# Variance as a Predictor of Health Outcomes (Resub)

> **NIH NIH R56** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $374,998

## Abstract

Abstract
The purpose of the proposed research is to develop a suite of flexible statistical models
and computationally scalable inferential methods to understand how variability of
biomarkers may be associated with future health outcomes. While variance is typically
understood as nuisance – the “noise” in “signal-to-noise” – there is increasing evidence
that underlying variability in subject-level measures over time may also be important in
predicting future health outcomes of interest. Previous work in this area has focused on
using repeated measures on predictors, one-at-a-time, to develop subject-level mean
and variance estimates to use as predictors in joint models of binary outcomes. The
technological advances in scientific measurements have resulted in biomarkers that are
multivariate, mixed-scale, and obtained at increasingly higher time resolutions. While the
scope of scientific questions involving the use of biomarkers in clinical studies has
greatly expanded, statistical method development has not kept apace. The proposed
research will extend existing work to model time-to-event outcomes, to perform multi-
outcome modeling of both scalar and multivariate outcomes as functions of multiple sets
of longitudinal predictors, and to deal with high dimensional longitudinal predictors such
as those provided by repeated long-term surveillance in prospective cohort studies and
by biometric ecological momentary assessment (EMA) measures.

## Key facts

- **NIH application ID:** 10490505
- **Project number:** 1R56AG066693-01A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** MICHAEL R. ELLIOTT
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $374,998
- **Award type:** 1
- **Project period:** 2021-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10490505

## Citation

> US National Institutes of Health, RePORTER application 10490505, Variance as a Predictor of Health Outcomes (Resub) (1R56AG066693-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10490505. Licensed CC0.

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