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Table 8.3-1, page 325.
use http://www.ats.ucla.edu/stat/stata/examples/kirk/ls4, clear
tabdisp s c, cellvar(y) by(b) /* levels of a not shown */
----------+-----------------------
| c
b and s | 1 2 3 4
----------+-----------------------
1 |
1 | 1 2 5 9
2 | 2 3 6 8
----------+-----------------------
2 |
1 | 3 8 9 2
2 | 4 6 8 3
----------+-----------------------
3 |
1 | 5 10 3 5
2 | 7 11 2 4
----------+-----------------------
4 |
1 | 7 6 3 6
2 | 10 3 4 7
----------+-----------------------
table b c, cont(sum y) row col /* levels of a not shown */
----------+----------------------------------
| c
b | 1 2 3 4 Total
----------+----------------------------------
1 | 3 5 11 17 36
2 | 7 14 17 5 43
3 | 12 21 5 9 47
4 | 17 9 7 13 46
|
Total | 39 49 40 44 172
----------+----------------------------------
table a, cont(sum y)
----------+-----------
a | sum(y)
----------+-----------
1 | 22
2 | 28
3 | 50
4 | 72
----------+-----------
Table 8.3-2, page 327.
Note: The term that Kirk calls residual is called a*b*c in this Stata model.
anova y a b c a*b*c
Number of obs = 32 R-squared = 0.9193
Root MSE = 1.08972 Adj R-squared = 0.8437
Source | Partial SS df MS F Prob > F
-----------+----------------------------------------------------
Model | 216.50 15 14.4333333 12.15 0.0000
|
a | 194.50 3 64.8333333 54.60 0.0000
b | 9.25 3 3.08333333 2.60 0.0884
c | 7.75 3 2.58333333 2.18 0.1308
a*b*c | 5.00 6 .833333333 0.70 0.6525
|
Residual | 19.00 16 1.1875
-----------+----------------------------------------------------
Total | 235.50 31 7.59677419
Omega-squared computation, page 329.
Note: The omega2 command can be downloaded by typing findit contrast (see How can I use the findit command to search for programs and get additional help? for more information about using findit).
omega2 54.6 3 omega squared = 0.8340 effect size = 2.2417
Table 8.4-1, page 331.
use http://www.ats.ucla.edu/stat/stata/examples/kirk/ls4a, clear
tabdisp b c, cellvar(y)
----------+-----------------------
| c
b | 1 2 3 4
----------+-----------------------
1 | 3 5 11 17
2 | 7 14 17 5
3 | 12 21 5 9
4 | 17 9 7 13
----------+-----------------------
Table 8.4-1, page 332.
nonadd y a b c Tukey's test of nonadditivity for randomized block designs F (1,5) = .0001702 Pr > F: .99009558
Figure 8.4-1, page 333.
anova y a b c, noanova predict yhat /* yhat is the fitted value */ predict e, rstandard /* e is the standardized residual */ graph twoway scatter e yhat, ylabel(-2(.5)2) xlabel(0(2)20)
Table 8.11-1, page 353.
use http://www.ats.ucla.edu/stat/stata/examples/kirk/ls4a, clear
tabdisp s b, cellvar(y) /* levels of a not shown */
----------+-----------------
| b
s | 1 2 3
----------+-----------------
1 | 7 14 12
2 | 3 5 11
3 | 6 7 11
4 | 12 13 9
5 | 7 9 8
6 | 8 13 9
----------+-----------------
Table 8.11-2, page 355.
anova y a b s
Number of obs = 18 R-squared = 0.9021
Root MSE = 1.38944 Adj R-squared = 0.7920
Source | Partial SS df MS F Prob > F
-----------+----------------------------------------------------
Model | 142.333333 9 15.8148148 8.19 0.0035
|
a | 49.7777778 2 24.8888889 12.89 0.0031
b | 34.1111111 2 17.0555556 8.83 0.0094
s | 58.4444444 5 11.6888889 6.05 0.0131
|
Residual | 15.4444444 8 1.93055556
-----------+----------------------------------------------------
Total | 157.777778 17 9.28104575
Omega-squared computation, page 354.
omega2 12.89 2 omega squared = 0.5692 effect size = 1.1494
Table 8.11-3, page 355.
Note: The fhcomp command can be downloaded by typing findit contrast (see How can I use the findit command to search for programs and get additional help? for more information about using findit).
fhcomp a
Fisher-Hayter pairwise comparisons for variable a
studentized range critical value(.05, 2, 8) = 3.2611823
mean critical
grp vs grp group means dif dif
-------------------------------------------------------
1 vs 2 7.3333 11.3333 4.0000* 1.8499
1 vs 3 7.3333 8.6667 1.3333 1.8499
2 vs 3 11.3333 8.6667 2.6667* 1.8499
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