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Determination of the optimal number ...

Akers, Allen.

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Determination of the optimal number of strata for bias reduction in propensity score matching.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Determination of the optimal number of strata for bias reduction in propensity score matching./
Author:	Akers, Allen.
Description:	57 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-08, Section: A, page: 2859.
Contained By:	Dissertation Abstracts International71-08A.
Subject:	Education, Tests and Measurements. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3417726
ISBN:	9781124153810

Determination of the optimal number of strata for bias reduction in propensity score matching.
Akers, Allen.

Determination of the optimal number of strata for bias reduction in propensity score matching. - 57 p.

Source: Dissertation Abstracts International, Volume: 71-08, Section: A, page: 2859.

Thesis (Ph.D.)--University of North Texas, 2010.

Previous research implementing stratification on the propensity score has generally relied on using five strata, based on prior theoretical groundwork and minimal empirical evidence as to the suitability of quintiles to adequately reduce bias in all cases and across all sample sizes. This study investigates bias reduction across varying number of strata and sample sizes via a large-scale simulation to determine the adequacy of quintiles for bias reduction under all conditions. Sample sizes ranged from 100 to 50,000 and strata from 3 to 20. Both the percentage of bias reduction and the standardized selection bias were examined. The results show that while the particular covariates in the simulation met certain criteria with five strata that greater bias reduction could be achieved by increasing the number of strata, especially with larger sample sizes. Simulation code written in R is included.

ISBN: 9781124153810Subjects--Topical Terms:

1017589
Education, Tests and Measurements.

Determination of the optimal number of strata for bias reduction in propensity score matching.
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020 $a 9781124153810
035 $a (UMI)AAI3417726
035 $a AAI3417726
040 $a UMI $c UMI
100 1 $a Akers, Allen. $3 858318
245 1 0 $a Determination of the optimal number of strata for bias reduction in propensity score matching.
300 $a 57 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-08, Section: A, page: 2859.
500 $a Adviser: Darrell M. Hull.
502 $a Thesis (Ph.D.)--University of North Texas, 2010.
520 $a Previous research implementing stratification on the propensity score has generally relied on using five strata, based on prior theoretical groundwork and minimal empirical evidence as to the suitability of quintiles to adequately reduce bias in all cases and across all sample sizes. This study investigates bias reduction across varying number of strata and sample sizes via a large-scale simulation to determine the adequacy of quintiles for bias reduction under all conditions. Sample sizes ranged from 100 to 50,000 and strata from 3 to 20. Both the percentage of bias reduction and the standardized selection bias were examined. The results show that while the particular covariates in the simulation met certain criteria with five strata that greater bias reduction could be achieved by increasing the number of strata, especially with larger sample sizes. Simulation code written in R is included.
590 $a School code: 0158.
650 4 $a Education, Tests and Measurements. $3 1017589
650 4 $a Education, Educational Psychology. $3 1017560
690 $a 0288
690 $a 0525
710 2 $a University of North Texas. $3 1017396
773 0 $t Dissertation Abstracts International $g 71-08A.
790 1 0 $a Hull, Darrell M., $e advisor
790 $a 0158
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3417726