Reading in between the lines a little, maybe you want lm(..., na.action = na.exclude)
That should return missing values for the influence statistics when the predictor or responses is missing in the input. Hadley On Thu, Nov 20, 2008 at 4:19 PM, David Kaplan <[EMAIL PROTECTED]> wrote: > Let me try to be more specific. > > The x y coordinates are different because of NAs in the dataset. In this > analysis, a set of hat values (a measure of influence in regression) is > given for each observation. On the basis of the regression that was run to > get these hat values, the sample size was 1164 (one removed due to NA). The > length of the data set is 1165. If I remove the NA from the data set, I can > get identify to run. What I would like to know is if there is a way to get > identify to ignore the NAs? > > > > Thanks in advance, > > > -- > ======================================================================= > David Kaplan, Ph.D. > Professor > Department of Educational Psychology > University of Wisconsin - Madison > Educational Sciences, Room, 1061 > 1025 W. Johnson Street > Madison, WI 53706 > > email: [EMAIL PROTECTED] > homepage: > http://www.education.wisc.edu/edpsych/default.aspx?content=kaplan.html > Phone: 608-262-0836 > > ______________________________________________ > 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. > -- http://had.co.nz/ ______________________________________________ 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.