I am having difficulty finding out what analysis suits my question best. My data can be found at: https://docs.google.com/spreadsheets/d/1roKj3DBEI05d6aatqA5Ge0mSIzPeBVTTXgDjaqCJ2fQ/edit?usp=sharing
It looks like this:
# A tibble: 132 x 65
category channel PPN1 PPN2 PPN3 PPN4 PPN5 PPN6 PPN7 PPN8 PPN9 PPN10 PPN11 PPN12
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 0 1 -20.4 49.2 -38.0 51.9 -25.5 2.85 21.1 113. -151. -180. 417. -12.0
2 1 1 -21.7 16.7 -2.34 -7.73 22.9 -41.1 33.6 -195. -101. -72.5 146. -70.4
3 2 1 24.8 24.1 -41.7 -29.2 40.1 -20.4 8.00 -288. -94.8 44.3 8.41 -47.0
4 0 2 -1.40 -36.0 19.7 52.3 30.9 18.5 -29.1 544. 101. 273. 101. 2.69
5 1 2 13.9 -48.0 -19.9 -34.5 -19.1 28.6 -32.0 -251. 167. 59.9 83.1 51.3
6 2 2 -44.9 -26.7 39.5 10.8 -38.1 10.5 -46.9 -79.0 119. -15.0 116. 3.01
7 0 5 -10.9 7.96 31.2 -83.9 -30.4 41.6 -35.0 616. -199. 175. 11.7 22.1
8 1 5 -36.0 1.32 31.3 -69.5 -10.7 -65.9 37.4 -252. 0.687 -32.7 141. -39.2
9 2 5 -33.9 -21.8 8.97 -45.5 12.5 -3.43 17.2 -206. -60.8 -36.2 102. -38.5
10 0 6 86.1 -6.47 -114. 158. 61.0 100. -74.2 14.4 -7.63 -15.1 -70.2 -39.8
# … with 122 more rows, and 51 more variables: PPN13 <dbl>, PPN14 <dbl>, PPN15 <dbl>, PPN16 <dbl>,
# PPN17 <dbl>, PPN18 <dbl>, PPN19 <dbl>, PPN20 <dbl>, PPN21 <dbl>, PPN22 <dbl>, PPN23 <dbl>, PPN24 <dbl>,
# PPN25 <dbl>, PPN26 <dbl>, PPN27 <dbl>, PPN28 <dbl>, PPN29 <dbl>, PPN30 <dbl>, PPN31 <dbl>, PPN32 <dbl>,
# PPN33 <dbl>, PPN34 <dbl>, PPN35 <dbl>, PPN36 <dbl>, PPN37 <dbl>, PPN38 <dbl>, PPN39 <dbl>, PPN40 <dbl>,
# PPN41 <dbl>, PPN42 <dbl>, PPN43 <dbl>, PPN44 <dbl>, PPN45 <dbl>, PPN46 <dbl>, PPN47 <dbl>, PPN48 <dbl>,
# PPN49 <dbl>, PPN50 <dbl>, PPN51 <dbl>, PPN52 <dbl>, PPN53 <dbl>, PPN54 <dbl>, PPN55 <dbl>, PPN56 <dbl>,
# PPN57 <dbl>, PPN58 <dbl>, PPN59 <dbl>, PPN60 <dbl>, PPN61 <dbl>, PPN62 <dbl>, PPN63 <dbl
I want to predict category based on the values under all subjects (PPN1,PPN2..). I also want to know what Channels are best at predicting this.
What analysis (in R) would you recommend?
I have looked into Repeated Measures ANOVA, mixed effect modelling (category as fixed and subject ID as random effect) and Linear Discriminant Analysis but none have satisfied my needs (yet).
This is my first statistical analysis so it might be a simple question. Thanks for your time!