<p>Check out chapter 3 of Macmillan and Creelman on rating scales. You have 3 ratings: left arrow (very confident it is on the left), space bar (not sure), right arrow (very confident it is on the right). You also have non-responses which may be equivalent to a space bar "not sure" or might be something else. I would probably want to know more about why they did not respond (and how often) before deciding what to do.</p>

<p>You also have 3 stimulus types (LVF-word, RVF-word, and double non-word) which makes things harder and I don't think is covered in M &amp; C. That said, you can extend their examples to 3 stimuli pretty easily. The index of sensitivity d' is a measure of distance between two distributions. It sounds like you want to know the distance between the LVF-word and double non-word distributions relative to the distance between the RVF-word and double non-word distributions, but maybe you only care about the LVF-word and RVF-word comparison.</p>

CC BY-SA 4.0
2019-04-25T18:50:21.737Z
2019-04-25T18:50:21.737Z
StrongBad
<p>i have a specific experimental setup (at least i think so :) It's a replication and i don't know how to correctly determine the false alarm rate for the visual fields since in the article i replicate the FA calculation procedure is not explicite shown. But my impression is that it kind of deviates from a simple 50% noise 50% signal+noise design. Moreover correct d'prime and bias measures depend on the calculated FA% scores. Maybe the design as such is not suitable for calculation of such SDT meassures? I read through the Nacmilian Creelman book (though not very carefully) and am not able to find a solution.</p>

<p>ok it's a lateralized lexical decision study testing the left hemisphere superiority in word recognition ( better word - non(pseudo)word discrimination in the Right vs Left visual field)</p>

<ol>
<li>overall 256 trials</li>
<li>on every trial 2 letter strings are presented for 100 ms: one string to the left and one to the right of a fixation point. ( xxxxx + xxxxx )</li>
<li>on 128 trials a word is presented  randomly to the left and right accompanied by a pseudoword: 64 RVF word presentations (e.g. gilus + virus) and 64 LVF word presentations (e.g. virus + gilus)</li>
<li>on 128 trials pseudwords are presented to both sides-hemifields e.g.(mudo + mumi).</li>
</ol>

<p>Subjects must press left button if word in LVF right button if word in RVF and spacebar if nonwords are in both hemifields.</p>

<p>Generally i would like to determine the d' or A' and bias measures for each hemifield, the correct calculation of FA% is crucial.</p>

<p>The Hit rate determination for LVF and RVF seems straight forward: correct left and right presses, each divided by 64, since there are 64 word presentations in each hemifield.</p>

<p>Question 1: when it comes to determining the false alarm rate for one hemifield which i would like to use for d' calculation: should i divide the measured FAs on one side by all possible FA occurences on that side i.e. 192 (128  bilateral nonword presentations + 64 nonwords in word-nonword trials)?</p>

<p>Question 2: because the script did not repeat timed out trials should they be  considered as misses?</p>

<p>thanks 
Kuba</p>

<signal-detection>
how to correctly determine false alarm rate (in a specific experimental setup)
Jakub Paszulewicz
# how to correctly determine false alarm rate (in a specific experimental setup)

(Asked by: username_0 on 2019-04-25)

i have a specific experimental setup (at least i think so :) It's a replication and i don't know how to correctly determine the false alarm rate for the visual fields since in the article i replicate the FA calculation procedure is not explicite shown. But my impression is that it kind of deviates from a simple 50% noise 50% signal+noise design. Moreover correct d'prime and bias measures depend on the calculated FA% scores. Maybe the design as such is not suitable for calculation of such SDT meassures? I read through the Nacmilian Creelman book (though not very carefully) and am not able to find a solution.

ok it's a lateralized lexical decision study testing the left hemisphere superiority in word recognition ( better word - non(pseudo)word discrimination in the Right vs Left visual field)

1. overall 256 trials
2. on every trial 2 letter strings are presented for 100 ms: one string to the left and one to the right of a fixation point. ( xxxxx + xxxxx )
3. on 128 trials a word is presented randomly to the left and right accompanied by a pseudoword: 64 RVF word presentations (e.g. gilus + virus) and 64 LVF word presentations (e.g. virus + gilus)
4. on 128 trials pseudwords are presented to both sides-hemifields e.g.(mudo + mumi).

Subjects must press left button if word in LVF right button if word in RVF and spacebar if nonwords are in both hemifields.

Generally i would like to determine the d' or A' and bias measures for each hemifield, the correct calculation of FA% is crucial.

The Hit rate determination for LVF and RVF seems straight forward: correct left and right presses, each divided by 64, since there are 64 word presentations in each hemifield.

Question 1: when it comes to determining the false alarm rate for one hemifield which i would like to use for d' calculation: should i divide the measured FAs on one side by all possible FA occurences on that side i.e. 192 (128 bilateral nonword presentations + 64 nonwords in word-nonword trials)?

Question 2: because the script did not repeat timed out trials should they be considered as misses?

thanks
Kuba

**Tags:** signal-detection


---

## 1 answers

### Answer by username_1 on 2019-04-25. Score: 1

Check out chapter 3 of Macmillan and Creelman on rating scales. You have 3 ratings: left arrow (very confident it is on the left), space bar (not sure), right arrow (very confident it is on the right). You also have non-responses which may be equivalent to a space bar "not sure" or might be something else. I would probably want to know more about why they did not respond (and how often) before deciding what to do.

You also have 3 stimulus types (LVF-word, RVF-word, and double non-word) which makes things harder and I don't think is covered in M & C. That said, you can extend their examples to 3 stimuli pretty easily. The index of sensitivity d' is a measure of distance between two distributions. It sounds like you want to know the distance between the LVF-word and double non-word distributions relative to the distance between the RVF-word and double non-word distributions, but maybe you only care about the LVF-word and RVF-word comparison.


---

