Would it be proper for me to reduce a model by iterating though the coefficients and dropping the ones with high p-values and then refitting and doing this again until all coefficients are significant? The algorithm I have in mind is (starting with the full model):
- fit regression on current set of regressors
- find coefficient with highest p-value
- drop regressor variable from model
- go to step 1
I select the "highest p-value" because the null hypothesis in my software package (python statsmodels) is that the coefficient is 0 so we only keep ones with low p-values. I can potentially then perform a stepAIC after running the above step. For example, here is a model I ran just now which I'd like to reduce.
OLS Regression Results
==============================================================================
Dep. Variable: c0000 R-squared: 0.183
Model: OLS Adj. R-squared: 0.105
Method: Least Squares F-statistic: 2.337
Date: Fri, 14 May 2021 Prob (F-statistic): 3.53e-28
Time: 13:14:07 Log-Likelihood: 23470.
No. Observations: 3285 AIC: -4.636e+04
Df Residuals: 2997 BIC: -4.461e+04
Df Model: 287
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
Intercept -1.323e-05 3.86e-06 -3.428 0.001 -2.08e-05 -5.66e-06
c1620 -0.0211 0.014 -1.541 0.123 -0.048 0.006
c1655 0.0021 0.015 0.137 0.891 -0.027 0.032
c0705 0.0300 0.010 2.890 0.004 0.010 0.050
c1210 0.0095 0.014 0.671 0.503 -0.018 0.037
c1900 -0.0082 0.013 -0.634 0.526 -0.034 0.017
c0905 0.0034 0.012 0.280 0.780 -0.021 0.027
c0650 0.0064 0.015 0.424 0.672 -0.023 0.036
c1130 0.0368 0.015 2.400 0.016 0.007 0.067
c1015 0.0477 0.014 3.426 0.001 0.020 0.075
c0300 0.0313 0.023 1.346 0.178 -0.014 0.077
c1535 0.0084 0.013 0.671 0.502 -0.016 0.033
c1650 0.0301 0.016 1.862 0.063 -0.002 0.062
c0235 -0.0446 0.024 -1.848 0.065 -0.092 0.003
c0545 0.0030 0.025 0.120 0.904 -0.046 0.052
c1515 0.0264 0.011 2.331 0.020 0.004 0.049
c2240 -0.0799 0.029 -2.763 0.006 -0.137 -0.023
c1255 -0.0166 0.010 -1.612 0.107 -0.037 0.004
c1820 0.0142 0.017 0.843 0.399 -0.019 0.047
c1215 0.0297 0.012 2.573 0.010 0.007 0.052
c2340 -0.0208 0.017 -1.200 0.230 -0.055 0.013
c2155 -0.0734 0.029 -2.491 0.013 -0.131 -0.016
c2145 0.0401 0.033 1.224 0.221 -0.024 0.104
c0920 0.0165 0.014 1.165 0.244 -0.011 0.044
c0215 0.0178 0.024 0.749 0.454 -0.029 0.064
c1855 -0.0314 0.018 -1.736 0.083 -0.067 0.004
c0535 0.0373 0.025 1.502 0.133 -0.011 0.086
c1310 0.0127 0.011 1.160 0.246 -0.009 0.034
c1420 -0.0342 0.010 -3.307 0.001 -0.054 -0.014
c1705 -0.0188 0.014 -1.318 0.188 -0.047 0.009
c1005 -0.0167 0.014 -1.212 0.225 -0.044 0.010
c0810 0.0198 0.011 1.760 0.079 -0.002 0.042
c0620 0.0100 0.018 0.568 0.570 -0.024 0.044
c0255 -0.0397 0.025 -1.617 0.106 -0.088 0.008
c2320 0.0530 0.027 1.959 0.050 -4.49e-05 0.106
c2200 -0.0014 0.009 -0.159 0.874 -0.019 0.016
c0520 0.0447 0.026 1.696 0.090 -0.007 0.096
c0835 0.0020 0.012 0.170 0.865 -0.021 0.025
c0155 -0.0242 0.023 -1.055 0.292 -0.069 0.021
c1000 0.0033 0.012 0.270 0.787 -0.021 0.027
c2040 -0.0329 0.026 -1.270 0.204 -0.084 0.018
c0530 -0.0024 0.026 -0.094 0.925 -0.053 0.049
c0250 -0.0072 0.024 -0.296 0.767 -0.054 0.040
c1240 -0.0170 0.008 -2.055 0.040 -0.033 -0.001
c1430 -0.0120 0.011 -1.102 0.270 -0.033 0.009
c0610 0.0213 0.015 1.373 0.170 -0.009 0.052
c1050 0.0436 0.016 2.762 0.006 0.013 0.075
c1320 -0.0146 0.012 -1.255 0.210 -0.037 0.008
c1710 -0.0257 0.016 -1.600 0.110 -0.057 0.006
c0855 0.0050 0.014 0.354 0.723 -0.023 0.033
c0130 -0.0459 0.022 -2.123 0.034 -0.088 -0.004
c0350 0.0087 0.028 0.316 0.752 -0.045 0.063
c0210 0.0229 0.025 0.909 0.364 -0.026 0.072
c1020 -0.0027 0.015 -0.184 0.854 -0.032 0.026
c0625 -0.0370 0.017 -2.219 0.027 -0.070 -0.004
c1915 -0.0137 0.019 -0.729 0.466 -0.051 0.023
c0600 0.0142 0.017 0.832 0.406 -0.019 0.048
c2135 -0.0091 0.031 -0.292 0.770 -0.070 0.052
c0305 -0.0187 0.024 -0.789 0.430 -0.065 0.028
c1330 0.0188 0.008 2.503 0.012 0.004 0.034
c1545 0.0085 0.012 0.692 0.489 -0.016 0.033
c2330 0.0163 0.028 0.582 0.560 -0.038 0.071
c1530 -0.0189 0.012 -1.603 0.109 -0.042 0.004
c1640 -0.0386 0.015 -2.512 0.012 -0.069 -0.008
c1450 -0.0291 0.011 -2.697 0.007 -0.050 -0.008
c0200 -0.0389 0.022 -1.795 0.073 -0.081 0.004
c0310 0.0906 0.026 3.464 0.001 0.039 0.142
c1815 0.0201 0.015 1.367 0.172 -0.009 0.049
c1315 0.0050 0.010 0.478 0.633 -0.015 0.025
c0120 -0.0145 0.021 -0.700 0.484 -0.055 0.026
c0605 0.0068 0.015 0.455 0.649 -0.022 0.036
c1630 0.0136 0.014 0.953 0.341 -0.014 0.042
c0040 0.0090 0.023 0.387 0.699 -0.037 0.055
c0435 -0.0921 0.029 -3.172 0.002 -0.149 -0.035
c0755 -0.0116 0.013 -0.886 0.376 -0.037 0.014
c0555 0.0050 0.023 0.221 0.825 -0.039 0.049
c2125 0.0148 0.031 0.483 0.629 -0.045 0.075
c0345 -0.0166 0.030 -0.551 0.581 -0.075 0.042
c0800 0.0244 0.011 2.208 0.027 0.003 0.046
c1610 0.0076 0.013 0.592 0.554 -0.018 0.033
c0455 0.0385 0.032 1.211 0.226 -0.024 0.101
c0410 -0.0141 0.024 -0.583 0.560 -0.062 0.033
c1910 0.0206 0.016 1.255 0.210 -0.012 0.053
c0025 -0.0155 0.022 -0.705 0.481 -0.059 0.028
c0735 0.0283 0.013 2.240 0.025 0.004 0.053
c0510 0.0655 0.026 2.545 0.011 0.015 0.116
c0335 -0.0153 0.027 -0.559 0.576 -0.069 0.038
c0240 -0.0022 0.025 -0.088 0.930 -0.051 0.046
c1200 -0.0295 0.013 -2.328 0.020 -0.054 -0.005
c1335 0.0090 0.007 1.274 0.203 -0.005 0.023
c0840 -0.0142 0.013 -1.108 0.268 -0.039 0.011
c0645 -0.0089 0.017 -0.531 0.595 -0.042 0.024
c0330 0.0298 0.030 0.993 0.321 -0.029 0.089
c1925 0.0145 0.019 0.746 0.456 -0.024 0.052
c1930 -0.0003 0.020 -0.017 0.986 -0.039 0.038
c0830 -0.0073 0.012 -0.604 0.546 -0.031 0.016
c0205 0.0291 0.023 1.266 0.206 -0.016 0.074
c1600 -0.0064 0.010 -0.649 0.517 -0.026 0.013
c0740 0.0228 0.013 1.768 0.077 -0.002 0.048
c1250 0.0183 0.010 1.910 0.056 -0.000 0.037
c2100 -4.595e-05 0.007 -0.007 0.994 -0.013 0.013
c1030 0.0035 0.015 0.228 0.819 -0.026 0.033
c1730 -0.0291 0.017 -1.716 0.086 -0.062 0.004
c2255 0.0331 0.027 1.204 0.229 -0.021 0.087
c2105 0.0025 0.009 0.278 0.781 -0.015 0.020
c1225 0.0117 0.014 0.826 0.409 -0.016 0.040
c1145 -0.0005 0.013 -0.039 0.969 -0.026 0.025
c1745 -0.0355 0.017 -2.116 0.034 -0.068 -0.003
c1750 0.0074 0.017 0.424 0.672 -0.027 0.042
c1055 0.0154 0.016 0.965 0.335 -0.016 0.047
c2220 -0.0140 0.030 -0.469 0.639 -0.073 0.045
c1635 -0.0013 0.015 -0.085 0.933 -0.031 0.028
c1135 -0.0317 0.015 -2.093 0.036 -0.061 -0.002
c1440 -0.0157 0.011 -1.408 0.159 -0.038 0.006
c0640 -0.0008 0.016 -0.052 0.959 -0.033 0.031
c2315 -0.0387 0.027 -1.432 0.152 -0.092 0.014
c1345 0.0115 0.009 1.290 0.197 -0.006 0.029
c0825 0.0360 0.013 2.762 0.006 0.010 0.062
c0420 -0.0588 0.033 -1.792 0.073 -0.123 0.006
c1615 -0.0406 0.014 -2.948 0.003 -0.068 -0.014
c2115 0.0190 0.028 0.686 0.493 -0.035 0.073
c2335 0.0278 0.027 1.034 0.301 -0.025 0.080
c0100 0.0343 0.022 1.560 0.119 -0.009 0.077
c1700 0.0195 0.014 1.376 0.169 -0.008 0.047
c0750 0.0329 0.014 2.426 0.015 0.006 0.060
c0925 -0.0223 0.014 -1.541 0.123 -0.051 0.006
c1555 -0.0116 0.013 -0.916 0.360 -0.036 0.013
c1040 0.0288 0.015 1.885 0.060 -0.001 0.059
c1455 -0.0111 0.011 -1.053 0.292 -0.032 0.010
c0930 -0.0047 0.014 -0.334 0.738 -0.032 0.023
c1120 0.0065 0.014 0.448 0.654 -0.022 0.035
c2015 -0.0532 0.024 -2.177 0.030 -0.101 -0.005
c1150 0.0031 0.012 0.267 0.789 -0.020 0.026
c2110 0.0138 0.026 0.543 0.588 -0.036 0.064
c2010 0.0134 0.023 0.580 0.562 -0.032 0.059
c0245 -0.0055 0.026 -0.217 0.828 -0.056 0.044
c0230 0.0355 0.025 1.407 0.160 -0.014 0.085
c0700 0.0058 0.012 0.492 0.623 -0.017 0.029
c0505 0.0117 0.025 0.459 0.646 -0.038 0.062
c1010 -0.0173 0.015 -1.181 0.238 -0.046 0.011
c1845 0.0503 0.020 2.579 0.010 0.012 0.089
c1940 0.0031 0.020 0.152 0.880 -0.037 0.043
c1725 0.0270 0.016 1.639 0.101 -0.005 0.059
c1140 -0.0145 0.015 -0.964 0.335 -0.044 0.015
c2225 0.0234 0.028 0.838 0.402 -0.031 0.078
c1245 0.0043 0.009 0.504 0.615 -0.012 0.021
c1850 -0.0157 0.020 -0.796 0.426 -0.054 0.023
c0745 0.0273 0.013 2.117 0.034 0.002 0.053
c1950 0.0076 0.021 0.358 0.720 -0.034 0.049
c1445 -0.0271 0.011 -2.570 0.010 -0.048 -0.006
c0050 0.0164 0.023 0.709 0.478 -0.029 0.062
c2350 -0.0219 0.026 -0.858 0.391 -0.072 0.028
c0030 0.0427 0.024 1.781 0.075 -0.004 0.090
c0440 0.0468 0.030 1.557 0.120 -0.012 0.106
c0710 -0.0056 0.011 -0.492 0.622 -0.028 0.017
c2230 -0.0200 0.031 -0.652 0.515 -0.080 0.040
c2345 0.0007 0.024 0.030 0.976 -0.047 0.049
c0515 0.0410 0.028 1.461 0.144 -0.014 0.096
c2310 -0.0475 0.030 -1.590 0.112 -0.106 0.011
c1840 0.0240 0.016 1.465 0.143 -0.008 0.056
c0935 0.0352 0.013 2.806 0.005 0.011 0.060
c0425 -0.0794 0.033 -2.395 0.017 -0.144 -0.014
c0320 -0.0263 0.028 -0.943 0.346 -0.081 0.028
c0055 -0.0163 0.019 -0.858 0.391 -0.053 0.021
c2250 -0.0565 0.029 -1.975 0.048 -0.113 -0.000
c0945 0.0030 0.014 0.209 0.835 -0.025 0.031
c0525 -0.0607 0.028 -2.184 0.029 -0.115 -0.006
c0140 -0.0044 0.022 -0.206 0.837 -0.047 0.038
c1715 -0.0266 0.015 -1.735 0.083 -0.057 0.003
c2005 -0.0076 0.017 -0.447 0.655 -0.041 0.026
c1415 0.0072 0.010 0.732 0.464 -0.012 0.027
c1735 -0.0173 0.015 -1.185 0.236 -0.046 0.011
c2025 0.0092 0.026 0.355 0.723 -0.042 0.060
c1830 0.0310 0.018 1.713 0.087 -0.004 0.066
c2235 0.0037 0.030 0.126 0.900 -0.054 0.062
c0010 -0.0042 0.019 -0.219 0.827 -0.042 0.034
c0635 -0.0338 0.016 -2.105 0.035 -0.065 -0.002
c1520 -0.0172 0.012 -1.391 0.164 -0.041 0.007
c1350 -0.0142 0.010 -1.464 0.143 -0.033 0.005
c0035 -0.0155 0.021 -0.727 0.467 -0.057 0.026
c0445 0.0249 0.032 0.777 0.437 -0.038 0.088
c0225 -0.0239 0.024 -0.995 0.320 -0.071 0.023
c0910 -0.0190 0.013 -1.442 0.149 -0.045 0.007
c1755 0.0225 0.018 1.260 0.208 -0.013 0.058
c1435 -0.0201 0.010 -1.930 0.054 -0.041 0.000
c0340 -0.0885 0.026 -3.371 0.001 -0.140 -0.037
c0655 0.0246 0.015 1.648 0.099 -0.005 0.054
c0315 -0.0327 0.029 -1.116 0.265 -0.090 0.025
c0815 -0.0066 0.012 -0.531 0.596 -0.031 0.018
c1100 0.0208 0.014 1.464 0.143 -0.007 0.049
c0955 -0.0159 0.015 -1.050 0.294 -0.045 0.014
c2035 0.0469 0.026 1.825 0.068 -0.003 0.097
c0500 0.0040 0.027 0.149 0.881 -0.048 0.056
c0115 -0.0138 0.021 -0.653 0.514 -0.055 0.028
c1550 0.0007 0.013 0.056 0.955 -0.025 0.027
c1115 -0.0108 0.015 -0.717 0.473 -0.040 0.019
c1305 0.0070 0.010 0.706 0.480 -0.012 0.026
c0015 0.0275 0.021 1.335 0.182 -0.013 0.068
c0045 -0.0014 0.022 -0.063 0.950 -0.044 0.041
c0430 -0.1043 0.033 -3.150 0.002 -0.169 -0.039
c1105 -0.0387 0.015 -2.555 0.011 -0.068 -0.009
c0020 -0.0524 0.023 -2.314 0.021 -0.097 -0.008
c1155 0.0168 0.015 1.152 0.249 -0.012 0.045
c0400 -0.0263 0.028 -0.938 0.348 -0.081 0.029
c1800 -0.0096 0.010 -0.963 0.335 -0.029 0.010
c0105 -0.0097 0.020 -0.479 0.632 -0.050 0.030
c2055 -0.0240 0.025 -0.955 0.340 -0.073 0.025
c0450 -0.0150 0.031 -0.481 0.630 -0.076 0.046
c1825 -0.0108 0.018 -0.605 0.545 -0.046 0.024
c1300 -0.0006 0.010 -0.054 0.957 -0.021 0.020
c0540 -0.0524 0.026 -2.018 0.044 -0.103 -0.001
c1205 -0.0312 0.013 -2.357 0.019 -0.057 -0.005
c0725 -0.0408 0.013 -3.100 0.002 -0.067 -0.015
c0145 0.0541 0.022 2.482 0.013 0.011 0.097
c1125 -0.0061 0.016 -0.385 0.700 -0.037 0.025
c1540 0.0123 0.012 1.042 0.297 -0.011 0.036
c1220 0.0113 0.012 0.958 0.338 -0.012 0.034
c1230 -0.0026 0.006 -0.433 0.665 -0.014 0.009
c1510 0.0094 0.010 0.902 0.367 -0.011 0.030
c0415 0.0412 0.030 1.371 0.170 -0.018 0.100
c0355 -0.0218 0.030 -0.731 0.465 -0.080 0.037
c2150 -0.0052 0.030 -0.174 0.862 -0.063 0.053
c1400 -0.0023 0.008 -0.274 0.784 -0.019 0.014
c1805 -0.0149 0.011 -1.369 0.171 -0.036 0.006
c1945 -0.0205 0.020 -1.033 0.302 -0.059 0.018
c2045 0.0530 0.024 2.201 0.028 0.006 0.100
c1235 -0.0117 0.008 -1.415 0.157 -0.028 0.005
c0615 0.0133 0.017 0.778 0.437 -0.020 0.047
c2030 -0.0444 0.024 -1.822 0.069 -0.092 0.003
c1920 0.0375 0.019 2.000 0.046 0.001 0.074
c2050 0.0954 0.025 3.849 0.000 0.047 0.144
c0005 0.0059 0.015 0.399 0.690 -0.023 0.035
c2130 0.0307 0.030 1.029 0.304 -0.028 0.089
c0940 0.0242 0.014 1.679 0.093 -0.004 0.052
c2205 0.0187 0.021 0.870 0.384 -0.023 0.061
c1405 -0.0193 0.009 -2.254 0.024 -0.036 -0.003
c2305 0.0333 0.024 1.364 0.173 -0.015 0.081
c1935 0.0058 0.019 0.301 0.764 -0.032 0.044
c0325 -0.0593 0.030 -1.969 0.049 -0.118 -0.000
c1810 -0.0213 0.014 -1.497 0.134 -0.049 0.007
c1835 0.0327 0.015 2.130 0.033 0.003 0.063
c0900 0.0037 0.011 0.325 0.745 -0.019 0.026
c1425 -0.0215 0.011 -1.965 0.049 -0.043 -5.06e-05
c0125 -0.0408 0.022 -1.891 0.059 -0.083 0.002
c0850 -0.0030 0.013 -0.236 0.814 -0.028 0.022
c1325 -0.0477 0.012 -3.888 0.000 -0.072 -0.024
c1525 0.0098 0.012 0.821 0.412 -0.014 0.033
c0135 0.0353 0.020 1.731 0.084 -0.005 0.075
c1505 0.0205 0.010 2.140 0.032 0.002 0.039
c1740 0.0008 0.018 0.044 0.965 -0.034 0.035
c0805 0.0098 0.011 0.924 0.355 -0.011 0.031
c2020 -0.0237 0.024 -0.981 0.327 -0.071 0.024
c2120 -0.0276 0.028 -1.002 0.316 -0.082 0.026
c0950 -0.0076 0.015 -0.517 0.605 -0.037 0.021
c1605 -0.0037 0.013 -0.288 0.773 -0.029 0.021
c1025 -0.0109 0.014 -0.755 0.450 -0.039 0.017
c1355 0.0063 0.011 0.588 0.556 -0.015 0.027
c0845 0.0061 0.013 0.469 0.639 -0.019 0.032
c1905 -0.0246 0.014 -1.774 0.076 -0.052 0.003
c2000 -0.0022 0.018 -0.122 0.903 -0.038 0.033
c1955 -0.0034 0.021 -0.160 0.873 -0.045 0.038
c0150 -0.0024 0.022 -0.110 0.912 -0.045 0.040
c0110 -0.0321 0.021 -1.541 0.124 -0.073 0.009
c2210 -0.0170 0.024 -0.724 0.469 -0.063 0.029
c1340 -0.0003 0.009 -0.029 0.977 -0.018 0.017
c0220 0.0204 0.026 0.789 0.430 -0.030 0.071
c1110 0.0089 0.015 0.609 0.542 -0.020 0.038
c0405 -0.0499 0.030 -1.662 0.097 -0.109 0.009
c0915 -0.0351 0.013 -2.605 0.009 -0.062 -0.009
c2140 0.0210 0.030 0.690 0.490 -0.039 0.081
c0630 0.0278 0.016 1.718 0.086 -0.004 0.059
c2355 0.0119 0.023 0.512 0.609 -0.034 0.057
c0720 0.0248 0.013 1.939 0.053 -0.000 0.050
c1410 0.0022 0.009 0.237 0.813 -0.016 0.021
c1645 -0.0095 0.016 -0.604 0.546 -0.040 0.021
c1500 0.0441 0.009 5.129 0.000 0.027 0.061
c2325 0.0680 0.029 2.338 0.019 0.011 0.125
c0730 0.0118 0.011 1.060 0.289 -0.010 0.034
c0715 -0.0039 0.012 -0.317 0.751 -0.028 0.020
c1045 -0.0221 0.016 -1.411 0.158 -0.053 0.009
c1625 -0.0135 0.014 -0.952 0.341 -0.041 0.014
c0820 0.0259 0.012 2.146 0.032 0.002 0.050
c1720 0.0090 0.016 0.553 0.580 -0.023 0.041
c2245 -0.0404 0.030 -1.346 0.178 -0.099 0.018
c2300 0.0118 0.024 0.486 0.627 -0.036 0.060
c2215 0.0115 0.026 0.435 0.664 -0.040 0.063
c1035 -0.0063 0.015 -0.423 0.672 -0.036 0.023
c0550 0.0230 0.024 0.942 0.346 -0.025 0.071
==============================================================================
Omnibus: 4043.713 Durbin-Watson: 1.954
Prob(Omnibus): 0.000 Jarque-Bera (JB): 4176392.615
Skew: -5.781 Prob(JB): 0.00
Kurtosis: 177.295 Cond. No. 1.12e+04
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The condition number is large, 1.12e+04. This might indicate that there are
strong multicollinearity or other numerical problems.
MSr: 0.0003056669174634134
MSe: 0.00019993423813406298