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Inverse of Probit

3 messages · Calum, David Winsemius, Ben Bolker

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Hi there,
I hope someone can help me.

I have a dataset of Concentration against Mortality, and I am trying to
compare the use of Logit and Probit models using this data.

The issue I am having is trying to back transform the data from the probit
model, to plot it in normal space instead of log space.
I know this can be done with a logit model using the code below, where
ilogit is a function for the inverse logit:

NEWCONC <- seq(0,0.6, length=25)
NEWMORT <- predict(LOGIT, Conc=NEWCONC, se=TRUE)

plot(data=DATA, Prop~Conc)
lines(NEWCONC, ilogit(NEWMORT$fit))

However, I can't seem to find a function equivalent to ilogit for a probit
model, that I could use in this code:

NEWCONC <- seq(0,0.6, length=25)
NEWMORT <- predict(PROBIT, Conc=NEWCONC, se=TRUE)

plot(data=DATA, Prop~Conc)
lines(NEWCONC,###INVERSE PROBIT### (NEWMORT$fit))


Any advice on this issue would be appreciated,
Thanks,
Calum



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On Nov 19, 2013, at 10:59 AM, Calum wrote:

            
You should be looking at ?predict and paying particular attention to the 'type' argument. I think you want: type='response'
David Winsemius
Alameda, CA, USA
1 day later
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David Winsemius <dwinsemius <at> comcast.net> writes:
[snip snip snip]

  There are three ways you can get the inverse-link function

1. dig into the family object: binomial(link="probit")$linkinv
2. know that the probit link is the qnorm() (Normal quantile) function,
and the inverse-probit is pnorm() (the Normal CDF). (Similarly, it
seems that a lot of users don't know that plogis()/qlogis() similarly
provide the logistic and logit functions ...
3. As David Winsemius suggests, use predict(...,type="response")
(but options #1 and #2 are useful in providing flexibility).