My wife has been using a diagnostic from Manley (1991; "Randomization and MonteCarlo Methods in Biology") that compares a normal multiple regression's performance with that using random predicted variables. Is there something like this already available in R? If not, the "boot" package looks like a good place to start looking for methods, no? Thanks in advance Bruce L.
Manly's randomization analysis of multiple regression
2 messages · Nurnberg-LaZerte, Frank E Harrell Jr
On Wed, 14 May 2003 22:52:33 -0400
Nurnberg-LaZerte <mail at fwr.on.ca> wrote:
My wife has been using a diagnostic from Manley (1991; "Randomization and MonteCarlo Methods in Biology") that compares a normal multiple regression's performance with that using random predicted variables. Is there something like this already available in R? If not, the "boot" package looks like a good place to start looking for methods, no? Thanks in advance Bruce L.
This is related to that: Look at the validate function in the Design package (http://hesweb1.med.virginia.edu/biostat/s/Design.html) which has a "randomize" option to get the apparent and validated performance of models fitted by randomly permuting the vector of response variable values. This is not a high-precision way to estimate bias in your original R^2 etc. but rather is a teaching tool. For efficient estimation of future model performance use the validation bootstrap option (the default for validate( )). --- Frank E Harrell Jr Prof. of Biostatistics & Statistics Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat