Model studies in one analysis using treatment as a five level moderator in a meta-regression

Hello,


I am medical student, writing a meta-analysis on complication and reoperation rates after the five most common treatments of distal radius fractures. I have been busy with the statistics for months by my self, but find it quite hard since our classes were very basic. Now I want to compare the treatment modalities to see if there are significant differences. Using R I was able to synthesize the complication rates and reoperation rates for each treatment method. But I never had any R course and managed by trial and error, so the code probably doesn't look that great. Someone told me I could best model the data in one analysis using treatment as a five level moderator in a meta-regression. Can some help me with the R code to do this? Your help would be very much appreciated.


Thank you,


Jay


Study| Event Type| Treatment| Number of Events (n)| N| n/N|

Kumaravel| Complications| EF| 3| 23| 0,1304348|

Franck| Complications| EF| 2| 20| 0,1|

Schonnemann| Complications| EF| 8| 30| 0,2666667|

Aita| Complications| EF| 1| 16| 0,0625|

Hove| Complications| EF| 31| 39| 0,7948718|

Andersen| Complications| EF| 26| 75| 0,3466667|

Krughaug| Complications| EF| 22| 75| 0,2933333|

Moroni| Complications| EF| 0| 20| 0|

Plate| Complications| IMN| 3| 30| 0,1|

Chappuis| Complications| IMN| 4| 16| 0,25|

Gradl| Complications| IMN| 12| 66| 0,1818182|

Schonnemann| Complications| IMN| 6| 31| 0,1935484|

Aita| Complications| IMN| 1| 16| 0,0625|

Dremstrop| Complications| IMN| 17| 44| 0,3863636|

Wong| Complications| PC| 1| 30| 0,0333333|

Kumaravel| Complications| PC| 4| 25| 0,16|


Dataset on my dropbox: https://www.dropbox.com/s/j1urqzr99bt76ip/Basics%20excel%20file%20complication%20and%20reoperation%20rate.xlsx?dl=0

Basics excel file complication and reoperation rate.xlsx<https://www.dropbox.com/s/j1urqzr99bt76ip/Basics%20excel%20file%20complication%20and%20reoperation%20rate.xlsx?dl=0>
www.dropbox.com
Shared with Dropbox




library(meta)
library(stargazer)
library(foreign)

All <-read.spss("C:\\Users\\313635aa.STUDENT\\Desktop\\Meta-Analyse Complications and Reoperations.sav",to.data.frame = T, use.value.labels = T)
All <- na.omit(All)

Complications <- All[which(All[,"Event_Type"] == "Complications"),]
Re_operation <- All[which(All[,"Event_Type"] == "Reoperations"),]

EF <- All[which(All[,"Treatment"] == "EF"),]
IMN <- All[which(All[,"Treatment"] == "IMN"),]
pc <- All[which(All[,"Treatment"] == "PC"),]
KW <- All[which(All[,"Treatment"] == "KW"),]
VPO <- All[which(All[,"Treatment"] == "VPO"),]

EF_C <- EF[which(EF[,"Event_Type"] == "Complications"),]
EF_R <- EF[which(EF[,"Event_Type"] == "Reoperations"),]

IMN_C <- IMN[which(IMN[,"Event_Type"] == "Complications"),]
IMN_R <- IMN[which(IMN[,"Event_Type"] == "Reoperations"),]

pc_C <- pc[which(pc[,"Event_Type"] == "Complications"),]
pc_R <- pc[which(pc[,"Event_Type"] == "Reoperations"),]

KW_C <- KW[which(KW[,"Event_Type"] == "Complications"),]
KW_R <- KW[which(KW[,"Event_Type"] == "Reoperations"),]

VPO_C <- VPO[which(VPO[,"Event_Type"] == "Complications"),]
VPO_R <- VPO[which(VPO[,"Event_Type"] == "Reoperations"),]

Output <- function(x, y, k.min=10){
file <- metaprop(Events_n, N, Study_ID, data = x)

forest.meta(file, studlab = T, pooled.totals = T, bysort = F)

dev.copy2pdf(file=y, width = 11.69, height = 8.27)
print(file)
}

R code on my dropbox: https://www.dropbox.com/s/67pnfpi10qu110v/R%20code%20voor%20forrest%20en%20funnel%20plots.rtf?dl=0

[https://cfl.dropboxstatic.com/static/images/icons128/page_white_word.png]<https://www.dropbox.com/s/67pnfpi10qu110v/R%20code%20voor%20forrest%20en%20funnel%20plots.rtf?dl=0>

R code voor forrest en funnel plots.rtf<https://www.dropbox.com/s/67pnfpi10qu110v/R%20code%20voor%20forrest%20en%20funnel%20plots.rtf?dl=0>
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Shared with Dropbox






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