Skip to Main Content
 

Global Search Box

 
 
 

ETD Abstract Container

Abstract Header

Determination of Change in Online Monitoring of Longitudinal Data: An Evaluation of Methodologies

Jokinen, Jeremy D.
http://orcid.org/0000-0002-5705-8188
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1440499260

Abstract Details

2015, Doctor of Philosophy (PhD), Ohio University, Experimental Psychology (Arts and Sciences).
Longitudinal data collection is becoming increasingly common with the increased use of internet-based/technologically-based methods for data capture. In fields as diverse as healthcare, engineering, fisheries management, political science, economics, and psychology, often analyses are conducted to determine if some change to the pattern of incoming data has occurred. If a change has occurred analysis should make that determination as quickly as possible. A data-pattern change is critical information, as it may indicate a change in the health status of patients, changing political attitudes, or, as in the case of the proposed study, changes to the safety profile of consumer products. The methods to analyze these longitudinal databases for indicators of change are as varied as the fields collecting the data. To date, no single study has examined the varied methodologies to determine the relative accuracy of the methods and no study has attempted to determine the relative duration over which accurate change determinations are made. This study examined the performance of these methodologies across three sets of simulated data as well as a single, large-scale safety database for a major consumer healthcare company. The simulated data is comprised of random noise data streams and data streams with actual changes in data pattern (signals). The three simulated data sets differ by the strength of the signal. The consumer safety database is comprised of call center data (n>725,000 records) from consumers who call to report a side effect (adverse event) while taking a company product. Healthcare professionals flag products identified as having a confirmed safety signal. Analyses were conducted retrospectively to determine if this change in safety status could have been detected by the statistical methods examined in this study for 30 days prior to the date of the confirmed signal. For each of the three simulated data sets and the actual product safety database, mean and 95% CI for sensitivity and specificity as well as AUC ROC over time line graphs were used to examine differences between statistical methodologies. Results of analysis the simulated data set and the actual data set indicated the modified control chart method performed well throughout the 31-day time period of analysis. Modified control charting performed significantly better than other methods, proving to be a useful change detection method more than 20 days prior to the confirmed safety signal. Though RCI, Bayesian, and CUSUM did not perform as well as modified control charting, they did perform significantly better than all other methods. The computational simplicity of RCI makes this method worth considering for broad applications.
Bruce Carlson, PhD (Committee Chair)
Quantitative Psychology
Change detection; CUSUM; Bayesian; online data monitoring

Recommended Citations

Citations

  • Jokinen, J. D. (2015). Determination of Change in Online Monitoring of Longitudinal Data: An Evaluation of Methodologies [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1440499260

    APA Style (7th edition)

  • Jokinen, Jeremy. Determination of Change in Online Monitoring of Longitudinal Data: An Evaluation of Methodologies . 2015. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1440499260.

    MLA Style (8th edition)

  • Jokinen, Jeremy. "Determination of Change in Online Monitoring of Longitudinal Data: An Evaluation of Methodologies ." Doctoral dissertation, Ohio University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1440499260

    Chicago Manual of Style (17th edition)

ohiou1440499260
794
© , all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.