如何将 cat 结果保存为 data.frame

Question

Here Im trying to save my results as data.frame but I couldn't the only way I was able to show them by using "cat"

library(metafor)
id <- c(1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3)
year <- c(1978, 1983, 1974, 1989, 1974, 2002, 1990, 1974, 1998, 1989, 1974, 1983, 1978, 1998, 1978, 1974, 1974, 1998)
study.name <- c("Banninger 1978", "Roberts 1983", "Beard 1974", "Mahomed 1989", "Livingstone 1974", "Upton 2002", "Olah 1990", "Rogers 1974", "Mackrodt 1998",
                "Mahomed 1989", "Beard 1974", "Roberts 1983", "Banninger 1978", "Mackrodt 1998", "Banninger 1978", "Beard 1974", "Livingstone 1974", "Mackrodt 1998")
y <- c(-0.81, -0.87, -0.67, -0.77, -0.03, -0.94, -0.78, -0.12, -0.34, -0.34, -0.76, -0.87, -0.55, -0.99, -0.44, -0.14, -0.34, -0.76)
s <- c(0.11, 0.19, 0.05, 0.17, 0.09, 0.03, 0.08, 0.22, 0.21, 0.27, 0.15, 0.04, 0.15, 0.09, 0.02, 0.11, 0.03, 0.09)
data <- as.data.frame(cbind(id, year, study.name, y, s))

data.ids <- unique(data$id)
n.ma.binary <- length(data.ids)
for(i in 1:n.ma.binary){
  temp <- data[data$id == data.ids[i],]
  temp <- temp[order(temp$year),]                    # sorting MA by year
  
  list <- lapply(4:nrow(temp)-1, function(k) head(temp, k))
  
  
  for(j in 1:length(list)){
    dd <- as.data.frame(list[j])
    
    result <- rma(yi = as.numeric(dd$y), vi = as.numeric(dd$s))
    alpha <- 0.05
    n <- result$k       
    # To get PI
    lower.PI <- result$b - qt(1-alpha/2,n-2)*sqrt(2*result$tau2 + (result$se.tau2)^2)
    upper.PI <- result$b + qt(1-alpha/2,n-2)*sqrt(2*result$tau2 + (result$se.tau2)^2)
  
    remaining <- temp[ !(temp$study.name %in% dd$study.name), ]
    
    decision <- as.numeric(ifelse(sapply(remaining$y, function(p) 
      any(lower.PI <= p & upper.PI >= p)),"1", "0"))
    
    proportion <- mean(decision)

    cat(list.num = j, new.id = unique(temp$id), proportion = proportion, 
        lower.PI = lower.PI, upper.PI = upper.PI,  "\n")
  }
}

Is anyone able to save the results as data.frame?

Answer 1

It is a bit more involved since you are doing multiple analyses within each group. Modify your code as follows. First, insert the following before entering the first loop:

results.all <- data.frame(list.num=NA, new.id=NA, proportion=NA, lower.PI=NA, upper.PI=NA)
idx <- 0

Now replace the cat statement with the following:

idx <- idx+1
results.all[idx,] <- c(list.num = j, new.id = unique(temp$id), proportion = proportion, lower.PI = lower.PI, upper.PI = upper.PI)

Now you can print the data frame:

results.all
#   list.num new.id proportion           lower.PI           upper.PI
# 1        1      1          0  -5.75317346362513   5.07162070815196
# 2        2      1          0  -1.97747383048426   1.06346158846251
# 3        3      1          0  -1.44463494970073  0.414992978516971
# 4        4      1          0  -1.14935843511063 0.0548216056175898
# 5        5      1          0 -0.886747285977298 -0.295909268008411
# 6        6      1          0 -0.710099787395835 -0.441424896621657
# 7        1      2          0  -2.02192058321991  0.431485800611215
# 8        2      2          0  -1.13751587707834 -0.372704387238843
# 9        1      3          0  -0.80174083281866 0.0528883738022665