Don't most stat packages make adjustments to the degrees of freedom if the homogeneity of variance assumption is questionable? That'd be the biggest issue, and one that's easy to adjust for.
m > -----Original Message----- > From: Wuensch, Karl L [mailto:[EMAIL PROTECTED] > Sent: Tuesday, May 16, 2006 8:21 AM > To: Teaching in the Psychological Sciences (TIPS) > Subject: [tips] RE: stats help > > You will get more power if you keep all the valid data. As > Stuart notes, pay close attention to distributional and > variance assumptions when sample sizes are greatly different. > > Cheers, > > Karl W. > > -----Original Message----- > From: Stuart McKelvie [mailto:[EMAIL PROTECTED] > Sent: Monday, May 15, 2006 5:13 PM > To: Teaching in the Psychological Sciences (TIPS) > Subject: [tips] RE: stats help > > Dear Stephen, > > You can run this with unequal n. Look at variances to see how > much they violate the homogeneity assumption. Another idea: > Choose a random set of > 15 cases from the normal group. Check it their mean matches > the mean of the total normals. If so, then run an ANOVA with > 11, 15 and 17. > > Stuart > > --- > To make changes to your subscription go to: > http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mo > de=0&lang=english > > --- To make changes to your subscription go to: http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mode=0&lang=english
