2.50
Hdl Handle:
http://hdl.handle.net/10755/316884
Category:
Abstract
Type:
Presentation
Title:
A Bayesian Meta-Analysis of NCLEX-RN Success Predictors
Author(s):
Park, Kyuwon
Lead Author STTI Affiliation:
Beta Tau
Author Details:
Kyuwon Park, MS, RN, email: k.park1@umiami.edu
Abstract:

Poster presented on: Friday, April 4, 2014, Saturday, April 5, 2014

Introduction:

 Bayesian statistical analysis is seldom used in nursing research despite its widespread use in other fields. Meta-analysis is particularly suitable for the Bayesian inference because the data collected from the previous studies may contribute well to establish a prior distribution and it often deals with missing effect sizes that can be estimated well from Bayesian inference methods. This study utilizes Bayesian meta-analysis methods on the previous NCLEX-RN predictor studies.

Method(s):

Any Bayesian statistical analysis needs a prior distribution of the particular parameter of investigation. It enables a representation of the past knowledge regarding the parameter. Since this study is the first attempt of Bayesian meta-analysis on NCLEX-RN predictor studies, non-informative prior is used so that a posterior distribution of the interested parameter, mean of the effect sizes, relies more heavily on the previous studies themselves. The effect sizes are considered as a part of a random variable and the heterogeneity of the mean of the effect sizes are incorporated into the meta-analysis model. The parameter and the credible intervals are estimated by MCMC (Markov Chain Monte Carlo) simulation.

Results:

Various predictors tested in the previous studies are investigated inclduing SAT, ACT, GPA, and statndardized test scores. Mean and credible intervals of logged odds ratio of NCLEX-RN pass vs fail for each predictor are estimated. 

Discussion & Conclusions: 

Despite its complex solution and a consequential computation requirement, Bayesian meta-analysis has been utilized a lot more lately in physical and social science studies. Technological advances in the personal computers and increased availability of Bayesian analysis tools enable the widespread use of Bayesian statistical methods and challenge the dominant frequentist paradigm in statistics. Bayesian way of thinking may also contribute to the advancement of nursing science as it has been to the other fields.  

Keywords:
NCLEX-RN; Bayesian; Meta-analysis
Repository Posting Date:
13-May-2014
Date of Publication:
13-May-2014
Conference Date:
2014
Conference Name:
Nursing Education Research Conference 2014
Conference Host:
Sigma Theta Tau International, the Honor Society of Nursing; National League of Nursing
Conference Location:
Indianapolis, Indiana, USA
Description:
Nursing Education Research Conference 2014 Theme: Nursing Education Research, held in Hyatt Regency Indianapolis
Note:
This is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription.  Contact your library for assistance in obtaining the as-published article

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_GB
dc.type.categoryAbstracten_GB
dc.typePresentationen_GB
dc.titleA Bayesian Meta-Analysis of NCLEX-RN Success Predictorsen_GB
dc.contributor.authorPark, Kyuwonen_GB
dc.contributor.departmentBeta Tauen_GB
dc.author.detailsKyuwon Park, MS, RN, email: k.park1@umiami.eduen_GB
dc.identifier.urihttp://hdl.handle.net/10755/316884-
dc.description.abstract<p>Poster presented on: Friday, April 4, 2014, Saturday, April 5, 2014</p><table cellspacing="0" cellpadding="0" border="0"> <tbody> <tr> <td><p><b>Introduction: </b><p> Bayesian statistical analysis is seldom used in nursing research despite its widespread use in other fields. Meta-analysis is particularly suitable for the Bayesian inference because the data collected from the previous studies may contribute well to establish a prior distribution and it often deals with missing effect sizes that can be estimated well from Bayesian inference methods. This study utilizes Bayesian meta-analysis methods on the previous NCLEX-RN predictor studies. </td> </tr> <tr> <td></td> </tr> <tr> <td><p><b>Method(s): </b><p>Any Bayesian statistical analysis needs a prior distribution of the particular parameter of investigation. It enables a representation of the past knowledge regarding the parameter. Since this study is the first attempt of Bayesian meta-analysis on NCLEX-RN predictor studies, non-informative prior is used so that a posterior distribution of the interested parameter, mean of the effect sizes, relies more heavily on the previous studies themselves. The effect sizes are considered as a part of a random variable and the heterogeneity of the mean of the effect sizes are incorporated into the meta-analysis model. The parameter and the credible intervals are estimated by MCMC (Markov Chain Monte Carlo) simulation. </td> </tr> <tr> <td></td> </tr> <tr> <td><p><b>Results:</b><p>Various predictors tested in the previous studies are investigated inclduing SAT, ACT, GPA, and statndardized test scores. Mean and credible intervals of logged odds ratio of NCLEX-RN pass vs fail for each predictor are estimated.  </td> </tr> <tr> <td></td> </tr> <tr> <td><p><b>Discussion & Conclusions: </b><p>Despite its complex solution and a consequential computation requirement, Bayesian meta-analysis has been utilized a lot more lately in physical and social science studies. Technological advances in the personal computers and increased availability of Bayesian analysis tools enable the widespread use of Bayesian statistical methods and challenge the dominant frequentist paradigm in statistics. Bayesian way of thinking may also contribute to the advancement of nursing science as it has been to the other fields.<b>  </b><p><b> </b> </td> </tr> </tbody> </table>en_GB
dc.subjectNCLEX-RNen_GB
dc.subjectBayesianen_GB
dc.subjectMeta-analysisen_GB
dc.date.available2014-05-13T16:44:42Z-
dc.date.issued2014-05-13-
dc.date.accessioned2014-05-13T16:44:42Z-
dc.conference.date2014en_GB
dc.conference.nameNursing Education Research Conference 2014en_GB
dc.conference.hostSigma Theta Tau International, the Honor Society of Nursingen_GB
dc.conference.hostNational League of Nursingen_GB
dc.conference.locationIndianapolis, Indiana, USAen_GB
dc.descriptionNursing Education Research Conference 2014 Theme: Nursing Education Research, held in Hyatt Regency Indianapolisen_GB
dc.description.noteThis is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription.  Contact your library for assistance in obtaining the as-published articleen_GB
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