On Wed, 2011-01-26 at 19:25 -1000, Ahnate Lim wrote: > Even when I try to predict y values from x, let's say I want to predict y at > x=0. Looking at the graph from the provided syntax, I would expect y to be > about 0.85. Is this right: > > predict(mylogit,newdata=as.data.frame(0),type="response")
Your original problem was the use of `newdata = as.data.frame(0.5)`. There are two problems here: i) if you don't name the input (x = 0.5, say) then you get a data frame with the name(s) "0.5": > as.data.frame(0.5) 0.5 1 0.5 and ii) if you do name it, you still get a data frame with name(s) "0.5" > as.data.frame(x = 0.5) 0.5 1 0.5 In both cases, predict wants to find a variable with the name `x` in the object supplied to `newdata`. It finds `x` but your `x` in the global workspace, but warns because it knows that `newdata` was a data frame with a single row - so there was a mismatch and you likely made a mistake. In these cases, `data.frame()` is preferred to `as.data.frame()`: predict(mylogit, newdata = data.frame(x = 0), type = "response") or we can use a list, to save a few characters: predict(mylogit, newdata = list(x = 0), type = "response") which give: > predict(mylogit, newdata = list(x = 0), type = "response") 1 0.813069 > predict(mylogit, newdata = data.frame(x = 0), type = "response") 1 0.813069 In summary, use `data.frame()` or `list()` to create the object passed as `newdata` and make sure you give the component containing the new values a *name* that matches the predictor in the model formula. HTH G > > # I get: > > Warning message: > 'newdata' had 1 rows but variable(s) found have 34 rows > > # Why do I need 34 rows? So I try: > > v=vector() > v[1:34]=0 > predict(mylogit,newdata=as.data.frame(v),type="response") > > # And I get a matrix of 34 values that appear to fit a logistic function, > instead of 0.85.. > > > > > On Wed, Jan 26, 2011 at 6:59 PM, David Winsemius > <dwinsem...@comcast.net>wrote: > > > > > On Jan 26, 2011, at 10:52 PM, Ahnate Lim 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.. > >> > > > > Right. Predict goes in the other direction ... x predicts y. > > > > Perhaps if you created a function of y w.r.t. x and then inverted it. > > > > ?approxfun # and see the posting earlier this week "Inverse Prediction > > with splines" where it was demonstrated how to reverse the roles of x and y. > > > >> > >> predict(mylogit,newdata=as.data.frame(0.5)) > >> > >> [[alternative HTML version deleted]] > >> > >> ______________________________________________ > >> R-help@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. > >> > > > > David Winsemius, MD > > West Hartford, CT > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@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. -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% ______________________________________________ R-help@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.