Lecture 10 All Possible Regressions and Statistics for Comparing Models

Lecture 10 All Possible Regressions and Statistics for Comparing Models

Info iconThis preview shows pages 1–8. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: I OWA S TATE U NIVERSITY Department of Animal Science I OWA S TATE U NIVERSITY Department of Animal Science All Possible Regressions and Statistics for Comparing Models Animal Science 500 Lecture No. 12 October 12, 2010 I OWA S TATE U NIVERSITY Department of Animal Science Example analysis The RSQUARE Procedure RECALL The RSQUARE procedure selects optimal subsets of independent variables in a multiple regression analysis I OWA S TATE U NIVERSITY Department of Animal Science Example analysis PROC RSQUARE options; MODEL dependents = independents / options; (options can appear in either PROC RSQUARE or any MODEL statement). SELECT = n specific maximum number of subset models INCLUDE = I requests that the first I variables after the equal sign be included in every regression SIGMA = n specifies the true standard deviation of I OWA S TATE U NIVERSITY Department of Animal Science Example analysis PROC RSQUARE options; MODEL dependents = independents / options; (options can appear in either PROC RSQUARE or any MODEL statement). PROC RSQUARE DATA=name OUTEST=EST ADJRSQ MSE CP; SELECT=n; MODEL = variable list; I OWA S TATE U NIVERSITY Department of Animal Science Example analysis PROC PRINT DATA=EST; PROC PLOT; PLOT _CP_*_P_ = C _P_*_P_ = P / OVERLAY; PLOT _MSE_*_P_ = M; Run; Quit I OWA S TATE U NIVERSITY Department of Animal Science PROC STEPWISE The STEPWISE procedure provides five methods for stepwise regression. General form: PROC STEPWISE; MODEL dependents = independents / options; Run; Quit; ** Assumes that you have at least one dependent variable and 2 or more independent variables. If only one independent variable exists then you are just doing a simple regression of x on y or y on x. I OWA S TATE U NIVERSITY Department of Animal Science Types of Regression Uses of PROC REG for standard problems:...
View Full Document

Page1 / 16

Lecture 10 All Possible Regressions and Statistics for Comparing Models

This preview shows document pages 1 - 8. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online