Detecting and correcting publication bias in meta-analysis

Show full item record

Title: Detecting and correcting publication bias in meta-analysis
Author: Li, Xin
Abstract: Publication bias (PB ) makes the resources for meta -analysis (M -A ) unreliable in the sense of completion and accuracy , so to investigate , identify and correct PB is a very important issue in M -A . The current study proposed an empirical comparison in both detection and correcting PB , using a Monte Carlo study . Conditions to be manipulated include the number of primary studies , number of missing studies and true effect size . RANNOR in SAS will be used to generate normally distributed random variables and , for each condition , 10 ,000 M -As will be simulated . Type I error rates are to be calculated for the conditions with no PB and powers were estimated for the conditions with PB and adequate type I error control . Finally , a demonstration of how M -A can and should be used as a part of program evaluations was given .
URI: http : / /hdl .handle .net /2152 /ETD -UT -2009 -12 -536
Date: 2010-09-22

Citation

Detecting and correcting publication bias in meta-analysis. Master's thesis, The University of Texas at Austin. Available electronically from http : / /hdl .handle .net /2152 /ETD -UT -2009 -12 -536 .

Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show full item record

Search DSpace

Advanced Search

Browse