[R-meta] Questin about Two moderators using R-metafor package

[Yumi]

Dear all,


I am doing a simulation study that includes two moderators in Meta-regression and investigate how the Accuracy of Parameter Estimation changes with the Number of Primary Studies included. 
The effect size is Pearson correlation, and I use the rma.uni() in metafor package. The equation is  yi<-0+xi*��1+xj*��2+e, and the two  regression coefficients are ��1 and ��2.
I found an interesting phenomenon that Bias and Power on the estimation of ��1 are far different from ��2.
When K=20,40,60,80,100,120,
I got the results as following:
Bias1=-0.49,-0.50,-0.49,-0.50,-0.50,-0.49
Bias2=0.00,-0.00,-0.00,-0.00,0.00,-0.00
Power1=0.0504, 0.0522, 0.0543, 0.052, 0.0499, 0.0506
Power2=0.9988, 1, 1, 1, 1, 1
I was wondering if it is meaningful to discuss the big differences between the results on two coefficients or I can just take the mean value between Bias1 and Bias2.


Sincerely,
Fang


The statements are as following.



library(metafor)

 

K<-20   #K=20,40,60,80,100,120

��1<-0.2

��2<-0.2

tau2<-0.32

output<-list(id=NULL,beta1=NULL,beta2=NULL,ci.lb1=NULL,ci.ub1=NULL,ci.lb2=NULL,ci.ub2=NULL)

 

for(i in 1:1000)

{output$id<-append(output$id,i)

nn<-rlnorm(K, meanlog =1,sdlog=0.9)

n<- round(nn*K)

n[n<25]<-25

n[n>1000]<-1000

vv<-1/(n-3)

vi<-sqrt(vv)

e<-rnorm(K, mean = 0, sd = sqrt(vv + tau2))

xi<-rnorm(K)

xj<-rnorm(K)

yi<-0+xi*��1+xj*��2+e




out<-rma.uni(yi,vi, mods=~xi+xj, tau2=tau2,test="knha",method="DL")

output$beta1<-append(output$beta1,out$b[1])

output$beta2<-append(output$beta2,out$b[2])

output$ci.lb1<-append(output$ci.lb1,out$ci.lb[1])

output$ci.ub1<-append(output$ci.ub1,out$ci.ub[1])

output$ci.lb2<-append(output$ci.lb2,out$ci.lb[2])

output$ci.ub2<-append(output$ci.ub2,out$ci.ub[2])

write.table(output,"D:/20-0.2-0.2-0.32.txt")

}








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