On Wed, 11 Jun 2003 19:54:11 +0200
Derek Eder <[EMAIL PROTECTED]> wrote:
> This is a question about the use of the Cox proportional hazards model to analyze
> event histories.
>
> I am looking at the responses of sympathetic nervous system activity to a stimulus.
> The activity I observe is a burst that can only occur once per heart beat cycle
> (e.g., a binary count). Typically bursts occur in 60-80% of the heart cycles *
> sensory stimuli can modify these burst probabilities.
>
> I give 48 stimuli-trials at random intervals and count the number of bursts
> associated with the stimuli. For example, a person with 75% burst probability at
> rest (e.g., 36/48) may have an stimulation induced increase to 87.5% (42 bursts in
> 48 trials). There are 14 subjects in each of 3 different patient groups. Simple
> enough.
>
> But what if the stimulus reactions are modified over time? The surprise of the
> stimulus (electric shock) soon wears off and the responses (e.g., increased burst
> probability) diminish over the trials.
>
> Intuition tells me that the Cox proportional hazard model cast as in Anderson-Gill
> counting formulation is a useful tool too look for possible changes in burst
> occurrence probability across time (48 trials). Can one assume that non-uniform
> burst probabilities would manifest in the cox.zph tests of proportionality of
> hazards? I also plotted the Cox model along with a Cox model of a surrogate data
> set, formulated by randomizing the trial times (e.g., removing any temporal
> dependencies) Am I on the right track?
>
>
>
> Thank you
>
>
> Derek Eder
>
>
> Oh yes, the relevance of this question to R ... ummmm. Yes, what is the assignment
> operator in R? (Just kidding).
>
Derek- This avoids answering your question but in problems like this I have found
pooled logistic regression can be easier to use and provide more easily interpretable
predictions and their confidence intervals. I have used cluster bootstrap variance
estimators in this context to adjust for intra-subject correlations. See
@ARTICLE{dag90rel,
author = {{D'Agostino}, Ralph B. and Lee, M. L. and Belanger, A. J. and
Cupples, L. A.},
year = 1990,
title = {Relation of pooled logistic regression to time dependent {Cox}
regression analysis: {The} {Framingham} {Heart} {Study}},
journal = Statistics in Medicine,
volume = 9,
pages = {1501-1515},
annote = {time-dependent covariable; repeated measures logistic
model; person-years logistic model}
}
---
Frank E Harrell Jr Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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