# "meta mean "and standardization of mean

Hello friends
I am conducting a meta-analysis of single -Arm studies: the out come is reduce pain and continuous data. So I used the "meta mean" package. But I have a question. Since the mean and standard deviation of the studies were measured by different tools and have different scales, they should be standardized before the meta-analysis. How and what command can I standardize the data in meta mean ?please guide me. thanks

Hi
you can calculate standardized mean difference by using

``````df_smd <- escalc(measure = "SMD",
m1i = m1i,
m2i = m2i,
sd1i = sd1i,
sd2i = sd2i,
n1i = n1i,
n2i = n2i,
data = dat.normand1999)
``````

you get a dataframe with yi and vi, these are SMD effect size and its variance
reference: 4.1 Calculating standardized mean differences | Doing Meta-Analysis in R and exploring heterogeneity using metaforest
hope it helps

Thanks very much for your help , but I have a single mean , SD and N for intervention group and without control group(single -Arm study) so now I'm getting this error in meta for packages:

Cannot compute outcomes. Check that all of the required
information is specified via the appropriate arguments.

Hi Kindly try this, hope it helps

#######################################################
#Creating Dataset
#######################################################
study <- c("Edinburgh", "Orpington-Mild", "Orpington-Moderate", "Orpington-Severe", "Montreal-Home", "Montreal-Transfer", "Newcastle", "Umea", "Uppsala")
n <- c(155, 31, 75, 18, 8, 57, 34, 110, 60)
mean <- c(55, 27, 64, 66, 14, 19, 52, 21, 30)
sd <- c(47, 7, 17, 20, 8, 7, 45, 16, 27)
df <- data.frame(study,n,mean,sd)

library(meta)
m1 <- metamean(n = n,
mean = mean,
sd = sd,
studlab = study,
data = df,
sm = 'MLN',
random = TRUE,
warn = TRUE,
prediction = TRUE)

#######################################################

# Forest Plot & Funnel Plot

#######################################################
meta::forest(m1)
meta::funnel(m1)

1 Like

Thanks a lot , :pray

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