# How to plot a Sequential Bayes Factor as participants are added

I am currently analyzing eye-tracking data using the Sequential Bayes Factor method, and I would like to plot how the resulting Bayes Factor (BF; calculated from average looking times) changes as participants are added.

I would like the x-axis to represent the number of participants included in the calculation, and the y-axis to represent the resulting Bayes Factor.

For example, when participants 1-10 are included, BF = [y-value], and that is one plot point on the graph. When participants 1-11 are included, BF = [y-value], and that is the second plot point on the graph.

Is there a way to do this in R?

For example, I have this data set:

``````ID      avg_PTL
<chr>     <dbl>
1 D07   -0.0609
2 D08    0.0427
3 D12    0.112
4 D15   -0.106
5 D16    0.199
6 D19    0.0677
7 D20    0.0459
8 d21   -0.158
9 D23    0.0650
10 D25    0.0579
11 D27    0.0463
12 D29    0.00822
13 D30    0.00613
14 D36   -0.0484
15 D37    0.0312
16 D39    0.000547
17 D44    0.0336
18 D46    0.0514
19 D48    0.236
20 D51   -0.000487
21 D60    0.0410
22 D61    0.0622
23 D62    0.0337
24 D64   -0.125
25 D65    0.215
26 D66    0.200
``````

And I calculate the BF with:

``````bf.mono.correct = ttestBF(x = avg_PTL_mono_correct\$avg_PTL)
``````

Any tips are much appreciated!

You can use `sapply` to run the test multuiple times and just subset the vector of observations each time. For example
``````srange <- 10:nrow(avg_PTL_mono_correct)