I am conducting a meta-analysis of effect sizes ***d*** in R using the metafor package. ***d*** represents differences in memory scores between patients and healthy. However some studies report only subscores of the measure of interest ***d*** (e.g. several different memory scores or scores from three separate blocks of memory testing). Please see the following dummy data set with ***d*** representing the studies' effect sizes as well as their standard deviations sd.: 

```
d <- round(rnorm(5,5,1),2)
sd <- round(rnorm(5,1,0.1),2)
study <- c(1,2,3,3,3)
subscore <- c(1,1,1,2,3)
my_data <- as.data.frame(cbind(study, subscore, d, sd))

library(metafor)
m1 <- rma(d,sd, data=my_data)
summary(m1)

```

I would like to ask for your opinion for the best way how to handle these subscores - e.g.:

1. Select one subscore from each study that reports more than one
 score.
2. Include all subscores (this would violate the assumption
 of independency of the rfx model as subscores of one study come from
 the same sample)
3. For each study that reports subscores: calculate
 an average score & average standard deviation and include this
 "merged effect size" in the rfx meta-analysis.
4. Include all
 subscores and add a dummy variable indicating from which study a
 certain score is derived.