Hi:

Are you trying to find something analogous to the median dose? If so, look
at function dose.p() in the MASS package and see if it does what you're
looking for. It can take a vector of quantiles as input.

HTH,
Dennis

On Wed, Jan 26, 2011 at 7:52 PM, Ahnate Lim <ahn...@gmail.com> wrote:

> Dear R-help,
>
> I have fitted a glm logistic function to dichotomous forced choices
> responses varying according to time interval between two stimulus. x values
> are time separation in miliseconds, and the y values are proportion
> responses for one of the stimulus. Now I am trying to extrapolate x values
> for the y value (proportion) at .25, .5, and .75. I have tried several
> predict parameters, and they don't appear to be working. Is this correct
> use
> and understanding of the predict function? It would be nice to know the
> parameters for the glm best fit, but all I really need are the extrapolated
> x values for those proportions. Thank you for your help. Here is the code:
>
> x <-
> c(-283.9, -267.2, -250.5, -233.8, -217.1, -200.4, -183.7, -167,
> -150.3, -133.6, -116.9, -100.2, -83.5, -66.8, -50.1, -33.4, -16.7,
> 16.7, 33.4, 50.1, 66.8, 83.5, 100.2, 116.9, 133.6, 150.3, 167,
> 183.7, 200.4, 217.1, 233.8, 250.5, 267.2, 283.9)
>
> y <-
> c(0, 0.333333333333333, 0, 0, 0, 0, 0, 0, 0, 0.333333333333333,
> 0, 0.133333333333333, 0.238095238095238, 0.527777777777778,
> 0.566666666666667,
> 0.845238095238095, 0.55, 1, 0.888888888888889, 1, 1, 1, 1, 1,
> 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5)
>
> weight <-
> c(1, 3, 2, 5, 4, 4, 3, 5, 5, 4, 5, 11, 22, 11, 15, 16, 11, 7,
> 14, 10, 16, 19, 11, 5, 4, 5, 6, 9, 4, 2, 5, 5, 2, 2)
>
> mylogit <- glm(y~x,weights=weight, family = binomial)
>
> # now I try plotting the predicted value, and it looks like a good fit,
> hopefully I can access what the glm is doing
>
> ypred <- predict(mylogit,newdata=as.data.frame(x),type="response")
> plot(x, ypred,type="l")
> points(x,y)
>
> # so I try to predict the x value when y (proportion) is at .5, but
> something is wrong..
>
> predict(mylogit,newdata=as.data.frame(0.5))
>
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>
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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