 # Meta Analysis Younghun Han

Yüklə 451 b.
 tarix 02.03.2018 ölçüsü 451 b. #29104 • ## Meta-analysis is the statistical procedure for combining the results of several studies that address a set of related research hypotheses.

• When the treatment effect (or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect
• When the effect is varies from one study to the next, meta-analysis may be used to identify reason for the variation

• ## A meta-analysis can increase power and provide standards of reporting results in genome-wide association studies (GWAS) • ## Effect size : In statistics, effect size is a measure of the strength of the relationship between two variables.

• Binary outcomes : odds ratio, relative risk, risk difference
• Continuous outcomes: difference in means, standardized difference in means, ∙ ∙ ∙

• ## (pooled, overall, or combined effect size)

• Weighted average = ∑i(effecti × weighti) / ∑weighti
• weight : sample size, Inverse of the variance, Quality ….. • ## Fixed effect model (assume that the studies are homogeneous)

• Mantel-Haenszel
• Peto
• Inverse Variance
• ## Random effect model

• DerSimonian and Laird
• When the studies are found to be homogeneous, random and fixed effects models are indistinguishable.
• ## Test for heterogeneity

• Cochrans’s Q statistics
• I2 • ## Forest plot • ## Publication bias

• Publication bias is the tendency to publish research with a positive outcome more frequently than research with a negative outcome.
• Publication bias can lead to misleading results
• Check publication bias by Funnel plots • ## Funnel plot

• Effect size vs Sample size
• Effect size vs S.E.
• Effect size vs 1/S.E. (precision)
• (a) (b) • ## Need 2×2 frequency table for Mantel-Haenszel • ## where ni = ai + bi + ci + di • ## Example1 : rs2838891 • ## Test for heterogeneity: X^2( 3 ) = 231.71 ( p-value 0 ) • ## >plot(LungOR, ylab="") # Forest Plot • ## # xlog=TRUE : x-axis tick marks are exponentiated ## Meta-Analysis using R (continuous) • ## >funnelplot() • ## metabias performs the test for publication bias • ## Test of OR=1 : z= 10.39 p = 0.000 ## Meta-Analysis using Stata (continuous) • ## Test of OR=1 : z= 0.98 p = 0.326 ## Meta-Analysis using Stata (continuous) • ## Example2 : rs1051730 • ## Test of OR=1 : z= 9.27 p = 0.000 ## Meta-Analysis using Stata (continuous) • ## Test of OR=1 : z= 9.27 p = 0.000 • ## Test of ES=1 : z= 9.27 p = 0.000 • ## Thank you!!! Yüklə 451 b.

Dostları ilə paylaş:

Verilənlər bazası müəlliflik hüququ ilə müdafiə olunur ©genderi.org 2022
rəhbərliyinə müraciət Ana səhifə