Statistical Methods for Psychology

we need to look at the expected mean squares when we have a random variable that is

nested within a fixed variable. These expected mean squares are shown in Table 13.10,

where I have broken them down by fixed and random models, even though I am only dis-

cussing a nested design with one random factor here. I don’t usually include syntax for

SPSS and SAS, but nested designs cannot be run directly from menus in SPSS, so I am in-

cluding the syntax for the analysis of these data.

SPSS Code

UNIANOVA

dv BY Gender Therapist

/RANDOM 5 Therapist

/METHOD 5 SSTYPE(3)

/INTERCEPT 5 INCLUDE

/CRITERIA 5 ALPHA(.05)

/DESIGN 5 Gender Therapist(Gender).

SAS Code

data GenderTherapist;

infile C:\Documents and Settings\David Howell\

My Documents\Methods7\Chapters\Chapter13\GenderTherapist.dat ;

input Gender Therapist dv;

Proc GLM data 5 GenderTherapist;

Class Gender Therapist;

Model dv 5 Gender Therapist(Gender);

Random Therapist Therapist(Gender);

Test H 5 Gender E 5 Therapist(Gender);

run;

¿

¿

436 Chapter 13 Factorial Analysis of Variance

Table 13.9 Nested design with a random effect

SSerror=SStotal 2 SSG 2 SST(G)=2667.79 2 240.25 2 1705.24=722.30

SSTherapist(Gender)=SSTherapist(Male) 1 SSTherapist(Female)=351.52 1 1353.72=1705.24

=10(135.372)=1353.72

=10[(6.5 2 13.16)^21 (7.6 2 13.16)^21... 1 (19.3 2 13.16)^2 ]

SST(Female)=naAX.j 2 X..B^2

=10(35.152)=351.52

=10[(7.0 2 10.06)^21 (6.9 2 10.06)^21... 1 (12.0 2 10.06)^2 ]

SST(Male)=naAX.j 2 X..B^2

=240.25

= 53 4[(10.06 2 11.61)^21 (13.16 2 11.61)^2 ]

SSG=ncaAXi. 2 X..B^2

=550.775

=(9 2 11.61)^21 (8 2 11.61)^21... 1 (21 2 11.61)^2

SStotal= aAX 2 XB^2