Hi All,

I been cracking my brain to get this right and hopefully I can get different ways to do it.

Here is a subset of my data :

So the variable that i want are time factor, color and linear extension. I wanted to create a column to get mean of the net linear extension of each color by time factor. SO it will be yellow's mean linear extension at time 2 subtract yellow's mean linear extension at time 1. Then yellow's mean linear extension at time 1 subract time 0. So to get the difference.

This is what I did -

script :

library(ggplot2)

library(rlang)

attach(data1)

library(FSA)

library(dplyr)

attach(colormorph)

sum = Summarize(Linear.Extension.mm.~ Time_factor + Colour)

sum$se = sum$sd / sqrt(sum$n)

sum # # to get the mean

ON CONSOLE -

Time_factor Colour n nvalid mean sd min Q1 median Q3 max

1 Time_0 Blue 15 15 75.19400 15.84137 46.20 67.5800 75.10 77.6950 118.29

2 Time_1 Blue 15 15 91.82333 17.40502 67.00 78.7550 87.94 104.3500 123.57

3 Time_2 Blue 15 15 116.15533 18.38197 92.37 103.3100 109.71 127.2450 152.37

4 Time_0 Brown 20 20 69.48950 11.81186 49.50 59.7250 69.28 80.7250 88.06

5 Time_1 Brown 20 20 83.55600 14.57220 56.72 73.6475 84.70 92.3575 108.75

6 Time_2 Brown 20 19 103.41211 22.14756 63.50 89.7200 99.14 122.7500 144.36

7 Time_0 Yellow 15 15 69.56000 11.21474 48.18 64.4100 67.14 74.0550 93.30

8 Time_1 Yellow 15 15 91.40667 17.94788 58.70 81.4550 89.81 97.5900 128.26

9 Time_2 Yellow 15 15 118.70533 20.45002 95.28 103.6850 114.38 125.0550 163.88

se

1 4.090223

2 4.493957

3 4.746204

4 2.641212

5 3.258443

6 4.952344

7 2.895632

8 4.634123

9 5.280173

Script :

colormorphdata %>%

group_by(Colour) %>%

arrange(Time_factor) %>%

mutate(netTLE = mean - lag(mean, default= first(mean)))

*-- this is where i got stuck*

I am wondering if anyone got any other way to calculate the difference in mean? Do I have to create a new mean column.

Thanks in advance!