University of Padova (IT)

Implicit assessment in Psychology

Implicit Association Test (IAT)


How much do you like Coke over Pepsi?

Single Category IAT (IAT)

How much do you like Coke?
OR


How much do you like Pepsi?

Their scores

The IAT and SC-IAT effects (i.e., the difference between the associative conditions) are expressed by using the so-called D-score, computed as:

\[\text{D-score} = \frac{M_{conditionA} - M_{conditionB}}{sd_{pooled}}\]

The steps that have to be undertaken to clean and prepare the data set for the computation make it an error prone procedure, raising replicability issues.

implicitMeasures

It’s on CRAN!

install.packages("implicitMeasures") # Install
library("implicitMeasures") # upload

…and there’s a data set you can play with:

data(raw_data)

Measures specific functions

IAT
Function Description
clean_iat() Clean IAT data
computeD() Compute IAT D-score
IATrel() Compute IAT realibility
multi_dscore() Compute & Plot multiple IAT D-scores

SC-IAT
Function Description
clean_sciat() Clean SC-IAT data
Dsciat() Compute SC-IAT D-score
multi_dsciat() Plot D-scores from two SC-IATs

Common functions

The objects obtained from functions computeD() or Dsciat() can be passed to the following functions:

Function Description
descript_d() Descriptive table of the D-scores (even in LaTeX format!)
d_distr() Plot of the results at the sample level
d_plot() Plot of the results at the individual level