C. Nicolay writes:

> I want to fit a curve by means of logistic regression with the
> following parameters:
>
> p(x) = exp(a + bx) / (1 + exp(a + bx))
>
> with x: foil of a certain thickness and p(x): detection (yes
> / no). I want to estimate x for p(x)=1/2.
>
> This is a problem within psychometrics (psychophysics).
> But unlike the normal psychometric problems concerning
> discrimination, I would like to estimate the above mentioned
threshold.
>
> This can be seen as being equivalent to a bio-assay problem.
> But in my case all observations (n=160) are made by one person (I
> have n=62 persons). Hence, they are dependent. But estimation
> within logistic regression requests independent observations.

I'm not entirely clear what you mean, because you use n to represent
both the number of observations and the number of subjects. I assume
that you have an average of 2.6 observations per person. With k=62
people in your sample, you would have n=160 total observations.

A simple solution is to randomly select one observation per person. This
would reduce your sample size from 160 to 62, but then you still have
independence.

It does seem wasteful, though, to toss away so much data. Models that
allow for dependence in logistic regression are quite complex. If you
want to follow up on this, look for information about the generalized
linear mixed model (GLMM). You might also consider a conditional
logistic regression model, though, that is used more often for matched
pairs data.

I don't have too much experience with either model, so I can't help much
more than that.

> After my opinion the dependency of the observations do not
> influence the estimate itsself but rather its variance. But I am not
> sure. Who can give me some hints or literature?? Thank You in
> advance for your help.

Since the logistic regression model is non-linear, there is an influence
on both the estimates and the standard errors. But the influence on the
estimates is not terribly large. 

Good luck!

Steve Simon, [EMAIL PROTECTED], Standard Disclaimer.
The STATS web page has moved to
http://www.childrens-mercy.org/stats.


-----Original Message-----
From: C. Nicolay [mailto:[EMAIL PROTECTED] 
Sent: Tuesday, November 25, 2003 2:33 AM
To: [EMAIL PROTECTED]
Subject: Logistic regression with dependent observations

I want to fit a curve by means of logistic regression with the following

parameters:

p(x) = exp(a + bx) / (1 + exp(a + bx))

with x: foil of a certain thickness and
p(x): detection (yes / no).
I want to estimate x for p(x)=1/2.

This is a problem within psychometrics (psychophysics). But unlike the 
normal psychometric problems concerning discrimination, I would like to 
estimate the above mentionned threshold.

This can be seen as being equivalent to a bio-assay problem. But in my 
case all observations (n=160) are made by one person (I have n=62 
persons). Hence, they are dependent. But estimation within logistic 
regression requests independent observations.

After my opinion the dependency of the observations do not influence the

estimate itsself but rather its variance. But I am not sure.
Who can give me some hints or literature??
Thank You in advance for your help.

C. Nicolay, MS
University of Bonn (Germany)

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