東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Analyzing Covid-19 Serology Data Using Sparse Longitudinal Methods.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analyzing Covid-19 Serology Data Using Sparse Longitudinal Methods./
Author:	Hollister, James.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
Description:	30 p.
Notes:	Source: Masters Abstracts International, Volume: 83-11.
Contained By:	Masters Abstracts International83-11.
Subject:	Biostatistics. -
ISBN:	9798438770046

Analyzing Covid-19 Serology Data Using Sparse Longitudinal Methods.
Hollister, James.

Analyzing Covid-19 Serology Data Using Sparse Longitudinal Methods. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 30 p.

Source: Masters Abstracts International, Volume: 83-11.

Thesis (M.S.)--The University of Arizona, 2022.

This item must not be sold to any third party vendors.

The Arizona Healthcare, Emergency Response, and Other Essential Workers Study (AZ HEROES) is a study funded by the US Centers for Disease Control and Prevention(CDC) that aims to examine the epidemiology and immunity of SARS-CoV-2 infection and COVID-19 illness among adults with high occupational exposure. This study follows a cohort of essential workers from Arizona with frequent exposure to COVID-19.As part of the surveillance in the study, participants regularly contribute blood draws that are tested for antibodies that are protective against COVID-19. One of the primary study objectives for AZ HEROES is examining post-vaccine immunologic response, and a common method for researching this is correlates of protection. However, due to participants missing blood draws or collecting blood at timepoints outside of the time window defined by the protocol, the serology data can be described as sparse, which can cause potential analytic issues.This thesis aims to investigate how immunologic response after vaccination differs for individuals in the AZ HEROES study using two different analytical approaches that account for the sparseness of the data. First, we use a Bayesian multi-level model to test for differences in peak antibody levels and rate of antibody decline over time between different populations defined by age, sex, and comorbidities. Then, we use the PACE (Principal Analysis by Conditional Estimation) method to evaluate overall and individual-level antibody trends over time. The PACE method is useful for sparse longitudinal datasets where the number and spacing of data points is irregular, which is the case for the AZ HEROES serology data.

ISBN: 9798438770046Subjects--Topical Terms:

1002712
Biostatistics.
Subjects--Index Terms:

AZ heroes

Analyzing Covid-19 Serology Data Using Sparse Longitudinal Methods.
LDR:02616nmm a2200313 4500 001 2349767
005 20221003074949.5
008 241004s2022 eng d
020 $a 9798438770046
035 $a (MiAaPQ)AAI29208459
035 $a AAI29208459
040 $a MiAaPQ $c MiAaPQ
100 1 $a Hollister, James. $3 3689182
245 1 0 $a Analyzing Covid-19 Serology Data Using Sparse Longitudinal Methods.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2022
300 $a 30 p.
500 $a Source: Masters Abstracts International, Volume: 83-11.
500 $a Advisor: Sun, Xiaoxiao.
502 $a Thesis (M.S.)--The University of Arizona, 2022.
506 $a This item must not be sold to any third party vendors.
520 $a The Arizona Healthcare, Emergency Response, and Other Essential Workers Study (AZ HEROES) is a study funded by the US Centers for Disease Control and Prevention(CDC) that aims to examine the epidemiology and immunity of SARS-CoV-2 infection and COVID-19 illness among adults with high occupational exposure. This study follows a cohort of essential workers from Arizona with frequent exposure to COVID-19.As part of the surveillance in the study, participants regularly contribute blood draws that are tested for antibodies that are protective against COVID-19. One of the primary study objectives for AZ HEROES is examining post-vaccine immunologic response, and a common method for researching this is correlates of protection. However, due to participants missing blood draws or collecting blood at timepoints outside of the time window defined by the protocol, the serology data can be described as sparse, which can cause potential analytic issues.This thesis aims to investigate how immunologic response after vaccination differs for individuals in the AZ HEROES study using two different analytical approaches that account for the sparseness of the data. First, we use a Bayesian multi-level model to test for differences in peak antibody levels and rate of antibody decline over time between different populations defined by age, sex, and comorbidities. Then, we use the PACE (Principal Analysis by Conditional Estimation) method to evaluate overall and individual-level antibody trends over time. The PACE method is useful for sparse longitudinal datasets where the number and spacing of data points is irregular, which is the case for the AZ HEROES serology data.
590 $a School code: 0009.
650 4 $a Biostatistics. $3 1002712
653 $a AZ heroes
653 $a SARS-CoV-2 infection
653 $a High occupational exposure
690 $a 0308
710 2 0 $a The University of Arizona. $b Biostatistics. $3 3352147
773 0 $t Masters Abstracts International $g 83-11.
790 $a 0009
791 $a M.S.
792 $a 2022
793 $a English