Description Usage Arguments Value Author(s) Examples
Integrates all the necessary functions and computes the SSI. The number of alternatives, attributes, simulations and the minimum threshold for pattern length can be adjusted.
1 2 | computeSSI(df, dfRan, participant, trial, alternative, attribute, num_alt,
num_att, threshold, iter)
|
df |
Object of class data frame |
dfRan |
The same object used for creating random data. |
participant |
Identifies each unique subject. |
trial |
Identifies each unique trial. |
alternative |
Represents column with eye fixations to different alternatives. |
attribute |
Represents column with eye fixations to different attributes. |
num_alt |
Number of alternatives in the experiment. |
num_att |
Number of attributes in the experiment. |
threshold |
Sets the threshold for pattern length to two or four. |
iter |
Number of simulation iterations. |
A data set with all identified alternative- and attribute-wise patterns and a data set with all corresponding SSI values.
Sonja Perkovic, bnsp@leeds.ac.uk
1 2 3 4 5 6 7 8 9 10 11 | #IMPORTANT! Variable names in your data set should match to the ones in the example below!
## Not run:
df <- data.frame(participant = rep(c(1:50), each = 400),
trial = rep(c(1:200), each = 100),
alternative = sample(1:4, 20000, TRUE),
attribute = sample(c("a","b","c","d"), 20000, TRUE))
SSI <- computeSSI(df, df, "participant", "trial", "alternative", "attribute", 4, 4, 4, 1000)
## End(Not run)
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