. do "C:\Users\DEFAUL~1.SID\AppData\Local\Temp\STD00000000.tmp"

. * do-file for lecture 8 of VHM 802, Winter 2014
. version 13

. set more off

. cd "h:\vhm\vhm802\data_csv"
h:\vhm\vhm802\data_csv

.
. * Example 13.1
. insheet using ch13ta1.csv, clear
(4 vars, 15 obs)

. anova change tx plant

Number of obs = 15 R-squared = 0.8875
Root MSE = 4.21011 Adj R-squared = 0.8031

Source | Partial SS df MS F Prob > F

+

Model | 1118.43333 6 186.405556 10.52 0.0020
|
tx | 432.033333 2 216.016667 12.19 0.0037
plant | 686.4 4 171.6 9.68 0.0037
|
Residual | 141.8 8 17.725

+

Total | 1260.23333 14 90.0166667

. margins tx

Predictive margins Number of obs = 15

Expression : Linear prediction, predict()

+

--------

| Delta-method
| Margin Std. Err. t P>|t| [95% Con f. Interval]

+

--------

tx |
1 | 4.3 1.882817 2.28 0.052 -.0417839 8.641784
2 | 5.9 1.882817 3.13 0.014 1.558216 10.24178
3 | 16.4 1.882817 8.71 0.000 12.05822 20.74178

+

--------

. pwcompare tx, pv mcomp(bon)

Pairwise comparisons of marginal linear predictions

Margins : asbalanced

+

| Number of
| Comparisons

+

tx | 3

+

+

--------
| Bon ferroni
| Contrast Std. Err. t P>|t|

+

--------
tx |
2 vs 1 | 1.6 2.662705 0.60 1.000
3 vs 1 | 12.1 2.662705 4.54 0.006
3 vs 2 | 10.5 2.662705 3.94 0.013

+

--------

.
. * Mangold example
. insheet using mangold.csv, clear
(4 vars, 25 obs)

. encode tx, gen(Tx) /* needed because tx has character values */

. anova yield row col Tx

Number of obs = 25 R-squared = 0.7503
Root MSE = 12.091 Adj R-squared = 0.5007

Source | Partial SS df MS F Prob > F

+

Model | 5272.32 12 439.36 3.01 0.0341
|
row | 4240.24 4 1060.06 7.25 0.0033
col | 701.84 4 175.46 1.20 0.3604
Tx | 330.24 4 82.56 0.56 0.6930
|
Residual | 1754.32 12 146.193333

+

Total | 7026.64 24 292.776667

. margins Tx, asbalanced /* asbalanced actually not needed here */

Adjusted predictions Number of obs = 25

Expression : Linear prediction, predict()

at : row (asbalanced)

col (asbalanced)

Tx (asbalanced)

+

--------

| Delta-method
| Margin Std. Err. t P>|t| [95% Con f. Interval]

+

--------

Tx |
A | 333.6 5.407279 61.69 0.000 321.8186 345.3814
B | 331.2 5.407279 61.25 0.000 319.4186 342.9814
C | 334.4 5.407279 61.84 0.000 322.6186 346.1814
D | 342 5.407279 63.25 0.000 330.2186 353.7814
E | 334.4 5.407279 61.84 0.000 322.6186 346.1814

+

--------

. lincom 4*4.Tx-1.Tx-2.Tx-3.Tx-5.Tx

( 1) - 1b.Tx - 2.Tx - 3.Tx + 4*4.Tx - 5.Tx = 0

+

--------

yield | Coef. Std. Err. t P>|t| [95% Con f. Interval]

+

--------

(1) | 34.4 24.18209 1.42 0.180 -18.28824 87.08824

+

--------

. di 146.193333*(34.4/24.18209)^2 /* SS for contrast */
295.83993

.
. * Example 14.2
. insheet using ch14ta1.csv, clear
(4 vars, 36 obs)

. anova plates session tx

Number of obs = 36 R-squared = 0.9913
Root MSE = .907785 Adj R-squared = 0.9809

Source | Partial SS df MS F Prob > F

+

Model | 1499.56481 19 78.9244639 95.77 0.0000
|
session | 10.0648148 11 .914983165 1.11 0.4127
tx | 1086.81481 8 135.851852 164.85 0.0000
|
Residual | 13.1851852 16 .824074074

+

Total | 1512.75 35 43.2214286

. anova plates session tx, sequential

Number of obs = 36 R-squared = 0.9913
Root MSE = .907785 Adj R-squared = 0.9809

Source | Seq. SS df MS F Prob > F

+

Model | 1499.56481 19 78.9244639 95.77 0.0000
|
session | 412.75 11 37.5227273 45.53 0.0000
tx | 1086.81481 8 135.851852 164.85 0.0000
|
Residual | 13.1851852 16 .824074074

+

Total | 1512.75 35 43.2214286

. table tx, contents(mean plates) /* simple means */

+

tx | mean(plates)

+

1 | 19.75
2 | 16.75
3 | 13.25
4 | 6.5
5 | 25.5
6 | 23.25
7 | 20.75
8 | 19.25
9 | 29.75

+

. margins tx, asbalanced /* asbalanced not needed here either */

Adjusted predictions Number of obs = 36

Expression : Linear prediction, predict()

at : session (asbalanced)

tx (asbalanced)

+

--------

| Delta-method
| Margin Std. Err. t P>|t| [95% Con f. Interval]

+

--------

tx |
1 | 19.75 .5167795 38.22 0.000 18.65448 20.84552
2 | 17.19444 .5167795 33.27 0.000 16.09892 18.28997
3 | 13.19444 .5167795 25.53 0.000 12.09892 14.28997
4 | 6.527778 .5167795 12.63 0.000 5.432254 7.623301
5 | 25.30556 .5167795 48.97 0.000 24.21003 26.40108
6 | 22.97222 .5167795 44.45 0.000 21.8767 24.06775
7 | 21.08333 .5167795 40.80 0.000 19.98781 22.17886
8 | 19.19444 .5167795 37.14 0.000 18.09892 20.28997
9 | 29.52778 .5167795 57.14 0.000 28.43225 30.6233

+

--------

. margins, over(tx) /* simple means */

Predictive margins Number of obs = 36

Expression : Linear prediction, predict()

over : tx

+

--------

| Delta-method
| Margin Std. Err. t P>|t| [95% Con f. Interval]

+

--------

tx |
1 | 19.75 .4538926 43.51 0.000 18.78779 20.71221
2 | 16.75 .4538926 36.90 0.000 15.78779 17.71221
3 | 13.25 .4538926 29.19 0.000 12.28779 14.21221
4 | 6.5 .4538926 14.32 0.000 5.537791 7.462209
5 | 25.5 .4538926 56.18 0.000 24.53779 26.46221
6 | 23.25 .4538926 51.22 0.000 22.28779 24.21221
7 | 20.75 .4538926 45.72 0.000 19.78779 21.71221
8 | 19.25 .4538926 42.41 0.000 18.28779 20.21221
9 | 29.75 .4538926 65.54 0.000 28.78779 30.71221

+

--------

. margins, over(tx) asbalanced /* least squares means */

Adjusted predictions Number of obs = 36

Expression : Linear prediction, predict()

over : tx

at : 1.tx

session (asbalanced)

tx (asbalanced)

2.tx

session (asbalanced)

tx (asbalanced)

3.tx

session (asbalanced)

tx (asbalanced)

4.tx

session (asbalanced)

tx (asbalanced)

5.tx

session (asbalanced)

tx (asbalanced)

6.tx

session (asbalanced)

tx (asbalanced)

7.tx

session (asbalanced)

tx (asbalanced)

8.tx

session (asbalanced)

tx (asbalanced)

9.tx

session (asbalanced)

tx (asbalanced)

+

--------

| Delta-method
| Margin Std. Err. t P>|t| [95% Con f. Interval]

+

--------

tx |
1 | 19.75 .5167795 38.22 0.000 18.65448 20.84552
2 | 17.19444 .5167795 33.27 0.000 16.09892 18.28997
3 | 13.19444 .5167795 25.53 0.000 12.09892 14.28997
4 | 6.527778 .5167795 12.63 0.000 5.432254 7.623301
5 | 25.30556 .5167795 48.97 0.000 24.21003 26.40108
6 | 22.97222 .5167795 44.45 0.000 21.8767 24.06775
7 | 21.08333 .5167795 40.80 0.000 19.98781 22.17886
8 | 19.19444 .5167795 37.14 0.000 18.09892 20.28997
9 | 29.52778 .5167795 57.14 0.000 28.43225 30.6233

+

--------

. * same contrasts as in GO
. lincom 1.tx+2.tx+3.tx+4.tx+5.tx+6.tx+7.tx+8.tx-8*9.tx

( 1) 1b.tx + 2.tx + 3.tx + 4.tx + 5.tx + 6.tx + 7.tx + 8.tx - 8*9.tx = 0

+

--------

plates | Coef. Std. Err. t P>|t| [95% Con f. Interval]

+

--------

(1) | -91 4.447221 -20.46 0.000 -100.4277 -81.57231

+

--------

. lincom 1.tx+2.tx+3.tx+4.tx-5.tx-6.tx-7.tx-8.tx

( 1) 1b.tx + 2.tx + 3.tx + 4.tx - 5.tx - 6.tx - 7.tx - 8.tx = 0

+

--------

plates | Coef. Std. Err. t P>|t| [95% Con f. Interval]

+

--------

(1) | -31.88889 1.482407 -21.51 0.000 -35.03145 -28.74633

+

--------

. lincom -3*1.tx-2.tx+3.tx+3*4.tx-3*5.tx-6.tx+7.tx+3*8.tx

( 1) - 3*1b.tx - 2.tx + 3.tx + 3*4.tx - 3*5.tx - 6.tx + 7.tx + 3*8.tx = 0

+

--------

plates | Coef. Std. Err. t P>|t| [95% Con f. Interval]

+

--------

(1) | -63.88889 3.314763 -19.27 0.000 -70.91587 -56.86191

+

--------

.
. * reload Mangold data
. insheet using mangold.csv, clear
(4 vars, 25 obs)

. drop if col==5 /* subdataset for Youden square */
(5 observations deleted)

. encode tx, gen(Tx)

. anova yield row col Tx

Number of obs = 20 R-squared = 0.7964
Root MSE = 12.4332 Adj R-squared = 0.5165

Source | Partial SS df MS F Prob > F

+

Model | 4838.28333 11 439.843939 2.85 0.0742
|
row | 4220.13333 4 1055.03333 6.83 0.0108
col | 366.95 3 122.316667 0.79 0.5320
Tx | 224.133333 4 56.0333333 0.36 0.8289
|
Residual | 1236.66667 8 154.583333

+

Total | 6074.95 19 319.734211

. margins Tx, asbalanced /* asbalanced not needed here either */

Adjusted predictions Number of obs = 20

Expression : Linear prediction, predict()

at : row (asbalanced)

col (asbalanced)

Tx (asbalanced)

+

--------

| Delta-method
| Margin Std. Err. t P>|t| [95% Con f. Interval]

+

--------

Tx |
A | 340.35 6.380199 53.34 0.000 325.6372 355.0628
B | 333.55 6.380199 52.28 0.000 318.8372 348.2628
C | 334.75 6.380199 52.47 0.000 320.0372 349.4628
D | 341.8833 6.380199 53.59 0.000 327.1706 356.5961
E | 334.2167 6.380199 52.38 0.000 319.5039 348.9294

+

--------

.
end of do-file

. exit, clear