How to save all the information obtained from a loop?

[DC7]

Hi community
I am writing this issue in connection with a former query. where a loop has been run:

for(i in 1:length(bacteria_names)){
  ma_model <- rma.mv(yi, vi, data = final_csv, subset = (Bacteria == bacteria_names[i]))
  re_table <- coef(summary(ma_model))
  df[i, -1] <- re_table
}

• I am seeing that the re_tableonly stores result for a single loop, not for all the loops. How can I save all the results?

• Another query is, as per the tutorial of metafor the summary(ma_model) command should show heterogeneity of the data like: tau^2, I^2, Q value, etc. I am getting only the Q-value information and that too for only one loop. How can I get all of them for all the loops?
  Here's what I get when I use summary(ma_model):

> summary(ma_model)

Multivariate Meta-Analysis Model (k = 6; method: REML)

  logLik  Deviance       AIC       BIC      AICc 
 -2.1902    4.3804    6.3804    5.9898    7.7137   

Variance Components: none

Test for Heterogeneity:
Q(df = 5) = 9.4612, p-val = 0.0920

Model Results:

estimate      se     zval    pval    ci.lb   ci.ub 
 -0.0855  0.0950  -0.8998  0.3682  -0.2718  0.1007    

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Thanks you very much in advance.
DC7

[GreyMerchant]

Hello!

There is an easy way to do it. You simply need re_table as a list. So in my example below my_list would work similar to your re_table where we assign each then. Have a look at my_list after the loop

my_list <- list()

for(i in 1:10){
  my_list[[i]] <- sample(1:10,3)
}

my_list

[DC7]

Thanks. But, it gives me the same result. Still i am getting result for only a single loop.

[GreyMerchant]

DId you try the example I had? You will see that all results get saved.

[DC7]

yes, I have seen that works in your example. But not in my case. I don't know why.

[GreyMerchant]

Can you share a proper reprex? FAQ: How to do a minimal reproducible example ( reprex ) for beginners - #2 by andresrcs

[DC7]

I am not sure reprex of which portion do you want. Actually it is a long script and lots of data are there.
Secondly, the problem lies in the ma_model. I want all the ma_model value for all the loops. It gives result for only a single loop which is

> ma_model

Multivariate Meta-Analysis Model (k = 6; method: REML)

Variance Components: none

Test for Heterogeneity:
Q(df = 5) = 9.4612, p-val = 0.0920

Model Results:

estimate      se     zval    pval    ci.lb   ci.ub 
 -0.0855  0.0950  -0.8998  0.3682  -0.2718  0.1007    

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Thanks

[GreyMerchant]

A reprex is meant to represent your problem as a minimal reproducible example. The code I provides shows how you would be able to assign repeatedly to an object and be able to look at all the values. Without having your code as a more simple example I cannot see how you're trying to incorporate it and can't really advise. If you're getting the same result then re_table is probably not a list and probably not assigning it to lists as re_table[[i]]

[DC7]

Hi thanks for your time. Is it possible for you to use the data frame in the referred query? I am also using the same code that has been used in the referred query.

(I am referring you to that question because it is really difficult to create a reprex of my data. As, I am working with a very complex data)

[DC7]

@GreyMerchant Sir/madam- please copy and paste the following table save as all_es.csv in the desktop and use that with the following code:

study	year	test	n_controls	n_patients	age_controls	age_patients	mean_controls	mean_patients	sd_controls	sd_patients	yi	vi
Caraquez	1998	n-back	12	15	39.1	23.4	1.01	15.4	31.1	0.9	-0.67601411442671	0.158462871905632
Caraquez	1998	n-back	12	15	39.1	23.4	1.01	54	2.1	7	-9.47933975490664	1.81403485535099
Franzen	2012	n-back	65	56	67.1	66.9	10	47	91.1	5	-0.549607753881664	0.03448997594063
Franzen	2012	n-back	65	56	67.1	66.9	50	67	4.1	2	-5.11910608650243	0.141527903385833
Franzen	2012	n-back	65	56	67.1	66.9	50	67	6.1	2	-3.61295800630745	0.087181698553085
Lieu	2012	digit_span	102	99	21.1	23.4	24	10	21.5	5	0.887578672128736	0.021864622961224
Lieu	2012	digit_span	102	99	21.1	23.4	12	20	1.5	5	-2.17285011427459	0.031649403358949
Lieu	2012	digit_span	102	99	21.1	23.4	12	20	1.9	9	-1.23386292200698	0.023692040401736
McMullin	1990	n-back	10	10	35.6	25.1	1.02	111	0.29	0.29	-363.179151876099	3297.67740893607
McMullin	1990	n-back	10	10	35.6	25.1	1.02	131	0.5	0.29	-304.549916872949	2318.966296683
McMullin	1990	n-back	10	10	35.6	25.1	1.02	1	2.5	0.29	0.01076236528614	0.200002895712664
Meyer	1992	digit_span	75	80	22.2	54.5	56	61	0.9	6.8	-1.00999884488257	0.029123970967734
Meyer	1992	digit_span	75	80	22.2	54.5	56	61	0.9	6.8	-1.00999884488257	0.029123970967734

Code:

library(RCurl)
library(bitops)
library(metafor)
library(Formula)
library(dplyr)
library(ggforestplot)

all_csv <- read.csv("~/Desktop/all_es.csv")
Bacteria <- unique(all_csv$Bacteria)






single_bacteria <- all_csv %>% count(Bacteria, sort = TRUE) %>% 
  filter(n == 1) %>% select(Bacteria) %>% .$Bacteria
single_bacteria
[1] "Adlercreutzia"   "Asaccharobacter" "Atopobium"

# Keep only those bacteria that have >1 studies without having to type each bacteria out
final_csv <- all_csv[which(!all_csv$Bacteria %in% single_bacteria), ]

# Our usual code, except now all_csv is replaced with final_csv
bacteria_names <- unique(final_csv$Bacteria)

df <- data.frame(matrix(NA, ncol = 7, nrow = length(bacteria_names)))
df[, 1] <- bacteria_names
names(df) <- c("Bacteria", "estimate", "se", "zval", "pval", "ci.lb", "ci.ub")
df

ma_model <- list()

for(i in 1:length(bacteria_names)){
  ma_model[[i]] <- rma.mv(yi, vi, data = final_csv, subset = (Bacteria == bacteria_names[i]))
  re_table <- coef(summary(ma_model))
  df[i, -1] <- re_table
}

ma_model

I think it will help you to work with my problem.

Thanks,
DC7

[cmues]

Seems like no one is helping you because copy/pasting a table like that doesn't just work, and requires some effort to get into R (I tried).

Also, your code already doesn't work on the second line (after the libraries). The Bacteria column/data is no where to be found.

[nirgrahamuk]

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[Bugs]

You could use a list structure to save the output using the for loop indices. You could also try using a matrix. For a large dataset I would suggest defining the size of the matrix. Increasing matrix size dynamically is time consuming and your program will take a long time to run.
Try a small dataset first. Get that to work, then scale up. Starting with the full data set will waste your time making mistakes that should have been solved with a small mockup. If you can get the program to work with five variables then you understand it well enough to scale up.