similar to: using metafor for meta-analysis of before-after studies

Hello I have a time-comsuming program which need to simplify, I have tested the annotated program as follow: > #define function which will be call > calsta <- function(c, n=100000) + { + i <- seq(from=0, length=c) + logx <- lchoose(NT-n, CT-i) + lchoose(n, i) + logmax <- max(logx) + logmax + log(sum(exp(logx - logmax))) + } > CT=6000 #assignment to CT >

Hello I have 4 1000*1000 matrix A,B,C,D. I want to use the corresponding element of the 4 matrices. Using the "for loop" as follow: E<-o for (i in 1:1000) {for (j in 1:1000) { E<-fisher.test(matrix(c(A[i][j],B[i][j],C[i][j],D[i][j]),2))#call fisher.test for every element } } It is so time-consuming Need vectorization Yours sincerely ZhaoXing Department of

Hello Suppose I have a matrix mat=(1:16,2) [,1] [,2] [,3] [,4] [1,] 1 5 9 13 [2,] 2 6 10 14 [3,] 3 7 11 15 [4,] 4 8 12 16 I just want to use the "apply" function to the matrix partially there is a vector end=c(2,3,1,3) #sum the 1st 2 numbers of the 1st column #sum the 1st 3 numbers of the 2nd column #sum the 1st number of the 3rd column

Hello Suppose I have a matrix mat=(1:16,2) [,1] [,2] [,3] [,4] [1,] 1 5 9 13 [2,] 2 6 10 14 [3,] 3 7 11 15 [4,] 4 8 12 16 there is a vector end=c(2,3,1,3) #coerce the 1st 2 numbers of the 1st column to a vector [1] 1 2 #coerce the 1st 3 numbers of the 2nd column and append it to the previous vector [1] 1 2 5 6 7 #coerce the 1st number of

Hello I have a 100*100 matrix which is from a intensive computation, e.g. mat. Is there any method/function that return the max of every row and the subscript of maximum value simultaneously #define the function > returnfunction<-function(x){ + value<-apply(x,1,max) + index<-apply(x,1,which.max) + } > mat<-matrix(c(3,5,7,2,1,10,4,3,2),3)#initilize the matrix for test >

Greetings, I wish to conduct a meta-analysis for which the outcome is a continuous variable measured on the same individuals before and after an intervention. Hence, the comparison is not made between two groups, but within groups, at diffrent times. Each study reports the mean outcome and SD before the intervention and the mean outcome and SD after the intervention. While p-values for

Hello T I want to order some calculation "result", there will be lots of "result" that need to calculate and order PS: the "result" is just a intermediate varible and ordering them is the very aim # problem: # For fixed NT and CT, and some pair (c,n). order the pair by corresponding result # c and n are both random variable CT<-6000 #assignment to CT

Hello I have a data consisting of 245 counties, including the population, number of illness and the geographical information of each county. Fixing each county, I want to sort the other county by distance, which can make a 245*245 matrix with each cell is the corresponding index of the county, e.g. the 3rd row of the matrix is a vector of descending order of the 245 indices, maybe

Hello I want to calculate natural logarithm of sum of combinations as follow: (R code) { com_sum=choose(2000000,482)*choose(1000000,118)+choose(2000000,483)*choose(1000000,117)+...+choose(2000000,i)*choose(1000000,600-i)+...+choose(2000000,600)*choose(1000000,0) #calculate the sum result=log(com_sum) #calculate the log of the sum } But

Hello, In SPSS the cluster analysis output includes an agglomerations schedule, which details the stages when cases are joined. Is it possible to obtain such output when performing cluster analysis in R? If so, I'd appreciate advice regarding how to obtain this information. Any assistance is appreciated, Regards Bob

This is a question of clarification. IN 2009 Higgins, Thompson and Spiegelhalter (J R Statist Soc A 172:137-159) gave WinBUGs code to get credible intervals from random effects meta analysis for the prediction interval of a new study. It appears that the predict.rma function creates approximate credible intervals (pending a function revision by the author) for that purpose. Is my assumption

Hi - I am conducting a meta-analysis and I have a matrix of f-statistics, Ns and dfs from a series of studies that tested for an interaction in a 2x2 anova. I'd like to test whether the 2x2 interaction is significant in the aggregate. Similarly, I have a matrix of chi-square statistics that I'd like to meta-analyze. How can I input these test statistics into the "metafor"

Dear all, I am very grateful that Wolfgang Viechtbauer implemented the standardised mean change for dependent groups. I was playing around a bit today, and I am not sure if I understand the "SMCR" procedure correctly. The documentation states that sd1i and sd2i are needed, but it seems to me that SMCR is ignoring sd2i (so Variances are not pooled). Instead, it uses sd1i (pre-test sd),

Dear R users, In metafor 1.6-0, the Mantel-Haenszel method is implemented by the rma.mh() function. I have observed that the sum of the weights computed by weights(x) doesn't add to 100% when x is an object of class rma.mh. The consequences of this fact can be clearly seen when a forest diagram is drawn with forest(x), which calls weights(x) (or more precisely, the method weights.rma.mh()

A new package is now available via CRAN, called metafor. The metafor package consists of a collection of functions for conducting meta-analyses in R. Fixed- and random-effects models (with and without moderators) can be fitted via the general linear (mixed-effects) model. For 2x2 table data, the Mantel-Haenszel and Peto's method are also implemented. The package also provides various plot

Hi Kim and Others, Can anyone please help me on how can I edit default labels ( "Study 1", "Study 2",...) using forest() - same question as below. Which option I should try? It would be a great help. Thanks in advance, On Sun, Dec 13, 2009 at 7:14 PM, Kim Jung Hwa <kimhwamaillist@gmail.com>wrote: > Hi All, > > I'm using forest() from metafor package to

Hi everyone, I'm using the metafor package to meta-analyze a set of proportions. This is working really well for the raw proportions, but is there a way to back-transform the arcsine transformed proportions in the rma or forest functions with the atransf option? The estimates and CIs for the transformed proportions need to be back-transformed to be the sin of the estimate squared.

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Dear R-experts! I am working on some meta-analysis using the metafor package. I would like to extract values of the confidence intervals of the effect sizes of the single studies from an rma object. Those values are printed out when plotting a forest plot using the forest function on the rma object, however I was not able to locate them. Many thanks for your help! Jokel [[alternative HTML

Hello, I once used the metawin software to perform a meta-analysis (see metawinsoft, Rosenberg et al.) and produced normal qqplot to test for a potential bias in the dataset. I now want to re-use the same dataset with the package metafor by W. Viechtbauer (great package btw). I run the qqnorm.rma.uni function. I use standardized effect sizes as in metawin. QQplot generated with metafor differs