Table 5.1 on page 78, Table 5.2 on page 79 and Figure 5.3 using data file gpa.sav. These tables are produced using SPSS.
GLM gpa1 gpa2 gpa3 gpa4 gpa5 gpa6 BY sex WITH highgpa /WSFACTOR = gpa 6 Polynomial /METHOD = SSTYPE(3) /PLOT = PROFILE( gpa*sex ) /PRINT = DESCRIPTIVE /CRITERIA = ALPHA(.05) /WSDESIGN = gpa /DESIGN = highgpa sex .
Table 5.2:
Figure 5.3 on page 80.
GET FILE='E:hoxspssgpaflat.sav'.
GRAPH /HISTOGRAM(NORMAL)=gpa .
Table 5.3 on page 81 using data file gpa4chp5.ws. Notice that the results for Part 3 and Part 4 are a little off from the book.
Part 1: Null model.
The result is:
Part 2: With additional variable time which is created as follow.
->CALCulate "time"="occas"-1
The result is:
Part 3: Variable job is added.
The result is:
Part 4: Variable highgpa and sex are added to the model.
The result is:
Table 5.4 on page 83.
Part 1: Variable time is included as a random effect.
Then result is:
Part 2: Cross level interaction of variable time and sex is included. We first created the interaction term.
->CALCulate "tmxsex"="time"*"sex"
The result is:
Figure 5.4. on page 84.
Table 5.5 on page 85.
Part 1: 1st occasion = 0, same as the first part of Table 5.4. We only show the result here.
Part 2: Variable time has been recoded as -5, …,-1, 0, …with the last occasion coded as zero. We first recode variable time into time1.
->CALCulate "time1"="time"-5
The result is:
Part 3: Variable time is recoded centered around its mean and is included as a fixed effect.
->CALCulate "timec"="time"-2.5
The result is:
Table 5.6 using data file vocagrwt.ws.
The result is:
->TABUlate 0 "age"
12 13 14 15 16
N 22 0 5 0 22
17 18 19 20 21
N 0 11 0 22 0
22 23 24 25 26 TOTALS
N 11 0 22 0 11 126
Table 5.7 on page 89.
Part 1: Intercept only model.
The result is:
Part 2: Variable age is grand mean centered and is included as a fixed effect.
->AVERage 1 "age"
N Missing Mean s.d. age 126 0 18.889 4.5786
->CALCulate "agec"="age"-18.889
The result is:
Part 3: The squared term of agec is included as a fixed effect.
->CALCulate "agec2"="agec"*"agec"
The result is:
Part 4: Centered variable agec is included as a random effect. We noticed that it took many more iterations for this model to converge.
The result is:
Table 5.8 on page 91.
Part 1: Intercept only model.
The result is:
Part 2: Variable age is centered on 12 months and is included as a fixed effect.
The result is:
Part 3: age12sq is included as a fixed effect.