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How to calculate the z score for grouped data in R?
To calculate the z score for grouped data, we can use ave function and scale function. For example, if we have a data frame called df that contains a grouping coloumn say GROUP and a numerical column say Response then we can use the below command to calculate the z score for this data −
ave(df$Response,df$GROUP,FUN=scale)
Example
Consider the below data frame −
grp<-sample(LETTERS[1:3],20,replace=TRUE) Response<-rpois(20,8) df1<-data.frame(grp,Response) df1
Output
grp Response 1 A 8 2 A 11 3 A 14 4 A 10 5 C 11 6 B 8 7 A 5 8 A 6 9 A 9 10 B 5 11 C 13 12 B 4 13 C 9 14 A 5 15 C 8 16 A 6 17 A 5 18 A 7 19 A 4 20 A 6
Calculating z score for Response by grouping column grp −
Example
ave(df1$Response,df1$grp,FUN=scale)
Output
[1] 0.2120368 1.2457162 2.2793957 0.9011564 0.3382407 1.1208971 [7] -0.8216426 -0.4770828 0.5565966 -0.3202563 1.2402159 -0.8006408 [13] -0.5637345 -0.8216426 -1.0147221 -0.4770828 -0.8216426 -0.1325230 [19] -1.1662024 -0.4770828
Example
class<-sample(c("first","second","third"),20,replace=TRUE)
Y<-rnorm(20)
df2<-data.frame(class,Y)
df2Output
class Y 1 first -0.11728051 2 second 0.52111014 3 third 0.10489245 4 second -1.26830798 5 second 1.43719885 6 second -0.06000703 7 second 0.11140428 8 first -0.58586144 9 first 1.33474582 10 second 0.30187417 11 third 0.73870989 12 third -0.80603254 13 third 1.32022423 14 third -1.18979778 15 third 0.81707529 16 third -0.70428792 17 third 0.47795339 18 third 1.27301587 19 second 0.71368222 20 third -0.36603555
Calculating z score for Y by grouping column class −
Example
ave(df2$Y,df2$class,FUN=scale)
Output
[1] -0.32736040 0.32592308 -0.06879654 -1.83319129 1.43127698 -0.37525369 [7] -0.16842857 -0.79529132 1.12265172 0.06139266 0.63815798 -1.08483444 [13] 1.28677408 -1.51288290 0.72556607 -0.97134937 0.34731243 1.23411828 [19] 0.55828083 -0.59406558
Updated on: 16-Mar-2021
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