Journal article
Does Testing More Frequently Shorten the Time to Detect Disease Progression?
Translational Vision Science & Technology, Vol.6(3), pp.1-1
2017
DOI: 10.1167/tvst.6.3.1
PMCID: PMC5412967
PMID: 28473945
Abstract
PURPOSE: With the rise of smartphone devices to monitor health status remotely, it is tempting to conclude that sampling more often will provide a more sensitive means of detecting changes in health status earlier over time, when interventions may improve outcomes.METHODS: The answer to this question is derived in the context of a model where observations are generated from a linear-trend model with independent as well as autocorrelated autoregressive-moving average, or ARMA(1,1), errors.RESULTS: The results imply a cautionary message that an increase in the sampling frequency may not always lead to a faster detection of trend changes. The benefit of rapid successive observations depends on how observations, taken closely together in time, are correlated.CONCLUSIONS: Shortening the observation period by half can be accomplished by increasing the number of independent observations to maintain the same power for detecting change over time. However, a strategy to detect progression of disease sooner by taking numerous closely spaced measurements over a shortened interval is limited by the degree of autocorrelation among adjacent observations. We provide a statistical model of disease progression that allows for autocorrelation among successive measurements, and obtain the power of detecting a linear change of specified magnitude when equal-spaced observations are taken over a given time interval.TRANSLATIONAL RELEVANCE: New emerging technology for home monitoring of visual function will provide a means to monitor sensory status more frequently. The model proposed here takes into account how successive measurements are correlated, which impacts the number of measurements needed to detect a significant change in status.
Details
- Title: Subtitle
- Does Testing More Frequently Shorten the Time to Detect Disease Progression?
- Creators
- Johannes LedolterRandy Kardon
- Resource Type
- Journal article
- Publication Details
- Translational Vision Science & Technology, Vol.6(3), pp.1-1
- DOI
- 10.1167/tvst.6.3.1
- PMID
- 28473945
- PMCID
- PMC5412967
- NLM abbreviation
- Transl Vis Sci Technol
- ISSN
- 2164-2591
- eISSN
- 2164-2591
- Language
- English
- Date published
- 2017
- Academic Unit
- Statistics and Actuarial Science; Iowa Neuroscience Institute; Business Analytics; Ophthalmology and Visual Sciences
- Record Identifier
- 9983980055802771
Metrics
28 Record Views