| dc.contributor.advisor |
Powers , Daniel A . |
|
| dc.contributor.committeeMember |
Saar -Tsechansky , Maytal |
|
| dc.creator |
Ye , Na , 1983 - |
|
| dc.date.accessioned |
2011 -08 -05T18 :47 :36Z |
|
| dc.date.available |
2011 -08 -05T18 :47 :36Z |
|
| dc.date.created |
2011 -05 |
|
| dc.date.issued |
2011 -08 -05 |
|
| dc.date.submitted |
May 2011 |
|
| dc.identifier.uri |
http : / /hdl .handle .net /2152 /ETD -UT -2011 -05 -3293 |
|
| dc.description.abstract |
The Vaccine Adverse Event Reporting System (VAERS ) received thousands of reports of adverse events that occurred after vaccine administrations from the post -marketing vaccine safety surveillance . However , the causality between vaccines and reported adverse events cannot be taken for granted . In this report several data mining methods were applied to VAERS database that is coded in MedDRA terms to discover possible associations between vaccines and adverse events . Efforts were devoted to identify events that are reported more frequently after administering one vaccine than other vaccines using the following data mining techniques : relative ratio (RR ) , statistical significance (LogP ) , proportional reporting ratio (PRR ) , and screened PRR (SPRR ) .
The vaccine -event combinations that ranked top in each method varied substantially among the methods . RR and PRR gave excessive weight to small counts of vaccine -event pairs , but SPRR was able to correct this weakness . There are only 33 vaccine -event pairs that were shared among the top 1 ,000 ranked in each method . Evaluating the properties of these data mining methods and exploring other methods will help improve vaccine safety surveillance . |
|
| dc.format.mimetype |
application /pdf |
|
| dc.language.iso |
eng |
|
| dc.subject |
Vaccine |
|
| dc.subject |
Adverse event |
|
| dc.subject |
Data mining |
|
| dc.subject |
Relative risk |
|
| dc.subject |
Proportional relative risk |
|
| dc.subject |
Screened proportional reporting ratio |
|
| dc.title |
Vaccine -adverse event association analysis on the VAERS database |
|
| dc.description.department |
Statistics |
|
| dc.type.genre |
thesis |
* |
| dc.type.material |
text |
* |
| thesis.degree.name |
Master of Science in Statistics |
|
| thesis.degree.level |
Masters |
|
| thesis.degree.discipline |
Statistics |
|
| thesis.degree.grantor |
University of Texas at Austin |
|
| thesis.degree.department |
Statistics |
|
| dc.date.updated |
2011 -08 -05T18 :47 :40Z |
|
| dc.identifier.slug |
2152 /ETD -UT -2011 -05 -3293 |
|