I'm trying to figure out which way I should deal with my data

I have data sampled from 2 "general areas" on opposite sides of the country.

in these general areas there are roughly 50 trakts placed (in a grid, random staring point) A trakt contain 16 sample plots.

Trakts have been revisited each year for a duration of 4 years

2x4x50 = 400 rows (actual number is 373 rows when i have removed trakts where not enough plots could be sampled due to terrain etc

rows = trakts

Columns= the measured variable

i got 8-10 columns i want to use

short example how the data looks now:

V1 - predictor, (4 different columns)

V2 - Response variable = proportional data

Code:

```
Area Year Trakt V1 V2
A 2015 1 25.165651 0
A 2015 2 11.16894652 0.1
A 2015 3 18.231 0.16
A 2014 1 3.1222 N/A
A 2014 2 6.1651 0.98
A 2014 3 8.651 1
A 2013 1 6.16416 0.16
B 2015 1 9.12312 0.44
B 2015 2 22.2131 0.17
B 2015 3 12.213 0.76
B 2014 1 1.123132 0.66
B 2014 2 0.000 0.44
B 2014 3 5.213265 0.33
B 2013 1 2.1236 0.268
```

*nested by trakts? should i rename some variable? i could go with A1 A2 A3 A4 B1 B2 B3 B4 or something to give each trakt its own name

I'll be doing lm, glm, glmms and all data analysis needed to get there with this dataset

I'm using R-studio

i have started by just using one area from one year to get going but i will soon need to know how to use all my data

looking forward to your answers!