code for performing curation and analysis of SARA Micro-Randomized Trial data and documentation.
jamieyap/smarter-weight-loss
This repository contains code for assessing the performance of various classification rules for determining whether a participant offered only an APP-based intervention would be considered an early non-responder.
jamieyap/CATIE2023_vMods
jamieyap/College-to-Work-Transition-Study
This repository contains code for curating data and testing hypotheses relating to the College-to-Work Transition study.
jamieyap/CountSMART
This repository contains code to estimate sample size needed to compare dynamic treatment regimens using longitudinal count outcomes from a Sequential Multiple Assignment Randomized Trial (SMART).
jamieyap/power-calc-mars-mrt
The material in this repository is a supplement to the manuscript titled `The Mobile-Assistance for Regulating Smoking (MARS) Micro-Randomized Trial Design Protocol' (Nahum-Shani, et al., 2021), submitted for consideration to the Journal of Contemporary Clinical Trials. The material include code and documentation for the power calculation for the Primary Aim and Secondary Aim of the trial.
jamieyap/S2S-sMRT
Creating curated datasets for analyses and estimation of treatment effects for the Sense2Stop stratified micro-randomized trial.
jamieyap/working-with-data-workshops
This repository contains code and material for the Working With Data Workshop.
jamieyap/MI-SafeCope
This repository contains code to construct features from intensive longitudinal data collected from youth at risk of suicide and calculate AUC using repeated stratified cross validation.