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use http://www.ats.ucla.edu/stat/stata/examples/kirk/cr4
Table 5.2-1, page 167. The variable order was added to the file to preserve the original ordering of the data.
tabdisp order a, cellvar(y)
----------+-----------------------
| a
order | 1 2 3 4
----------+-----------------------
1 | 4 4 5 3
2 | 6 5 6 5
3 | 3 4 5 6
4 | 3 3 4 5
5 | 1 2 3 6
6 | 3 3 4 7
7 | 2 4 3 8
8 | 2 3 4 10
----------+-----------------------
dotplot y, by(a) ylabel(1(1)10)
table a, contents(freq mean y sd y)
----------+-----------------------------------
a | Freq. mean(y) sd(y)
----------+-----------------------------------
1 | 8 3 1.511858
2 | 8 3.5 .9258201
3 | 8 4.25 1.035098
4 | 8 6.25 2.12132
----------+-----------------------------------
Figure 5.2-1(a), page 168.
egen mean = mean(y), by(a) generate e = y - mean dotplot e, by(a) ylabel(-3(1)4)
Table 5.3-2, page 172.
anova y a
Number of obs = 32 R-squared = 0.4455
Root MSE = 1.476 Adj R-squared = 0.3860
Source | Partial SS df MS F Prob > F
-----------+----------------------------------------------------
Model | 49.00 3 16.3333333 7.50 0.0008
|
a | 49.00 3 16.3333333 7.50 0.0008
|
Residual | 61.00 28 2.17857143
-----------+----------------------------------------------------
Total | 110.00 31 3.5483871
Three contrasts, page 173.
Note 1: The contrast 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).
Note 2: The contrast command reports results as F-ratios, not t-tests. In this case, F is just t2.
contrast a, value(1 -1 0 0) title(contrast 1) contrast 1 Contrast variable a (1 -1 0 0) source SS df MS Dep Var = y ---------+--------------------------------- N of obs = 32 contrast | 1 1 1.0000 F = 0.46 error | 61 28 2.1786 Prob > F = 0.5036 ---------+--------------------------------- contrast a, value(0 0 1 -1) title(contrast 2) contrast 2 Contrast variable a (0 0 1 -1) source SS df MS Dep Var = y ---------+--------------------------------- N of obs = 32 contrast | 16 1 16.0000 F = 7.34 error | 61 28 2.1786 Prob > F = 0.0114 ---------+--------------------------------- contrast a, value(1 1 -1 -1) title(contrast 3) contrast 3 Contrast variable a (1 1 -1 -1) source SS df MS Dep Var = y ---------+--------------------------------- N of obs = 32 contrast | 32 1 32.0000 F = 14.69 error | 61 28 2.1786 Prob > F = 0.0007 ---------+---------------------------------
Table 5.4-1, page 174.
Note: The fhcomp command can be downloaded by typing findit fhcomp (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, 3, 28) = 3.4994064
mean critical
grp vs grp group means dif dif
-------------------------------------------------------
1 vs 2 3.0000 3.5000 0.5000 1.8261
1 vs 3 3.0000 4.2500 1.2500 1.8261
1 vs 4 3.0000 6.2500 3.2500* 1.8261
2 vs 3 3.5000 4.2500 0.7500 1.8261
2 vs 4 3.5000 6.2500 2.7500* 1.8261
3 vs 4 4.2500 6.2500 2.0000* 1.8261
Omega-squared on page 178 and effect size on page 181.
Note: The omega2 command can be downloaded by typing findit omega2 (see How can I use the findit command to search for programs and get additional help? for more information about using findit).
omega2 omega squared = 0.3785 effect size = 0.7805
Parts of Table 5.7-4, page 196.
contrast a, value(-3 -1 1 3) title(linear trend) linear trend Contrast variable a (-3 -1 1 3) source SS df MS Dep Var = y ---------+--------------------------------- N of obs = 32 contrast | 44.1 1 44.1000 F = 20.24 error | 61 28 2.1786 Prob > F = 0.0001 ---------+--------------------------------- contrast a, value(1 -1 -1 1) title(quadratic trend) quadratic trend Contrast variable a (1 -1 -1 1) source SS df MS Dep Var = y ---------+--------------------------------- N of obs = 32 contrast | 4.5 1 4.5000 F = 2.07 error | 61 28 2.1786 Prob > F = 0.1617 ---------+--------------------------------- contrast a, value(-1 3 -3 1) title(cubic trend) cubic trend Contrast variable a (-1 3 -3 1) source SS df MS Dep Var = y ---------+--------------------------------- N of obs = 32 contrast | .4 1 0.4000 F = 0.18 error | 61 28 2.1786 Prob > F = 0.6716 ---------+---------------------------------
Figure 5.7-3, page 199.
predict p1 /* compute observed means */ graph twoway (scatter p1 a, connect(l)) (lfit p1 a), ylabel(2(1)7)
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