-----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]]On Behalf Of wuzzy Sent: Saturday, March 30, 2002 9:47 AM To: [EMAIL PROTECTED] Subject: prediction: underspecifiation in observational studies Maybe someone will point me to other newsgroups or mail groups on biological or clinical statistics as I know that sci.stat.edu is about the education of statistics not really about stats itself.. My question (frustration, rather) is: how do you deal with the fact that signs on coefficients of multivariable models change direction and size when you remove a predictor of the dependant variable(s). is there a test for this? ----------------------------------------------------------------- Multivariate regression handles only one error effect, and that is assigned to the right hand side of the equation. This is really two errors combined (assuming each of the X variables are precise, error free measurements), one for the error in the Y measurement, and two for the fact that left-out variables affect Y, but not being measured, are included. If I leave out one variable, all the other variables have to "pick up the load", and appropriately, the coefficient values change. One way is to regress each variable, one at a time, starting with the variable that has the greatest effect (R squared). Regress now on the residuals from the first regression using the next variable. Each measure is orthogonal. Continue for all variables and the effect of each variable can be determined from the R values, the value of the coefficient, and the standard error of the coefficient. One possible test is Fisher's R squared tests, in which his transformation gives approximate z values. The sequence of the corresponding cumulative P values provides a measure. DAHeiser . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
