Table 11.1, page 295.
use https://stats.idre.ucla.edu/stat/stata/examples/chp/p189, clear
corr x1-x6
(obs=30)
| x1 x2 x3 x4 x5 x6
---------+------------------------------------------------------
x1 | 1.0000
x2 | 0.5583 1.0000
x3 | 0.5967 0.4933 1.0000
x4 | 0.6692 0.4455 0.6403 1.0000
x5 | 0.1877 0.1472 0.1160 0.3769 1.0000
x6 | 0.2246 0.3433 0.5316 0.5742 0.2833 1.0000
VIFs and eigenvalues, page 295.
Note: The collin.ado program written by ATS can be installed on your computer over the Internet by typing search collin (see How can I use the search command to search for programs and get additional help? for more information about using search).
collin x1 x2 x3 x4 x5 x6
Collinearity Diagnostics
SQRT Cond
Variable VIF VIF Tolerance Eigenval Index
-------------------------------------------------------------
x1- 2.67 1.63 0.3749 3.1692 1.0000
x6 1.60 1.27 0.6247 1.0063 1.7746
2.27 1.51 0.4403 0.7629 2.0382
3.08 1.75 0.3249 0.5525 2.3950
1.23 1.11 0.8143 0.3172 3.1607
1.95 1.40 0.5124 0.1918 4.0654
-------------------------------------------------------------
Mean VIF 2.13 Condition Number 4.0654
Part of Table 11.2, page 296.
Note: The probability to enter option, pe, was set to .99 so that all of the variables would enter and their order of entry observed.
* Stata 8 code.
sw regress y x1 x2 x3 x4 x5 x6, pe(.99)
* Stata 9 code and output.
stepwise, pe(.99): regress y x1 x2 x3 x4 x5 x6
begin with empty model
p = 0.0000 ^lt; 0.9900 adding x1
p = 0.1278 ^lt; 0.9900 adding x3
p = 0.2082 ^lt; 0.9900 adding x6
p = 0.5616 ^lt; 0.9900 adding x2
p = 0.6426 ^lt; 0.9900 adding x4
p = 0.7963 ^lt; 0.9900 adding x5
Source | SS df MS Number of obs = 30
---------+------------------------------ F( 6, 23) = 10.50
Model | 3147.96634 6 524.661057 Prob > F = 0.0000
Residual | 1149.00032 23 49.9565359 R-squared = 0.7326
---------+------------------------------ Adj R-squared = 0.6628
Total | 4296.96667 29 148.171264 Root MSE = 7.068
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x1 | .6131876 .1609831 3.809 0.001 .2801687 .9462065
x3 | .3203321 .1685203 1.901 0.070 -.0282787 .6689429
x6 | -.2170567 .1782095 -1.218 0.236 -.585711 .1515977
x2 | -.0730501 .1357247 -0.538 0.596 -.353818 .2077178
x4 | .0817321 .2214777 0.369 0.715 -.3764293 .5398936
x5 | .0383814 .1469954 0.261 0.796 -.2657018 .3424647
_cons | 10.78708 11.58926 0.931 0.362 -13.18713 34.76128
------------------------------------------------------------------------------
Part of table 11.3, page 297.
Note: The probability to remove option, pr, was set to .01 so that all of the variables except the last one would be removed and their order of removal observed.
* Stata 8 code.
sw regress y x1 x2 x3 x4 x5 x6, pr(.01)
* Stata 9 code and output.
stepwise, pr(.01): regress y x1 x2 x3 x4 x5 x6
begin with full model
p = 0.7963 >= 0.0100 removing x5
p = 0.6426 >= 0.0100 removing x4
p = 0.5616 >= 0.0100 removing x2
p = 0.2082 >= 0.0100 removing x6
p = 0.1278 >= 0.0100 removing x3
Source | SS df MS Number of obs = 30
---------+------------------------------ F( 1, 28) = 59.86
Model | 2927.58425 1 2927.58425 Prob > F = 0.0000
Residual | 1369.38241 28 48.9065148 R-squared = 0.6813
---------+------------------------------ Adj R-squared = 0.6699
Total | 4296.96667 29 148.171264 Root MSE = 6.9933
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x1 | .7546098 .0975329 7.737 0.000 .5548227 .9543969
_cons | 14.37632 6.619986 2.172 0.039 .8158929 27.93675
------------------------------------------------------------------------------
Regression equation, page 296.
Note: The probability to remove option, pr, was set to .33 to correspond to a t-value of 1.0.
* Stata 8 code.
sw regress y x1 x2 x3 x4 x5 x6, pr(.33)
* Stata 9 code and output.
stepwise, pr(.33): regress y x1 x2 x3 x4 x5 x6
begin with full model
p = 0.7963 >= 0.3300 removing x5
p = 0.6426 >= 0.3300 removing x4
p = 0.5616 >= 0.3300 removing x2
Source | SS df MS Number of obs = 30
---------+------------------------------ F( 3, 26) = 22.92
Model | 3117.85753 3 1039.28584 Prob > F = 0.0000
Residual | 1179.10914 26 45.3503515 R-squared = 0.7256
---------+------------------------------ Adj R-squared = 0.6939
Total | 4296.96667 29 148.171264 Root MSE = 6.7343
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x1 | .6227297 .1181464 5.271 0.000 .3798763 .8655832
x6 | -.1869508 .1448537 -1.291 0.208 -.4847019 .1108003
x3 | .312387 .1541997 2.026 0.053 -.0045751 .6293491
_cons | 13.57774 7.5439 1.800 0.084 -1.928967 29.08445
------------------------------------------------------------------------------
Tables 11.7 and 11.8, page 301.
use https://stats.idre.ucla.edu/stat/stata/examples/chp/p301, clear
list year ftp unemp m lic
year ftp unemp m lic
1. 1961 260.35 11 455.5 178.15
2. 1962 269.8 7 480.2 156.41
3. 1963 272.04 5.2 506.1 198.02
4. 1964 272.96 4.3 535.8 222.1
5. 1965 272.51 3.5 576 301.92
6. 1966 261.34 3.2 601.7 391.22
7. 1967 268.89 4.1 577.3 665.56
8. 1968 295.99 3.9 596.9 1131.21
9. 1969 319.87 3.6 613.5 837.8
10. 1970 341.43 7.1 569.3 794.9
11. 1971 356.59 8.4 548.8 817.74
12. 1972 376.69 7.7 563.4 583.17
13. 1973 390.19 6.3 609.3 709.59
list year gr clear w nman
year gr clear w nman
1. 1961 215.98 93.4 558724 538.1
2. 1962 180.48 88.5 538584 547.6
3. 1963 209.57 94.4 519171 562.8
4. 1964 231.67 92 500457 591
5. 1965 297.65 91 482418 626.1
6. 1966 367.62 87.4 465029 659.8
7. 1967 616.54 88.3 448267 686.2
8. 1968 1029.75 86.1 432109 699.6
9. 1969 786.23 79 416533 729.9
10. 1970 713.77 73.9 401518 757.8
11. 1971 750.43 63.4 398046 755.3
12. 1972 1027.38 62.5 373095 787
13. 1973 666.5 58.9 359647 819.8
list year g he we h
year g he we h
1. 1961 133.9 2.98 117.18 8.6
2. 1962 137.6 3.09 134.02 8.9
3. 1963 143.6 3.23 141.68 8.52
4. 1964 150.3 3.33 147.98 8.89
5. 1965 164.3 3.46 159.85 13.07
6. 1966 179.5 3.6 157.19 14.57
7. 1967 187.5 3.73 155.29 21.36
8. 1968 195.4 2.91 131.75 28.03
9. 1969 210.3 4.25 178.74 31.49
10. 1970 223.8 4.47 178.3 37.39
11. 1971 227.7 5.04 209.54 46.26
12. 1972 230.9 5.47 240.05 47.24
13. 1973 230.2 5.76 258.05 52.33
Table 11.9, page 301.
regress h g m w, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 3, 9) = 115.03
Model | 3139.9039 3 1046.63463 Prob > F = 0.0000
Residual | 81.8858502 9 9.09842781 R-squared = 0.9746
---------+------------------------------ Adj R-squared = 0.9661
Total | 3221.78975 12 268.482479 Root MSE = 3.0164
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
g | .1041508 .1527901 0.682 0.513 .2354133
m | -.1330913 .0297607 -4.472 0.002 -.4046823
w | -.0002635 .0000972 -2.711 0.024 -1.024555
_cons | 199.3063 81.57561 2.443 0.037 .
------------------------------------------------------------------------------
Table 11.1, page 302.
regress h g, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 1, 11) = 122.93
Model | 2957.17935 1 2957.17935 Prob > F = 0.0000
Residual | 264.610399 11 24.0554908 R-squared = 0.9179
---------+------------------------------ Adj R-squared = 0.9104
Total | 3221.78975 12 268.482479 Root MSE = 4.9046
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
g | .4238596 .0382288 11.087 0.000 .9580545
_cons | -53.61314 7.230834 -7.415 0.000 .
------------------------------------------------------------------------------
regress h m, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 1, 11) = 4.68
Model | 961.954657 1 961.954657 Prob > F = 0.0533
Residual | 2259.83509 11 205.439554 R-squared = 0.2986
---------+------------------------------ Adj R-squared = 0.2348
Total | 3221.78975 12 268.482479 Root MSE = 14.333
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
m | .1797066 .0830479 2.164 0.053 .5464227
_cons | -74.87015 46.38238 -1.614 0.135 .
------------------------------------------------------------------------------
regress h w, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 1, 11) = 95.44
Model | 2888.84975 1 2888.84975 Prob > F = 0.0000
Residual | 332.939995 11 30.2672723 R-squared = 0.8967
---------+------------------------------ Adj R-squared = 0.8873
Total | 3221.78975 12 268.482479 Root MSE = 5.5016
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
w | -.0002436 .0000249 -9.770 0.000 -.9469213
_cons | 135.5437 11.40463 11.885 0.000 .
------------------------------------------------------------------------------
regress h g m, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 2, 10) = 103.29
Model | 3073.02599 2 1536.51299 Prob > F = 0.0000
Residual | 148.763759 10 14.8763759 R-squared = 0.9538
---------+------------------------------ Adj R-squared = 0.9446
Total | 3221.78975 12 268.482479 Root MSE = 3.857
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
g | .5083883 .0426769 11.912 0.000 1.149116
m | -.0885298 .0317246 -2.791 0.019 -.269187
_cons | -20.05391 13.30252 -1.508 0.163 .
------------------------------------------------------------------------------
regress h g w, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 2, 10) = 56.05
Model | 2957.94195 2 1478.97098 Prob > F = 0.0000
Residual | 263.847795 10 26.3847795 R-squared = 0.9181
---------+------------------------------ Adj R-squared = 0.9017
Total | 3221.78975 12 268.482479 Root MSE = 5.1366
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
g | .3840859 .2373508 1.618 0.137 .8681538
w | -.0000235 .000138 -0.170 0.868 -.0912077
_cons | -35.58906 106.2883 -0.335 0.745 .
------------------------------------------------------------------------------
regress h m w, beta
Source | SS df MS Number of obs = 13
---------+------------------------------ F( 2, 10) = 182.07
Model | 3135.67622 2 1567.83811 Prob > F = 0.0000
Residual | 86.1135256 10 8.61135256 R-squared = 0.9733
---------+------------------------------ Adj R-squared = 0.9679
Total | 3221.78975 12 268.482479 Root MSE = 2.9345
------------------------------------------------------------------------------
h | Coef. Std. Err. t P>|t| Beta
---------+--------------------------------------------------------------------
m | -.1414025 .0264117 -5.354 0.000 -.4299537
w | -.0003282 .0000207 -15.888 0.000 -1.275933
_cons | 252.5913 22.69316 11.131 0.000 .
------------------------------------------------------------------------------