Table 5.1, page 124. Salary Survey Data.
get file 'D:p124.sav'. list.
s x e m 13876 1 1 1 11608 1 3 0 18701 1 3 1 11283 1 2 0 11767 1 3 0 20872 2 2 1 11772 2 2 0 10535 2 1 0 12195 2 3 0 12313 3 2 0 14975 3 1 1 21371 3 2 1 19800 3 3 1 11417 4 1 0 20263 4 3 1 13231 4 3 0 12884 4 2 0 13245 5 2 0 13677 5 3 0 15965 5 1 1 12336 6 1 0 21352 6 3 1 13839 6 2 0 22884 6 2 1 16978 7 1 1 14803 8 2 0 17404 8 1 1 22184 8 3 1 13548 8 1 0 14467 10 1 0 15942 10 2 0 23174 10 3 1 23780 10 2 1 25410 11 2 1 14861 11 1 0 16882 12 2 0 24170 12 3 1 15990 13 1 0 26330 13 2 1 17949 14 2 0 25685 15 3 1 27837 16 2 1 18838 16 2 0 17483 16 1 0 19207 17 2 0 19346 20 1 0 Number of cases read: 46 Number of cases listed: 46
Table 5.3 and Figure 5.1, page 126-127.
compute E1 = (e = 1). compute E2 = (e = 2). exe. regression /dependent = s /method enter = x e1 e2 m /save sresid(r) /scatterplot (*sresid, x).
Figure 5.2, page 128. Standardized residuals versus education-management
categorical variable.
if (e = 1) & (m = 0) c = 1. if (e = 1) & (m = 1) c = 2. if (e = 2) & (m = 0) c = 3. if (e = 2) & (m = 1) c = 4. if (e = 3) & (m = 0) c = 5. if (e = 3) & (m = 1) c = 6. exe. graph /scatterplot = c with r.
Table 5.4 and Figure 5.3, page 129. Expanded Model and standardized residuals
versus years of experience.
compute me1 = m*e1. compute me2 = m*e2. exe. regression /dependent = s /method enter = x e1 e2 m me1 me2 /scatterplot (*sresid, x).
Table 5.5 and Figure 5.4, page 129-130. Expanded model (with obs. 33 deleted)
and standardized residuals versus years of experience.
compute id = $casenum. exe. compute filter = (id~=33). filter by filter. exe. regression /dependent = s /method enter = x e1 e2 m me1 me2 /scatterplot (*sresid, x) /save sresid(rs).
Figure 5.5, page 130. Standardized residuals versus education-management
category, (obs. 33 deleted).
graph /scatterplot = c with rs.
Table 5.6, page 131. Estimates of Base Salary Using the Nonadditive Model in
(5.2), (obs. 33 deleted).
glm s by e m with x /emmeans = tables(e*m) with(x = 0) /design x e m e*m.
Table 5.7, page 134. Data on Preemployment Testing Program.
get file 'D:p134.sav'. list.
test race jperf
.28 1 1.83
.97 1 4.59
1.25 1 2.97
2.46 1 8.14
2.51 1 8.00
1.17 1 3.30
1.78 1 7.53
1.21 1 2.03
1.63 1 5.00
1.98 1 8.04
2.36 0 3.25
2.11 0 5.30
.45 0 1.39
1.76 0 4.69
2.09 0 6.56
1.50 0 3.00
1.25 0 5.85
.72 0 1.90
.42 0 3.85
1.53 0 2.95
Number of cases read: 20 Number of cases listed: 20
Table 5.8 and Figure 5.7, page 135.
regression /dependent = jperf /method enter = test /save sresid(sr) /scatter (*sresid, test).
Table 5.9 and Figure 5.8, page 135.
compute rt = race*test. exe. regression /dependent = jperf /method enter = test race rt /scatter (*sresid, test).
Part of Table 5.10 and Figure 5.10, page 136-137.
Use the select if command to restrict the following analysis when race
=1. The temporary command allows the restriction to last for one procedure,
after which it returns to the unrestricted data set.
temporary. select if (race = 1). regression /dependent = jperf /method enter = test /scatter (*sresid, test).
Part of Table 5.10 and Figure 5.11, page 136-137.
temporary. select if (race = 0). regression /dependent = jperf /method enter = test /scatter (*sresid, test).
Figure 5.9, page 136.
graph /scatterplot = race with sr.
