Page 343, table 13.1 Regression of estimated 1980 U.S. census undercount of area characteristics, for 66 central cities, state remainders, and states.
NOTE: Stata lists the variables in descending order of their VIF, which is different from the order that they are listed in the text.
use https://stats.idre.ucla.edu/stat/stata/examples/ara/ericksen, clear
(From Fox, Applied Regression Analysis. Use 'notes' command for source of data)
regress undcount perc_min crimrate poverty diffeng hsgrad housing city countprc
Source | SS df MS Number of obs = 66
-------------+------------------------------ F( 8, 57) = 17.25
Model | 280.795421 8 35.0994276 Prob > F = 0.0000
Residual | 115.984804 57 2.03482113 R-squared = 0.7077
-------------+------------------------------ Adj R-squared = 0.6667
Total | 396.780225 65 6.10431116 Root MSE = 1.4265
------------------------------------------------------------------------------
undcount | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
perc_min | .0798341 .0226094 3.53 0.001 .0345595 .1251086
crimrate | .0301168 .0129978 2.32 0.024 .0040892 .0561444
poverty | -.178369 .0849158 -2.10 0.040 -.3484098 -.0083281
diffeng | .2151249 .0922088 2.33 0.023 .0304799 .3997699
hsgrad | .0612903 .0447749 1.37 0.176 -.0283698 .1509505
housing | -.0349569 .0246298 -1.42 0.161 -.0842771 .0143633
city | 1.159982 .7706438 1.51 0.138 -.3832056 2.703169
countprc | .0369889 .0092531 4.00 0.000 .0184598 .055518
_cons | -1.771393 1.382183 -1.28 0.205 -4.539166 .9963797
------------------------------------------------------------------------------
* Stata 8 code.
vif
* Stata 9 code and output.
estat vif
Variable | VIF 1/VIF
-------------+----------------------
perc_min | 5.01 0.199638
poverty | 4.63 0.216208
hsgrad | 4.62 0.216489
city | 3.54 0.282666
crimrate | 3.34 0.299080
housing | 1.87 0.534261
countprc | 1.69 0.591254
diffeng | 1.64 0.611409
-------------+----------------------
Mean VIF | 3.29
display sqrt(5.01)
2.2383029
di sqrt(4.63)
2.1517435
di sqrt(4.62)
2.1494185
di sqrt(3.54)
1.8814888
di sqrt(3.34)
1.8275667
di sqrt(1.87)
1.3674794
di sqrt(1.69)
1.3
di sqrt(1.64)
1.2806248
Page 343 Table 13.2 Correlations among eight predictors of the 1980 U.S. census undercount.
corr perc_min crimrate poverty diffeng hsgrad housing city countprc
(obs=66)
| perc_min crimrate poverty diffeng hsgrad housing city
-------------+---------------------------------------------------------------
perc_min | 1.0000
crimrate | 0.6549 1.0000
poverty | 0.7384 0.3691 1.0000
diffeng | 0.3954 0.5116 0.1516 1.0000
hsgrad | 0.5352 0.0666 0.7506 -0.1164 1.0000
housing | 0.3568 0.5317 0.3352 0.3402 0.2348 1.0000
city | 0.7577 0.7286 0.5375 0.4804 0.3148 0.5657 1.0000
countprc | -0.3344 -0.2331 -0.1570 -0.1082 -0.4142 -0.0863 -0.2688
| countprc
-------------+---------
countprc | 1.0000
Page 355, table 13.3 B. Fox’s Canadian women’s labor force participation data T is year; L is women’s labor force participation rate, in percent; F is the total fertility rate, per 1000; M is men’s average weekly wages in 1935 dollars; W is women’s average weekly wages; D is per-capita consumer debt; and P is the percentage of part-time workers.
use https://stats.idre.ucla.edu/stat/stata/examples/ara/bfox, clear
(From Fox, Applied Regression Analysis. Use 'notes' command for source of data)
list year womwork fertil mwage fwage debt parttime
Observation 1
year 1946 womwork 25.3 fertil 3748
mwage 25.35 fwage 14.05 debt 18.18
parttime 10.28
Observation 2
year 1947 womwork 24.4 fertil 3996
mwage 26.14 fwage 14.61 debt 28.33
parttime 9.28
Observation 3
year 1948 womwork 24.2 fertil 3725
mwage 25.11 fwage 14.23 debt 30.55
parttime 9.51
Observation 4
year 1949 womwork 24.2 fertil 3750
mwage 25.45 fwage 14.61 debt 35.81
parttime 8.87
Observation 5
year 1950 womwork 23.7 fertil 3669
mwage 26.79 fwage 15.26 debt 38.39
parttime 8.54
Observation 6
year 1951 womwork 24.2 fertil 3682
mwage 26.33 fwage 14.58 debt 26.52
parttime 8.84
Observation 7
year 1952 womwork 24.1 fertil 3845
mwage 27.89 fwage 15.66 debt 45.65
parttime 8.6
Observation 8
year 1953 womwork 23.8 fertil 3905
mwage 29.15 fwage 16.3 debt 52.99
parttime 5.49
Observation 9
year 1954 womwork 23.6 fertil 4047
mwage 29.52 fwage 16.57 debt 54.84
parttime 6.67
Observation 10
year 1955 womwork 24.3 fertil 4043
mwage 32.05 fwage 17.99 debt 65.53
parttime 6.25
Observation 11
year 1956 womwork 25.1 fertil 4092
mwage 32.98 fwage 18.33 debt 72.56
parttime 6.32
Observation 12
year 1957 womwork 26.2 fertil 4168
mwage 32.25 fwage 17.64 debt 69.49
parttime 7.3
Observation 13
year 1958 womwork 26.6 fertil 4073
mwage 32.52 fwage 18.16 debt 71.71
parttime 8.65
Observation 14
year 1959 womwork 26.9 fertil 4100
mwage 33.95 fwage 18.58 debt 78.89
parttime 8.8
Observation 15
year 1960 womwork 27.9 fertil 4119
mwage 34.63 fwage 18.95 debt 84.99
parttime 9.39
Observation 16
year 1961 womwork 29.1 fertil 4159
mwage 35.14 fwage 18.78 debt 87.71
parttime 10.23
Observation 17
year 1962 womwork 29.9 fertil 4134
mwage 34.49 fwage 18.74 debt 95.31
parttime 10.77
Observation 18
year 1963 womwork 29.8 fertil 4017
mwage 35.99 fwage 19.71 debt 104.4
parttime 10.84
Observation 19
year 1964 womwork 30.9 fertil 3886
mwage 36.68 fwage 20.06 debt 116.8
parttime 11.7
Observation 20
year 1965 womwork 32.1 fertil 3467
mwage 37.96 fwage 20.94 debt 130.99
parttime 12.33
Observation 21
year 1966 womwork 33.2 fertil 3150
mwage 38.68 fwage 21.2 debt 135.25
parttime 12.18
Observation 22
year 1967 womwork 34.5 fertil 2879
mwage 39.65 fwage 21.95 debt 142.93
parttime 13.67
Observation 23
year 1968 womwork 35.1 fertil 2681
mwage 41.2 fwage 22.68 debt 155.47
parttime 13.82
Observation 24
year 1969 womwork 36.1 fertil 2563
mwage 42.44 fwage 23.75 debt 165.04
parttime 14.91
Observation 25
year 1970 womwork 36.9 fertil 2571
mwage 42.02 fwage 25.63 debt 164.53
parttime 15.52
Observation 26
year 1971 womwork 37 fertil 2503
mwage 45.32 fwage 26.79 debt 169.63
parttime 15.47
Observation 27
year 1972 womwork 37.9 fertil 2302
mwage 45.61 fwage 27.51 debt 190.62
parttime 15.85
Observation 28
year 1973 womwork 40.1 fertil 2931
mwage 45.59 fwage 27.35 debt 209.6
parttime 15.4
Observation 29
year 1974 womwork 40.6 fertil 1875
mwage 48.06 fwage 29.64 debt 216.66
parttime 16.23
Observation 30
year 1975 womwork 42.2 fertil 1866
mwage 46.12 fwage 29.33 debt 224.34
parttime 16.71
Page 358, Figure 13.6 Plot of C(p)-p against p for the census undercount regression. Only subsets for which C(p)-p < 10 are shown. The following capitalized letter are employed to label the predictors in each subset: Minority, Crime, Poverty, Language, High school, hOusing, cIty, and coNventaional. Ericksen, et al. (1989) selected the predictor subset MCN (i.e., Minority, Crime and coNventaional).
NOTE: We were unable to reproduce this graph.
Page 359 Table 13.4 Best subset regression models for Ericksen et. al.’s census undercount data. Coefficient standard errors are in parentheses.
use https://stats.idre.ucla.edu/stat/stata/examples/ara/ericksen, clear (From Fox, Applied Regression Analysis. Use 'notes' command for source of data)
p = 4
regress undcount perc_min crimrate countprc
Source | SS df MS Number of obs = 66
-------------+------------------------------ F( 3, 62) = 36.35
Model | 252.966408 3 84.322136 Prob > F = 0.0000
Residual | 143.813817 62 2.3195777 R-squared = 0.6375
-------------+------------------------------ Adj R-squared = 0.6200
Total | 396.780225 65 6.10431116 Root MSE = 1.523
------------------------------------------------------------------------------
undcount | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
perc_min | .0786078 .01473 5.34 0.000 .0491629 .1080527
crimrate | .0363026 .0100445 3.61 0.001 .016224 .0563813
countprc | .0280009 .0080623 3.47 0.001 .0118846 .0441172
_cons | -2.22443 .5609767 -3.97 0.000 -3.345807 -1.103054
------------------------------------------------------------------------------
p = 5
regress undcount perc_min crimrate countprc diffeng
Source | SS df MS Number of obs = 66
-------------+------------------------------ F( 4, 61) = 30.84
Model | 265.503897 4 66.3759742 Prob > F = 0.0000
Residual | 131.276328 61 2.15207096 R-squared = 0.6691
-------------+------------------------------ Adj R-squared = 0.6475
Total | 396.780225 65 6.10431116 Root MSE = 1.467
------------------------------------------------------------------------------
undcount | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
perc_min | .0751885 .0142587 5.27 0.000 .0466764 .1037006
crimrate | .027154 .010391 2.61 0.011 .0063758 .0479321
countprc | .0272961 .0077712 3.51 0.001 .0117566 .0428356
diffeng | .2093535 .0867368 2.41 0.019 .0359126 .3827943
_cons | -1.975947 .5500616 -3.59 0.001 -3.075864 -.8760313
------------------------------------------------------------------------------
p = 6
regress undcount perc_min crimrate countprc diffeng poverty
Source | SS df MS Number of obs = 66
-------------+------------------------------ F( 5, 60) = 26.16
Model | 272.005773 5 54.4011547 Prob > F = 0.0000
Residual | 124.774452 60 2.0795742 R-squared = 0.6855
-------------+------------------------------ Adj R-squared = 0.6593
Total | 396.780225 65 6.10431116 Root MSE = 1.4421
------------------------------------------------------------------------------
undcount | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
perc_min | .1009673 .0202241 4.99 0.000 .0605131 .1414214
crimrate | .0243456 .0103372 2.36 0.022 .003668 .0450231
countprc | .029327 .0077251 3.80 0.000 .0138746 .0447795
diffeng | .1838497 .0864747 2.13 0.038 .0108747 .3568248
poverty | -.1100304 .0622272 -1.77 0.082 -.2345034 .0144426
_cons | -.7926886 .860341 -0.92 0.361 -2.513627 .9282497
------------------------------------------------------------------------------