Dear All,
I have a question concerning the mlogit function.
In my experimental design, I collect 80 trials for each participant. The
subjects are asked to provide the answer by choosing among 4 different
alternatives.
Now I would like to model the choices of my participants as a function of nine
continuous predictors, however I cant understand how the data frame must be
re-shaped. None of the examples in the vignette and in other articles seem to
fit my dataset.
Does anybody know what would be the proper way to arrange the dataset?
Many thanks in advance
Giovanni
Here is an extract of the dataset:
Subject Trial Choice X1 X2 X3 X4 X5
X6 X7 X8 X9
Subj1 1 1 0.00 0.62 0.04
-0.84 0.12 -0.06 0.58 -0.05 0.04
Subj1 2 2 0.00 0.62 0.04
-0.84 0.12 -0.06 0.58 -0.05 0.04
Subj1 3 4 0.02 -0.01 0.02
-0.23 0.01 0.30 0.12 -0.01 0.01
Subj1 4 3 0.01 -0.02 0.03
-0.24 0.03 0.37 0.12 -0.02 0.03
Subj1 5 3 0.01 -0.02 0.03
-0.24 0.03 0.37 0.12 -0.02 0.03
Subj1 80 3 0.01 -0.02 0.03
-0.24 0.03 0.37 0.12 -0.02 0.03
Subj2 1 3 0.01 -0.04 0.03
-0.22 0.03 0.33 0.10 -0.02 0.03
Subj2 2 2 0.02 0.01 0.02
-0.12 0.01 0.26 0.07 -0.01 0.01
Subj2 3 1 0.03 -0.01 0.02
-0.12 0.02 0.23 0.07 -0.02 0.02
Subj2 4 2 -0.02 0.00 0.00
-0.19 -0.01 0.35 0.06 -0.04 0.01
Subj2 5 2 0.01 -0.01 -0.01
-0.10 0.00 0.27 0.05 -0.01 0.00
Subj2 80 2 0.01 -0.01 -0.01
-0.10 0.00 0.27 0.05 -0.01 0.00
Subj3 1 4 0.02 0.31 0.01
-0.20 0.01 0.04 0.12 -0.01 0.01
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