I am a student running an IAT test for a Intro Psych class. In other words, I have no experience in IAT tests. I just had a subject take a test and I have a .dat file, but I have no idea how to read/interpret the data. The columns of data are as follows from left to right:
date
time
subject
blockcode
blocknum
trialcode
trialnum
response
correct
latency
stimulusnumber1
stimulusitem1
expressions.da
expressions.db
expressions.d
I have taken basic stats so I do know how to run basic z tests.
Please help! I'm in way over my head.
Note that the column "expressions.d" contains the Cohen's D score that indicates the direction and magnitude of the association. Inquisit keeps a running tally of this score for each trial. The last row of data for each participant therefore has the final score for that participant.
So, you could just take the last row of data for each particpant and get the value of expressions.d to get each participant's score.
-Sean
Hi,
Just one clarification. Isn't the D score the IAT score which is similar to Cohen's d but not the same thing? Most studies using the IAT report both the D score and Cohen's d. Or am I just confusing things :)?
Best,
Kaarinen
My understanding was that these are the same thing. Cohen's D is a general measure of effect size, and is computed as the difference between conditions divided by the standard deviation. That's the same way the IAT D score is computed.
However, there may be some subtle difference I'm not aware of.
In fact there is a subtle difference between the two measures. Quoting Greenwald, Banaji and Nosek (2003, p.201):
"Division of a difference between means by a standard deviation is quitesimilar to the well-known effect-size measure, d (Cohen, 1977). Thedifference between the present D measure and the d measure of effect sizeis that the standard deviation in the denominator of D is computed from thescores in both conditions, ignoring the condition membership of eachscore. By contrast, the standard deviation used in computing the effect sized is a pooled within-treatment standard deviation. To acknowledge boththis measure’s similarity to d and its difference, the present measure isidentified with an italicized uppercase letter (D) rather than an italicizedlowercase letter."
Hope this helps,
~Dave
"To understand recursion, you must first understand recursion." - Unknown Zen Master
Awesome, Dave, thanks for setting things straight.
No problem. Now here's a question for you, Sean: Do the IAT templates provide d or D? I'm just too lazy to find out myself right now. Besides, any further investigation on my part would severly conflict with my personal 'No (more) IAT' policy...;-)
Maybe this one's for Sean, then, if Dave has had it with the method :).
There's some huge difference between D and d, since many studies report both figures and these seem to differ a lot. It could be that the effect size d is calculated somewhat differently from your idea here, or there's some other differing thing to it, but the figures might be really far apart when reporting the study mean effects. For example, the first three studies in a methodological IAT paper* give the figures D=0.49/d=1.23; D=0.37/d=0.86; D=0.30/d=0.73. Cohen's d can also have a number greater than 1, whereas D cannot.
This is kinda giving me the impression that I should think about how to calculate d in addition to D for my results...
In the simplest version, Cohen's d is just the difference between two means divided by standard deviation. The IAT D, however, takes a lot more into account - at least when the improved scoring algorithm is used. This is what I was going after in a previous question concerning the need for making a SPSS syntax for my ST-IAT; is your ST-IAT algorithm simply comparing the absolute latencies in the two relevant tasks or does it, for example, also calculate the mean latencies for some practice trials to get the latency scale for an individual user. The improved scoring algo does this, among other things, but I think the ST-IAT template doesn't. Does it, however, take too long latencies (+10000ms) or great number of errors into account?
* Lane et al. (2007). Understanding and Usingthe Implicit Association Test: IV
Kaarinen:Maybe this one's for Sean, then, if Dave has had it with the method :).
Don't even get me started...;-)
Kaarinen:Cohen's d can also have a size greater than 1, whereas D cannot.
Which is not true. While Cohen's d may trail off into infinity in theory, D actually varies between -2 and +2. See Sriram, Greenwald, & Nosek (2006), p. 57, footnote 2, or Nosek & Sriram (2007), p. 396, footnote 2.
This will be my last post on the topic of IAT for a while. I'll leave the rest to Sean.
Whoops, just edited my post while you were answering :).
Has this been resolved off-forum?
Apologies for letting this drop.
The scoring algorithm used in the ST-IAT was taken directly from the IAT, which in turn was taken from the SPSS script, which in turn was based on Tony's IAT script, which in turn reflects the improved scoring algorithm reported in Greenwald, Nosek, and Banaji (2003).
Latencies above 10000 ms are indeed discarded by both the Inquisit and SPSS script. I may be misunderstanding something, but I'm not aware of any part of the improved algorithm that involves calculating "the mean latencies for some practice trials to get the latency scale for an individual user". Do you have a reference for this?
It's certainly possible that in adapting the IAT score to the ST-IAT that something isn't right, but I'm not aware of any mistakes. Is there anything in particular that seems fishy here?
I must have said that in the wrong way :). The mentioned article Greenwald, Nosek, and Banaji (2003, p. 42) summarises the difference in this way:
The improved algorithm has three substantial changes from the conventional procedure: (a) use of practice-block data (Step 1 in Table 7), (b)use of error penalties (computed in Steps 5 and 7), and (c) use of individual-respondent standard deviations to provide the measure’s scale unit (computed in Step 6 and applied in Step 11).
Now, as you might have already guessed, I'm not too knowledgeable in IAT scoring and I'm interested in this because I'd like to know if whtether I can report the running D scores as ones calculated by the improved algorithm or as something else. I'm also not even completely sure how the imporved alogrithm is applied with a ST-IAT, since the article is obviously advising the scoring of conventional IATs, which has a different number of block etc.
Basically, I'm just trying to grasp what the template calculates from the user latencies, but I'm not trying to take this to any higher level or start a methodological discussion on different procedures which would be way beyond my skills :).