GLM fit or Cubic smoothing spline for categorical boundary data?? (Pragati Rao )

Subject: GLM fit or Cubic smoothing spline for categorical boundary data??
From:    Pragati Rao  <pragatir@xxxxxxxx>
Date:    Fri, 4 May 2012 16:43:53 +0530
List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>

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Hi all,

I have identification responses for stimuli along F2 and VOT continuums
from a group of subjects. I tried fitting glmfit() with logistic regression
in MATLAB because each subject had to choose either 'pa' or 'ta' for F2 and
'ta' or 'da' for VOT task. However, in many subjects I noticed that the
curve leaves out many data points and gives absurd values for categorical
boundaries. So I tried fitting cubic spline using csaps(). As expected the
curve fits very well. I have attached png files of results obtained through
both techniques. Can we use cubic smoothing spline on such a data set?

I do not have a strong base in statistics. Any help will be greatly
appreciated.

Regards,
Pragati Rao
Research Officer,
All India Institute of Speech and Hearing,
Mysore, India.

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Hi all,<br><br>I have identification responses for stimuli along F2 and VOT=
 continuums from a group of subjects. I tried fitting glmfit() with logisti=
c regression in MATLAB because each subject had to choose either &#39;pa&#3=
9; or &#39;ta&#39; for F2 and &#39;ta&#39; or &#39;da&#39; for VOT task. Ho=
wever, in many subjects I noticed that the curve leaves out many data point=
s and gives absurd values for categorical boundaries. So I tried fitting cu=
bic spline using csaps(). As expected the curve fits very well. I have atta=
ched png files of results obtained through both techniques. Can we use cubi=
c smoothing spline on such a data set? <br>
<br>I do not have a strong base in statistics. Any help will be greatly app=
reciated.<br><br>Regards,<br>Pragati Rao<br>Research Officer,<br>All India =
Institute of Speech and Hearing,<br>Mysore, India.<br><br>

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