This function computes the mean of each group, then divides each observation by its corresponding group mean. This is commonly done when pooling data across environments.
normalize_group_mean(x, group)
| x | the variable containing the data to normalized |
|---|---|
| group | the variable containing the groups |
Returns a vector of normalized values
Computes the mean for each group, then divides each value by the mean for the corresponding group.
“Composite Materials Handbook, Volume 1. Polymer Matrix Composites Guideline for Characterization of Structural Materials,” SAE International, CMH-17-1G, Mar. 2012.
library(dplyr) carbon.fabric.2 %>% filter(test == "WT") %>% select(condition, strength) %>% mutate(condition_norm = normalize_group_mean(strength, condition)) %>% head(10)#> condition strength condition_norm #> 1 CTD 142.817 1.0542187 #> 2 CTD 135.901 1.0031675 #> 3 CTD 132.511 0.9781438 #> 4 CTD 135.586 1.0008423 #> 5 CTD 125.145 0.9237709 #> 6 CTD 135.203 0.9980151 #> 7 CTD 128.547 0.9488832 #> 8 CTD 127.709 0.9426974 #> 9 CTD 127.074 0.9380101 #> 10 CTD 126.879 0.9365706## condition strength condition_norm ## 1 CTD 142.817 1.0542187 ## 2 CTD 135.901 1.0031675 ## 3 CTD 132.511 0.9781438 ## 4 CTD 135.586 1.0008423 ## 5 CTD 125.145 0.9237709 ## 6 CTD 135.203 0.9980151 ## 7 CTD 128.547 0.9488832 ## 8 CTD 127.709 0.9426974 ## 9 CTD 127.074 0.9380101 ## 10 CTD 126.879 0.9365706