How to plot a Sequential Bayes Factor as participants are added

Question

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!

Answer 1

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)
BF <- sapply(srange, function(i) {
  extractBF(ttestBF(x = avg_PTL_mono_correct$avg_PTL[1:i]), onlybf=TRUE)
})

plot(srange, BF)

Will result in