Millisecond Forums

Whether you get one or two files depends on the script and Inquisit version you're using. At any rate, the overall D-score in the raw data file is the value in the expressions.d column in the final row of data for a given participant. As for what the score means, see the first post in this thread.

Hi,

I am running an IAT and I am trying to get familiar with the data output. For some reason I´m only getting 1 output file instead of two (according to the user manual - https://www.millisecond.com/download/library/v5/iat/pictureiat/pictureiat.manual - I should be getting two different files, the raw data and the summary data.). Does anybody knows why is this happening?

Also in the RAW Data file I am getting 180 lines of d-scores (- the practice trials). Is there a summary score for the overall association? how can I know if the association is positive or negative between the targets and the attributes?

Thank you in advance for all your help,

Andres
 

Is it possible to run a mediation with the d-scores (Greenwald, 2003, improved) as the results of the IAT for the implicit associations as a dependent variable? We are not sure about it because of the negative values and because we have a different scale (7-point lickert) which is also included in the mediation analysis. We also thought about a transformation of the d-score data or something similar before running the mediaion to make the results of the IAT comparable with our other scales or is this not necessary? The same question arises for running a regression analysis. Is this possible with the d-score results?

Maybe somebody of you has experience with something similar or can give some advice.

Thanks a lot in advance!

> So it is ok if I don't follow the recommendation in this case?

That seems like a subjective call to make, and it certainly isn't mine to make -- given that the question is neither about how scores are calculated (they are calculated using the "improved algorithm" regardless) nor to Inquisit more broadly. If you can put forth good arguments for not excluding subjects, I'd say it's fine. But I am neither in a position to find those arguments (I know nothing about your broader study) nor to judge their merit (my opinion matters little; what matters are the opinions of your co-authors, reviewers, thesis advisors, etc.).

Hope this helps.

Thanks a lot for your quick reply!
So it is ok if I don't follow the recommendation in this case? Could I justify this with arguing that I've used six IATs and I didn't want to loose any data or/and subjects?
Thanks again for helping me out!

The scores are calculated according to the improved scoring algorithm.

Whether a given subject has latencies < 300 ms in 10% or more of all trials changes nothing about the calculation of D.

Instead, the recommendation is that such subjects' data should be *discarded* entirely from any analysis. I.e., if you have a participant X who responded < 300 ms in more than 10% of all trials, you simply throw her/his entire data set away.

Hi Dave,
I hope it's not too late for this reply.
I have a few questions concerning 'expressions.d'. You wrote that the only difference between the calculation of Inquisit and the 'improved scoring algorithm' would be that subjects below 300ms on 10+% of the trials are not automatically discarded. I'm writing my bachelor thesis at the Moment and I used only the automatic generated d-scores for my calculations. now I'm asking myself if it's still ok to write, that the computation of IAT scores is based on the scoring algorithm provided by Greenwald et al. (2003) and how I could establish the fact that subjects below 300ms on 10+% of the trials were not automatically discarded? Even though I have the raw data collected it would cost me months to transfer them into a SPSS data set and compute them with the provided syntax for several reasons. So is there a convincing explanation which i could use for my argumentation why I haven't discarded subjects below 300ms? Next time i would handle it different because now I know much more about IATs and the functions of Inquisit. But for this time it would be so helpful if I could to it that way. Thanks in advance for helping me out!

D-scores are sometimes classified as indicating a "slight", "moderate" or "strong" association. The respective cutoff values are chosen to roughly correspond to typical effect size characterizations.

See https://implicit.harvard.edu/implicit/demo/background/raceinfo.html for an example.

An absolute value >= .65 would indicate a "strong" association, it is not that case that any value below that would indicate *no association*. Instead, absolute values >= .35 are usually taken to indicate a "moderate" association, while >= .15 would indicate a "slight" effect.
Anything between 0 and .15 would be taken as showing no association.

Hello, I have received conflicting reviews on cutoff scores for the IAT. In one article it is said that any value above +0.65 or below -0.65 indicates a preference one way or another. Some other areas say that any value positive or negative indicates a preference whereas 0 does not. In my data the value I receive (mean value of 150 participants) was 0.46, standard deviation of 0.31. Does this indicate a preference? I would be happy to talk more if you should have the time.

Thank you for your help,

If you used any of the templates available from the millisecond.com library, the D-scores are also recorded to the raw data files. The last line for a given participant gives you the final scores.

Of course, you can also calculate D from the raw latency data. You can use the SPSS syntax files available from the library's IAT page as a starting point.