From: Mike Lawrence <mike_at_thatmike.com>

Date: Sat, 08 Nov 2008 12:51:24 -0400

}

Date: Sat, 08 Nov 2008 12:51:24 -0400

Hi all,

Where f(x) is a logistic function, I have data that follow: g(x) = f(x)*.5 + .5

How would you suggest I modify the standard glm(..., family='binomial') function to fit this? Here's an example of a clearly ill-advised attempt to simply use the standard glm(..., family='binomial') approach:

*########
**# First generate some data
*

########

#define the scale and location of the modified logistic to be fit

location = 20

scale = 30

# choose some x values

x = runif(200,-200,200)

# generate some random noise to add to x in order to

# simulate real-word measurement and avoid perfect fits

x.noise = runif(length(x),-10,10)

# define the probability of success for each x given the modified logistic

prob.success = plogis(x+x.noise,location,scale)*.5 + .5

# obtain y, the observed success/failure at each x

y = rep(NA,length(x)) for(i in 1:length(x)){ y[i] = sample( x = c(1,0) , size = 1 , prob = c(prob.success[i], 1-prob.success[i]))

}

#show the data and the source modified logistic

plot(x,y)

curve(plogis(x,location,scale)*.5 + .5,add=T)

*########
*

# Now try to fit the data

########

#fit using standard glm and plot the result

fit = glm(y~x,family='binomial')

curve(plogis(fit$coefficients[1]+x*fit$coefficients[2])*.5+.5,add=T,col='red',lty=2)

# It's clear that it's inappropriate to use the standard

"glm(y~x,family='binomial')"

# method to fit the modified logistic data, but what is the alternative?

-- Mike Lawrence Graduate Student Department of Psychology Dalhousie University www.thatmike.com Looking to arrange a meeting? Check my public calendar and find a time that is mutually free: http://tinyurl.com/mikescalendar (tiny url redirects to google calendar) ~ Certainty is folly... I think. ~ [[alternative HTML version deleted]] ______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Sat 08 Nov 2008 - 19:37:23 GMT

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