<p>I found that currently the form of psychometric function assumes that the proportion correct lies between 0.5-1 given the range of stimulus level, but how to fit a psychometric function when the subject's performance never goes to 1 (and it is not because of lapse)?</p>

<p>An example of how this situation can happen: suppose I want to study how stimulus presentation time affect a small target's visibility in a given peripheral visual field location by a 2AFC task. The target's feature is fixed throughout the experiment. I can imagine that with longer stimulus presentation time (like 1 ms vs. 200 ms), subject can make more correct responses, but because of the limit of peripheral vision, the correct response rate can never go to 100% even if you present the stimulus for a very long time. How can I fit a psychometric function (proportion correct ~ stimulus presentation time) to data like this?</p>

<measurement><methodology><vision>
Fit a psychometric function when the maximum is not 100% (not because of lapse)
Cloudy
# Fit a psychometric function when the maximum is not 100% (not because of lapse)

(Asked by: username_0 on 2018-11-11)

I found that currently the form of psychometric function assumes that the proportion correct lies between 0.5-1 given the range of stimulus level, but how to fit a psychometric function when the subject's performance never goes to 1 (and it is not because of lapse)?

An example of how this situation can happen: suppose I want to study how stimulus presentation time affect a small target's visibility in a given peripheral visual field location by a 2AFC task. The target's feature is fixed throughout the experiment. I can imagine that with longer stimulus presentation time (like 1 ms vs. 200 ms), subject can make more correct responses, but because of the limit of peripheral vision, the correct response rate can never go to 100% even if you present the stimulus for a very long time. How can I fit a psychometric function (proportion correct ~ stimulus presentation time) to data like this?

**Tags:** measurement, methodology, vision


---

## 0 answers

