STAT SPEAKS: Colloquium on the Statistical Sciences

Last updated: Nov. 7, 2023, 11:24 a.m.

Speaker: Eric J. Daza, DrPH, MPS

Date: Nov. 9, 2023, 5 p.m.

Venue: UPSS Lecture Hall II

Abstract: Temporally dense single-person “small data” have become widely available thanks to mobile apps (e.g., that provide patient-reported outcomes) and wearable sensors. Many caregivers and self-trackers want to use these intensive longitudinal data to help a specific person change their behavior to achieve desired health outcomes. Ideally, this involves discerning possible causes from correlations using that person’s own observational time series data. In paper one, we estimate within-individual average treatment effects of sleep duration on physical activity and vice-versa. We introduce the model-twin randomization (MoTR; “motor”) and propensity score twin (PSTn; “piston”) methods for analyzing Fitbit sensor data. MoTR is a Monte Carlo implementation of the g-formula (i.e., standardization, back-door adjustment); PSTn implements propensity score inverse probability weighting. They estimate idiographic stable recurring effects, as done in n-of-1 trials and single-case experimental designs. We characterize and apply both methods to the two authors’ own data and compare our approaches to standard methods (with possible confounding) to show how to use causal inference to make truly personalized recommendations for health behavior change. In paper two, we apply MoTR to the three authors, thereby providing a guide for using MoTR to investigate your own recurring health conditions—and demonstrating how any suggested effects can differ greatly from those of other individuals.

UPSS and UPSCRFI invite you to attend the colloquium on 9 November 2023 from 5:00 PM - 6:00 PM at the UPSS Lecture Hall 2!

𝐔𝐬𝐢𝐧𝐠 𝐖𝐞𝐚𝐫𝐚𝐛𝐥𝐞𝐬 𝐚𝐧𝐝 𝐀𝐩𝐩𝐬 𝐭𝐨 𝐂𝐡𝐚𝐫𝐚𝐜𝐭𝐞𝐫𝐢𝐳𝐞 𝐘𝐨𝐮𝐫 𝐎𝐰𝐧 𝐑𝐞𝐜𝐮𝐫𝐫𝐢𝐧𝐠 𝐀𝐯𝐞𝐫𝐚𝐠𝐞 𝐓𝐫𝐞𝐚𝐭𝐦𝐞𝐧𝐭 𝐄𝐟𝐟𝐞𝐜𝐭𝐬
Eric J. Daza, DrPH, MPS
Lead Biostatistician (Data Science), Evidation Health, California, USA
Founder and Chief Editor, Stats-of-1

Kindly answer the form at https://bit.ly/2023-November-9-Colloquium to register.

The celebration is made possible by our partners:
IN PARTNERSHIP WITH
Accenture Inc.
Cocolife
UPSS Alumni Association
UPSS Class '93
UPSS Class '97
UPSS Class '99

ALSO BROUGHT TO YOU BY
Unilab
Pfizer
UPSS Class 2009

SPECIAL THANKS TO
TeaVia MR, Inc.
EGM Lending Corp.

#Stat70theFuture
#TrailblazingTodayTransformingTomorrow