------------------------------------------------------------------------------------------------------------------------------------- name: log: C:\vhm812-data\l2b_linear_reg_diag.txt log type: text opened on: 19 Jan 2021, 09:29:08 . set more off . . * open the DAISY dataset . use daisy2red.dta, clear . * create variables . gen parity1=parity-1 . gen calv_mth=month(calv_dt) . gen aut_calv=(calv_mth>=2 & calv_mth<=7) if !missing(calv_mth) . label value aut_calv noyes . gen hs100_ctr=(herd_size-251)/100 . gen hs100_ctr_sq=hs100_ctr^2 . * save new dataset to be used later, not needed for this exercise . save daisy2red_01, replace file daisy2red_01.dta saved . . *final model . reg wpc hs100_ctr hs100_ctr_sq parity1 i.aut_calv i.twin i.dyst i.rp##i.vag_disch Source | SS df MS Number of obs = 1,574 -------------+---------------------------------- F(9, 1564) = 13.22 Model | 296062.694 9 32895.8549 Prob > F = 0.0000 Residual | 3892027.86 1,564 2488.50886 R-squared = 0.0707 -------------+---------------------------------- Adj R-squared = 0.0653 Total | 4188090.56 1,573 2662.48605 Root MSE = 49.885 ------------------------------------------------------------------------------ wpc | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- hs100_ctr | 19.85708 2.163397 9.18 0.000 15.61361 24.10054 hs100_ctr_sq | 11.13827 3.111145 3.58 0.000 5.035817 17.24073 parity1 | 1.13721 .8583103 1.32 0.185 -.5463501 2.82077 | aut_calv | yes | -8.263839 2.537751 -3.26 0.001 -13.24159 -3.286086 | twin | yes | 20.68314 9.845165 2.10 0.036 1.37203 39.99425 | dyst | yes | 11.70041 5.462576 2.14 0.032 .985666 22.41516 | rp | yes | 5.98687 4.811976 1.24 0.214 -3.451734 15.42547 | vag_disch | yes | 1.228196 7.161395 0.17 0.864 -12.81875 15.27514 | rp#vag_disch | yes#yes | 22.85194 12.51605 1.83 0.068 -1.698056 47.40194 | _cons | 64.33029 2.634114 24.42 0.000 59.16352 69.49705 ------------------------------------------------------------------------------ . *initial diagnostic . capture drop fit stdres . predict fit, xb . predict stdres, rstandard . . *homoskedasticity . scatter stdres fit . egen fitcat=cut(fit), at(0 50 55 60 65 70 75 80 85 90 95 200) icodes . tabstat stdres, s(mean sd count) by(fitcat) Summary for variables: stdres by categories of: fitcat fitcat | mean sd N ---------+------------------------------ 0 | -.0570064 .7397317 92 1 | -.0073181 .899948 179 2 | .0578738 .9474714 210 3 | -.0595596 .8973734 233 4 | .0241511 1.009195 240 5 | .1411393 1.186747 129 6 | -.0596733 1.042643 135 7 | -.0978648 1.090551 119 8 | .1050465 1.206279 93 9 | -.0443726 1.063637 107 10 | -.0275786 .9893797 37 ---------+------------------------------ Total | .0000153 1.000497 1574 ---------------------------------------- . estat hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of wpc chi2(1) = 20.58 Prob > chi2 = 0.0000 . estat imtest Cameron & Trivedi's decomposition of IM-test --------------------------------------------------- Source | chi2 df p ---------------------+----------------------------- Heteroskedasticity | 74.11 44 0.0030 Skewness | 143.84 9 0.0000 Kurtosis | 33.27 1 0.0000 ---------------------+----------------------------- Total | 251.22 54 0.0000 --------------------------------------------------- . . *normality . qnorm stdres . hist stdres, normal (bin=31, start=-1.5436347, width=.18891791) . summ stdres, d Standardized residuals ------------------------------------------------------------- Percentiles Smallest 1% -1.295559 -1.543635 5% -1.085226 -1.491268 10% -.9411177 -1.445124 Obs 1,574 25% -.7014489 -1.43959 Sum of Wgt. 1,574 50% -.3049904 Mean .0000153 Largest Std. Dev. 1.000497 75% .4302664 3.716394 90% 1.438834 3.910809 Variance 1.000993 95% 2.065976 4.020359 Skewness 1.371514 99% 3.24163 4.31282 Kurtosis 4.72451 . swilk stdres Shapiro-Wilk W test for normal data Variable | Obs W V z Prob>z -------------+------------------------------------------------------ stdres | 1,574 0.87871 115.660 11.977 0.00000 . . **transforming wpc . xi:boxcox wpc hs100_ctr hs100_ctr_sq parity1 i.aut_calv i.twin i.dyst i.rp*i.vag_disch i.aut_calv _Iaut_calv_0-1 (naturally coded; _Iaut_calv_0 omitted) i.twin _Itwin_0-1 (naturally coded; _Itwin_0 omitted) i.dyst _Idyst_0-1 (naturally coded; _Idyst_0 omitted) i.rp _Irp_0-1 (naturally coded; _Irp_0 omitted) i.vag_disch _Ivag_disch_0-1 (naturally coded; _Ivag_disch_0 omitted) i.rp*i.vag_di~h _IrpXvag_#_# (coded as above) Fitting comparison model Iteration 0: log likelihood = -8439.9903 Iteration 1: log likelihood = -8082.9461 Iteration 2: log likelihood = -8035.2171 Iteration 3: log likelihood = -8034.9512 Iteration 4: log likelihood = -8034.9511 Fitting full model Iteration 0: log likelihood = -8382.2918 Iteration 1: log likelihood = -8022.9541 Iteration 2: log likelihood = -7958.3552 Iteration 3: log likelihood = -7957.985 Iteration 4: log likelihood = -7957.9849 Number of obs = 1,574 LR chi2(9) = 153.93 Log likelihood = -7957.9849 Prob > chi2 = 0.000 ------------------------------------------------------------------------------ wpc | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- /theta | .1097595 .0270646 4.06 0.000 .0567138 .1628052 ------------------------------------------------------------------------------ Estimates of scale-variant parameters ---------------------------- | Coef. -------------+-------------- Notrans | hs100_ctr | .5236879 hs100_ctr_sq | .316867 parity1 | .0207726 _Iaut_calv_1 | -.2119782 _Itwin_1 | .5994942 _Idyst_1 | .1803076 _Irp_1 | .1697644 _Ivag_disc~1 | -.0333896 _IrpXvag_1_1 | .6352271 _cons | 4.90172 -------------+-------------- /sigma | 1.119778 ---------------------------- --------------------------------------------------------- Test Restricted LR statistic P-value H0: log likelihood chi2 Prob > chi2 --------------------------------------------------------- theta = -1 -9664.734 3413.50 0.000 theta = 0 -7966.6087 17.25 0.000 theta = 1 -8382.2918 848.61 0.000 --------------------------------------------------------- . gen wpc_ln=ln(wpc) . reg wpc_ln hs100_ctr hs100_ctr_sq parity1 i.aut_calv i.twin i.dyst i.rp##vag_disch Source | SS df MS Number of obs = 1,574 -------------+---------------------------------- F(9, 1564) = 18.05 Model | 86.9474063 9 9.66082293 Prob > F = 0.0000 Residual | 836.874538 1,564 .535086022 R-squared = 0.0941 -------------+---------------------------------- Adj R-squared = 0.0889 Total | 923.821945 1,573 .587299393 Root MSE = .7315 ------------------------------------------------------------------------------ wpc_ln | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- hs100_ctr | .343658 .0317233 10.83 0.000 .2814333 .4058827 hs100_ctr_sq | .2118728 .0456207 4.64 0.000 .1223885 .301357 parity1 | .0129844 .012586 1.03 0.302 -.0117028 .0376715 | aut_calv | yes | -.1371621 .0372127 -3.69 0.000 -.2101542 -.0641701 | twin | yes | .3927426 .1443661 2.72 0.007 .1095711 .6759141 | dyst | yes | .1109405 .0801013 1.39 0.166 -.0461768 .2680578 | rp | yes | .1123166 .0705612 1.59 0.112 -.0260878 .250721 | vag_disch | yes | -.0260135 .1050122 -0.25 0.804 -.231993 .1799661 | rp#vag_disch | yes#yes | .4136999 .183531 2.25 0.024 .0537072 .7736926 | _cons | 3.888587 .0386257 100.67 0.000 3.812823 3.96435 ------------------------------------------------------------------------------ . **model checking . capture drop fit stdres . predict fit, xb . predict stdres, rstandard . *homoskedasticity . estat hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of wpc_ln chi2(1) = 19.98 Prob > chi2 = 0.0000 . estat imtest Cameron & Trivedi's decomposition of IM-test --------------------------------------------------- Source | chi2 df p ---------------------+----------------------------- Heteroskedasticity | 48.63 44 0.2919 Skewness | 8.75 9 0.4605 Kurtosis | 0.52 1 0.4698 ---------------------+----------------------------- Total | 57.91 54 0.3332 --------------------------------------------------- . scatter stdres fit . *normality . qnorm stdres . hist stdres, normal (bin=31, start=-5.3996067, width=.25507099) . summ stdres, d Standardized residuals ------------------------------------------------------------- Percentiles Smallest 1% -2.211829 -5.399607 5% -1.564966 -4.989504 10% -1.242075 -3.61681 Obs 1,574 25% -.7143057 -3.316 Sum of Wgt. 1,574 50% -.0133218 Mean .000018 Largest Std. Dev. 1.000267 75% .7199247 2.358784 90% 1.333008 2.373729 Variance 1.000533 95% 1.628151 2.452677 Skewness -.1738834 99% 2.15899 2.507594 Kurtosis 3.382854 . swilk stdres Shapiro-Wilk W test for normal data Variable | Obs W V z Prob>z -------------+------------------------------------------------------ stdres | 1,574 0.98974 9.787 5.751 0.00000 . * check for collinearity issues . estat vif Variable | VIF 1/VIF -------------+---------------------- hs100_ctr | 1.14 0.878856 hs100_ctr_sq | 1.14 0.879714 parity1 | 1.04 0.962306 1.aut_calv | 1.02 0.985045 1.twin | 1.03 0.967484 1.dyst | 1.06 0.943538 1.rp | 1.26 0.796702 1.vag_disch | 1.60 0.624261 rp#vag_disch | 1 1 | 1.85 0.539810 -------------+---------------------- Mean VIF | 1.24 . estat vce, corr Correlation matrix of coefficients of regress model | 1. 1. 1. 1. 1. 1.rp# e(V) | hs100_~r hs100_~q parity1 aut_calv twin dyst rp vag_di~h 1.vag_~h _cons -------------+---------------------------------------------------------------------------------------------------- hs100_ctr | 1.0000 hs100_ctr_sq | 0.3269 1.0000 parity1 | -0.0415 -0.0468 1.0000 1.aut_calv | 0.0521 -0.0265 -0.0500 1.0000 1.twin | 0.0326 0.0464 -0.0666 -0.0487 1.0000 1.dyst | 0.1146 0.0717 0.1303 0.0023 -0.0214 1.0000 1.rp | 0.0230 0.0540 0.0318 0.0438 -0.0807 -0.0656 1.0000 1.vag_disch | 0.0304 0.0698 0.0649 0.0387 -0.0383 -0.1188 0.0742 1.0000 1.rp#| 1.vag_disch | -0.0184 -0.0571 -0.0644 -0.0024 -0.0429 0.0861 -0.3873 -0.5752 1.0000 _cons | -0.1716 -0.4415 -0.5404 -0.4246 0.0004 -0.2091 -0.1974 -0.1711 0.1133 1.0000 . . **linearity . * check modelling of herd_size and parity . lowess stdres herd_size . lowess stdres parity . * looking at herd_size without herd_size in the model . reg wpc_ln parity1 i.aut_calv i.twin i.dyst i.rp##vag_disch Source | SS df MS Number of obs = 1,574 -------------+---------------------------------- F(7, 1566) = 5.82 Model | 23.4240047 7 3.34628639 Prob > F = 0.0000 Residual | 900.39794 1,566 .574966756 R-squared = 0.0254 -------------+---------------------------------- Adj R-squared = 0.0210 Total | 923.821945 1,573 .587299393 Root MSE = .75827 ------------------------------------------------------------------------------ wpc_ln | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- parity1 | .0191623 .0130272 1.47 0.142 -.0063904 .0447149 | aut_calv | yes | -.156154 .0384813 -4.06 0.000 -.2316343 -.0806737 | twin | yes | .3353984 .1494624 2.24 0.025 .0422309 .6285659 | dyst | yes | .0081531 .0824313 0.10 0.921 -.1535343 .1698404 | rp | yes | .0906877 .0730356 1.24 0.215 -.0525701 .2339455 | vag_disch | yes | -.0684004 .1085865 -0.63 0.529 -.2813906 .1445898 | rp#vag_disch | yes#yes | .4618901 .1899367 2.43 0.015 .089333 .8344472 | _cons | 3.978786 .0359075 110.81 0.000 3.908354 4.049218 ------------------------------------------------------------------------------ . predict stdres1, rstandard . lowess stdres1 herd_size . * looking at parity without parity in the model . reg wpc_ln hs100_ctr hs100_ctr_sq i.aut_calv i.twin i.dyst i.rp##vag_disch Source | SS df MS Number of obs = 1,574 -------------+---------------------------------- F(8, 1565) = 20.18 Model | 86.3779092 8 10.7972387 Prob > F = 0.0000 Residual | 837.444036 1,565 .53510801 R-squared = 0.0935 -------------+---------------------------------- Adj R-squared = 0.0889 Total | 923.821945 1,573 .587299393 Root MSE = .73151 ------------------------------------------------------------------------------ wpc_ln | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- hs100_ctr | .3450169 .0316966 10.88 0.000 .2828447 .4071892 hs100_ctr_sq | .2140753 .0455717 4.70 0.000 .1246873 .3034633 | aut_calv | yes | -.1352417 .0371669 -3.64 0.000 -.2081438 -.0623395 | twin | yes | .4026686 .1440481 2.80 0.005 .1201211 .6852162 | dyst | yes | .1001739 .0794202 1.26 0.207 -.0556073 .2559551 | rp | yes | .1099998 .0705269 1.56 0.119 -.0283373 .2483368 | vag_disch | yes | -.0330431 .1047931 -0.32 0.753 -.2385927 .1725065 | rp#vag_disch | yes#yes | .4258954 .1831536 2.33 0.020 .066643 .7851478 | _cons | 3.910122 .0324999 120.31 0.000 3.846374 3.97387 ------------------------------------------------------------------------------ . predict stdres2, rstandard . lowess stdres2 parity1 . . **residuals and diagnostics . reg wpc_ln hs100_ctr hs100_ctr_sq parity1 aut_calv twin i.dyst i.rp##i.vag_disch Source | SS df MS Number of obs = 1,574 -------------+---------------------------------- F(9, 1564) = 18.05 Model | 86.9474063 9 9.66082293 Prob > F = 0.0000 Residual | 836.874538 1,564 .535086022 R-squared = 0.0941 -------------+---------------------------------- Adj R-squared = 0.0889 Total | 923.821945 1,573 .587299393 Root MSE = .7315 ------------------------------------------------------------------------------ wpc_ln | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- hs100_ctr | .343658 .0317233 10.83 0.000 .2814333 .4058827 hs100_ctr_sq | .2118728 .0456207 4.64 0.000 .1223885 .301357 parity1 | .0129844 .012586 1.03 0.302 -.0117028 .0376715 aut_calv | -.1371621 .0372127 -3.69 0.000 -.2101542 -.0641701 twin | .3927426 .1443661 2.72 0.007 .1095711 .6759141 | dyst | yes | .1109405 .0801013 1.39 0.166 -.0461768 .2680578 | rp | yes | .1123166 .0705612 1.59 0.112 -.0260878 .250721 | vag_disch | yes | -.0260135 .1050122 -0.25 0.804 -.231993 .1799661 | rp#vag_disch | yes#yes | .4136999 .183531 2.25 0.024 .0537072 .7736926 | _cons | 3.888587 .0386257 100.67 0.000 3.812823 3.96435 ------------------------------------------------------------------------------ . drop fit stdres . capture drop delres - dfit . capture drop _dfbeta* /* adjust if not defined */ . . predict fit, xb . predict stdres, rstandard . predict delres, rstudent . predict lev, lev . predict cook, cooksd . predict dfit, dfit . dfbeta _dfbeta_1: dfbeta(hs100_ctr) _dfbeta_2: dfbeta(hs100_ctr_sq) _dfbeta_3: dfbeta(parity1) _dfbeta_4: dfbeta(aut_calv) _dfbeta_5: dfbeta(twin) _dfbeta_6: dfbeta(1.dyst) _dfbeta_7: dfbeta(1.rp) _dfbeta_8: dfbeta(1.vag_disch) _dfbeta_9: dfbeta(1.rp#1.vag_disch) . scalar nobs=1574 . scalar nparam=10 . . ** formatting several variables at once to show only 3 decimals - advanced command - ignore for now . foreach var in wpc_ln fit stdres delres lev cook dfit _dfbeta* { 2. format `var' %5.3f 3. } . . * examine outliers . * number of standardized residuals outside -2/+2 and -3/+3 . * expect 5% (n=79) outside -2,+2 and 0.3% (n=14) outside -3,+3 . count if abs(stdres)>2 /* n=50 */ 50 . count if abs(stdres)>3 /* n=6, so one more very extreme residual values than expected */ 6 . sum delres, d Studentized residuals ------------------------------------------------------------- Percentiles Smallest 1% -2.214588 -5.448908 5% -1.565692 -5.028087 10% -1.242291 -3.630869 Obs 1,574 25% -.7141938 -3.326655 Sum of Wgt. 1,574 50% -.0133175 Mean -.0000384 Largest Std. Dev. 1.001035 75% .7198138 2.362236 90% 1.33334 2.377255 Variance 1.002071 95% 1.629012 2.456621 Skewness -.1785964 99% 2.161524 2.511847 Kurtosis 3.415061 . * outlier test based on deletion residuals . display 2*nobs*ttail(nobs-nparam-1, 5.02) /* P=0.0009 so S */ .0009064 . display invttail(nobs-nparam-1,.025/nobs) /* values >= abs(4.17) outliers*/ 4.1726361 . br if abs(delres) >=4 . **there are two observations with extreme residual values (outliers) . ** two cows with 1 days interval from the end of wp to conception . ** cows 2272 (herd 106) and cow 1032 (herd 4) . . *most extreme residuals . sort stdres . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres in 1/10 /* most extreme negative residuals * > / +------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres delres | |------------------------------------------------------------------------------------------------------| 1. | 1 0.000 3.946 no 263 1 no no no no -5.400 -5.449 | 2. | 1 0.000 3.646 yes 201 1 no no no no -4.990 -5.028 | 3. | 3 1.099 3.741 yes 235 3 no no no no -3.617 -3.631 | 4. | 4 1.386 3.809 no 201 3 no no no no -3.316 -3.327 | 5. | 4 1.386 3.633 yes 201 0 no no no no -3.076 -3.084 | |------------------------------------------------------------------------------------------------------| 6. | 5 1.609 3.822 no 201 4 no no no no -3.030 -3.038 | 7. | 5 1.609 3.770 no 201 0 no no no no -2.958 -2.965 | 8. | 7 1.946 3.933 no 263 0 no no no no -2.720 -2.726 | 9. | 7 1.946 3.767 no 185 1 no no no no -2.493 -2.497 | 10. | 9 2.197 3.990 yes 294 4 no no no no -2.455 -2.459 | +------------------------------------------------------------------------------------------------------+ . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres in -10/-1 /* most extreme positive residuals > */ +------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres delres | |------------------------------------------------------------------------------------------------------| 1565. | 214 5.366 3.741 yes 185 1 no yes no no 2.235 2.238 | 1566. | 232 5.447 3.795 yes 201 4 no yes no no 2.274 2.277 | 1567. | 218 5.384 3.728 yes 185 0 no yes no no 2.279 2.282 | 1568. | 230 5.438 3.754 yes 235 4 no no no no 2.307 2.310 | 1569. | 207 5.333 3.646 yes 201 1 no no no no 2.309 2.312 | |------------------------------------------------------------------------------------------------------| 1570. | 213 5.361 3.672 yes 201 3 no no no no 2.313 2.316 | 1571. | 240 5.481 3.767 yes 185 3 no yes no no 2.359 2.362 | 1572. | 217 5.380 3.646 yes 201 1 no no no no 2.374 2.377 | 1573. | 234 5.455 3.668 yes 125 1 no no no no 2.453 2.457 | 1574. | 253 5.533 3.707 yes 125 4 no no no no 2.508 2.512 | +------------------------------------------------------------------------------------------------------+ . . sort delres . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres in 1/5 /* most extreme negative residuals */ +------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres delres | |------------------------------------------------------------------------------------------------------| 1. | 1 0.000 3.946 no 263 1 no no no no -5.400 -5.449 | 2. | 1 0.000 3.646 yes 201 1 no no no no -4.990 -5.028 | 3. | 3 1.099 3.741 yes 235 3 no no no no -3.617 -3.631 | 4. | 4 1.386 3.809 no 201 3 no no no no -3.316 -3.327 | 5. | 4 1.386 3.633 yes 201 0 no no no no -3.076 -3.084 | +------------------------------------------------------------------------------------------------------+ . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres in -5/-1 /* most extreme positive residuals > */ +------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres delres | |------------------------------------------------------------------------------------------------------| 1570. | 213 5.361 3.672 yes 201 3 no no no no 2.313 2.316 | 1571. | 240 5.481 3.767 yes 185 3 no yes no no 2.359 2.362 | 1572. | 217 5.380 3.646 yes 201 1 no no no no 2.374 2.377 | 1573. | 234 5.455 3.668 yes 125 1 no no no no 2.453 2.457 | 1574. | 253 5.533 3.707 yes 125 4 no no no no 2.508 2.512 | +------------------------------------------------------------------------------------------------------+ . . . * leverage and influence diagnostics . * leverage . summ lev ,d Leverage ------------------------------------------------------------- Percentiles Smallest 1% .0016636 .0016636 5% .0018854 .0016636 10% .0020899 .0016636 Obs 1,574 25% .0023828 .0016636 Sum of Wgt. 1,574 50% .0031862 Mean .0063532 Largest Std. Dev. .0083435 75% .007048 .0633344 90% .0124777 .0636456 Variance .0000696 95% .0214789 .0637559 Skewness 3.50352 99% .0444552 .0642237 Kurtosis 17.16434 . di "leverage cutoff: " 2*nparam/nobs leverage cutoff: .01270648 . di "conservative leverage cutoff: " 3*nparam/nobs conservative leverage cutoff: .01905972 . * large leverage values . count if lev>=.01905972 /* many (n=108) high leverage values */ 108 . sort lev . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres lev in -10/-1 +------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres lev | |------------------------------------------------------------------------------------------------------| 1565. | 40 3.689 4.407 yes 263 0 no yes yes yes -1.005 0.046 | 1566. | 23 3.135 4.121 yes 185 0 yes yes no no -1.381 0.050 | 1567. | 99 4.595 4.592 no 294 1 yes yes no no 0.004 0.051 | 1568. | 32 3.466 4.262 yes 201 1 yes yes yes no -1.117 0.052 | 1569. | 110 4.700 4.162 yes 263 0 yes no no yes 0.758 0.058 | |------------------------------------------------------------------------------------------------------| 1570. | 53 3.970 4.227 yes 263 5 yes no no yes -0.362 0.059 | 1571. | 94 4.543 4.865 no 263 3 yes no yes yes -0.454 0.063 | 1572. | 137 4.920 4.994 no 294 2 yes no yes yes -0.105 0.064 | 1573. | 45 3.807 4.577 yes 201 4 yes no yes yes -1.089 0.064 | 1574. | 76 4.331 4.699 no 185 4 yes no yes yes -0.520 0.064 | +------------------------------------------------------------------------------------------------------+ . table twin rp dyst ---------------------------------------- | Dystocia at calving and | Retained placenta at calving Twins | ---- no ---- ---- yes --- born | no yes no yes ----------+----------------------------- no | 1,332 124 76 15 yes | 15 9 2 1 ---------------------------------------- . . * large Cook's D values . summ cook,d Cook's D ------------------------------------------------------------- Percentiles Smallest 1% 8.65e-08 5.57e-10 5% 1.44e-06 5.86e-09 10% 6.87e-06 1.08e-08 Obs 1,574 25% .0000447 1.16e-08 Sum of Wgt. 1,574 50% .000199 Mean .0006351 Largest Std. Dev. .0013679 75% .0006061 .0120243 90% .0014951 .0133958 Variance 1.87e-06 95% .0029054 .0141347 Skewness 5.314337 99% .0068727 .0174304 Kurtosis 42.05991 . di "Cook's D cutoff: " 4/nobs Cook's D cutoff: .0025413 . count if cook>=.0025413 /* many (n=92) high Cook's D values */ 92 . scatter fit cook, xline(0.002 0.008) . sort cook . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres lev cook if cook>0.008 /* most extreme Cook's D va > lues */ +--------------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres lev cook | |--------------------------------------------------------------------------------------------------------------| 1564. | 31 3.434 4.485 no 263 4 no no yes yes -1.463 0.036 0.008 | 1565. | 45 3.807 4.577 yes 201 4 yes no yes yes -1.089 0.064 0.008 | 1566. | 213 5.361 4.254 no 185 0 no no yes yes 1.542 0.036 0.009 | 1567. | 229 5.434 3.925 yes 294 1 no no no yes 2.084 0.021 0.009 | 1568. | 23 3.135 4.121 yes 185 0 yes yes no no -1.381 0.050 0.010 | |--------------------------------------------------------------------------------------------------------------| 1569. | 25 3.219 4.446 no 263 1 no no yes yes -1.708 0.035 0.011 | 1570. | 38 3.638 4.758 no 333 4 yes no no no -1.565 0.043 0.011 | 1571. | 11 2.398 3.881 yes 263 0 no yes no yes -2.056 0.028 0.012 | 1572. | 205 5.323 3.766 no 125 0 no no no yes 2.159 0.028 0.013 | 1573. | 11 2.398 4.031 no 263 1 no yes no yes -2.263 0.027 0.014 | |--------------------------------------------------------------------------------------------------------------| 1574. | 14 2.639 4.121 yes 235 2 yes no no no -2.066 0.039 0.017 | +--------------------------------------------------------------------------------------------------------------+ . scatter cook lev, xline(0.019) yline(0.0025) . . * large DFIT values . summ dfit, d DFITS ------------------------------------------------------------- Percentiles Smallest 1% -.2314434 -.4179343 5% -.1251009 -.3764578 10% -.0824913 -.3471186 Obs 1,574 25% -.0435816 -.3314645 Sum of Wgt. 1,574 50% -.000781 Mean .0003931 Largest Std. Dev. .0797594 75% .0452949 .2795224 90% .0887097 .298769 Variance .0063616 95% .120787 .3084654 Skewness -.1148466 99% .2251135 .3664328 Kurtosis 5.645826 . di "DFITS cutoff: " 2*sqrt(nparam/nobs)*(nobs>=120)+1*(nobs<120) DFITS cutoff: .15941443 . count if abs(dfit)>=.15941443 /* many (n=92) high DFITS values */ 92 . scatter fit dfit, xline(-0.25 -.15 0.15 0.25) . sort dfit . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres lev cook dfit if dfit<-0.25 /* most extreme negativ > e DFITS values */ +-----------------------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres lev cook dfit | |-----------------------------------------------------------------------------------------------------------------------| 1. | 14 2.639 4.121 yes 235 2 yes no no no -2.066 0.039 0.017 -0.418 | 2. | 11 2.398 4.031 no 263 1 no yes no yes -2.263 0.027 0.014 -0.376 | 3. | 11 2.398 3.881 yes 263 0 no yes no yes -2.056 0.028 0.012 -0.347 | 4. | 38 3.638 4.758 no 333 4 yes no no no -1.565 0.043 0.011 -0.331 | 5. | 25 3.219 4.446 no 263 1 no no yes yes -1.708 0.035 0.011 -0.325 | |-----------------------------------------------------------------------------------------------------------------------| 6. | 23 3.135 4.121 yes 185 0 yes yes no no -1.381 0.050 0.010 -0.316 | 7. | 45 3.807 4.577 yes 201 4 yes no yes yes -1.089 0.064 0.008 -0.284 | 8. | 31 3.434 4.485 no 263 4 no no yes yes -1.463 0.036 0.008 -0.283 | 9. | 14 2.639 3.839 no 185 0 no yes no yes -1.663 0.027 0.008 -0.277 | 10. | 32 3.466 4.262 yes 201 1 yes yes yes no -1.117 0.052 0.007 -0.262 | +-----------------------------------------------------------------------------------------------------------------------+ . list wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres lev cook dfit if dfit >0.25 /* most extreme positiv > e DFITS values */ +----------------------------------------------------------------------------------------------------------------------+ | wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres lev cook dfit | |----------------------------------------------------------------------------------------------------------------------| 1565. | 218 5.384 3.728 yes 185 0 no yes no no 2.279 0.012 0.007 0.257 | 1566. | 170 5.136 4.018 no 263 0 no yes no yes 1.549 0.027 0.007 0.257 | 1567. | 205 5.323 4.050 no 294 0 no no no yes 1.759 0.021 0.007 0.258 | 1568. | 253 5.533 3.920 no 201 3 no yes no no 2.221 0.013 0.007 0.259 | 1569. | 149 5.004 3.920 yes 263 3 no yes no yes 1.505 0.030 0.007 0.263 | |----------------------------------------------------------------------------------------------------------------------| 1570. | 240 5.481 3.767 yes 185 3 no yes no no 2.359 0.013 0.008 0.275 | 1571. | 232 5.447 3.795 yes 201 4 no yes no no 2.274 0.015 0.008 0.280 | 1572. | 213 5.361 4.254 no 185 0 no no yes yes 1.542 0.036 0.009 0.299 | 1573. | 229 5.434 3.925 yes 294 1 no no no yes 2.084 0.021 0.009 0.308 | 1574. | 205 5.323 3.766 no 125 0 no no no yes 2.159 0.028 0.013 0.366 | +----------------------------------------------------------------------------------------------------------------------+ . . * dfbeta diagnostics (for a subset of predictors) . di "DFBETA cutoff: " 2/sqrt(nobs)*(nobs>=120)+1*(nobs<120) DFBETA cutoff: .05041127 . sum _dfbeta* Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- _dfbeta_1 | 1,574 -7.55e-06 .0234409 -.0849601 .1193818 _dfbeta_2 | 1,574 9.10e-08 .0239995 -.1043 .1487626 _dfbeta_3 | 1,574 1.26e-06 .0256467 -.1231389 .1197248 _dfbeta_4 | 1,574 7.72e-07 .0253692 -.1311398 .1256247 _dfbeta_5 | 1,574 -7.48e-06 .0227778 -.4061289 .2394238 -------------+--------------------------------------------------------- _dfbeta_6 | 1,574 -.0000162 .0299013 -.2078438 .2472617 _dfbeta_7 | 1,574 4.82e-07 .0254968 -.1650124 .1895015 _dfbeta_8 | 1,574 2.40e-06 .029381 -.2821976 .3064255 _dfbeta_9 | 1,574 -7.50e-06 .0236208 -.2360168 .2135575 . graph box _dfbeta*, yline(-0.05 0.05) . . *you can repeat the next comands for other dbetas . sort _dfbeta_5 . list wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres cook dfit _dfbeta_5 in 1/10 /* most extreme negative dfb > _dyst values */ +--------------------------------------------------------------------------------------------------------------------+ | wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres cook dfit _dfbet~5 | |--------------------------------------------------------------------------------------------------------------------| 1. | 2.639 4.121 yes 235 2 yes no no no -2.066 0.017 -0.418 -0.406 | 2. | 3.638 4.758 no 333 4 yes no no no -1.565 0.011 -0.331 -0.314 | 3. | 3.135 4.121 yes 185 0 yes yes no no -1.381 0.010 -0.316 -0.273 | 4. | 3.466 4.262 yes 201 1 yes yes yes no -1.117 0.007 -0.262 -0.211 | 5. | 3.807 4.577 yes 201 4 yes no yes yes -1.089 0.008 -0.284 -0.187 | |--------------------------------------------------------------------------------------------------------------------| 6. | 4.331 4.699 no 185 4 yes no yes yes -0.520 0.002 -0.136 -0.091 | 7. | 4.043 4.344 yes 294 1 yes no no no -0.420 0.001 -0.086 -0.084 | 8. | 4.543 4.865 no 263 3 yes no yes yes -0.454 0.001 -0.118 -0.080 | 9. | 3.970 4.227 yes 263 5 yes no no yes -0.362 0.001 -0.091 -0.069 | 10. | 4.205 4.456 yes 294 1 yes no yes no -0.352 0.001 -0.076 -0.067 | +--------------------------------------------------------------------------------------------------------------------+ . list wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres cook dfit _dfbeta_5 in -10/-1 /* most extreme positive d > fb_dyst values */ +-------------------------------------------------------------------------------------------------------------------+ | wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres cook dfit _dfbet~5 | |-------------------------------------------------------------------------------------------------------------------| 1565. | 4.554 4.161 yes 185 3 yes no yes no 0.550 0.001 0.119 0.103 | 1566. | 4.663 4.253 yes 263 5 yes no no no 0.572 0.001 0.118 0.111 | 1567. | 4.913 4.494 no 294 2 yes no no no 0.584 0.001 0.119 0.117 | 1568. | 4.644 4.177 yes 201 3 yes no yes no 0.654 0.002 0.141 0.123 | 1569. | 4.700 4.162 yes 263 0 yes no no yes 0.758 0.004 0.187 0.148 | |-------------------------------------------------------------------------------------------------------------------| 1570. | 5.081 4.469 yes 294 2 yes no yes no 0.856 0.003 0.185 0.163 | 1571. | 4.949 4.245 no 235 1 yes no no no 0.983 0.004 0.202 0.197 | 1572. | 4.883 4.077 yes 201 4 yes no no no 1.124 0.005 0.229 0.218 | 1573. | 5.147 4.297 no 235 5 yes no no no 1.188 0.006 0.249 0.233 | 1574. | 5.050 4.188 no 201 2 yes no no no 1.202 0.006 0.246 0.239 | +-------------------------------------------------------------------------------------------------------------------+ . . *analysis without outliers . list wpc wpc_ln fit herd_size parity dyst rp vag_disch if wpc==1 +-----------------------------------------------------------------+ | wpc wpc_ln fit herd_s~e parity dyst rp vag_di~h | |-----------------------------------------------------------------| 1417. | 1 0.000 3.946 263 2 no no no | 1549. | 1 0.000 3.646 201 2 no no no | +-----------------------------------------------------------------+ . list wpc delres lev dfit cook _dfbeta* if wpc==1 /*main issue large residuals and dfit*/ +--------------------------------------------------------------------------------------------------------------------+ 1417. | wpc | delres | lev | dfit | cook | _dfbet~1 | _dfbet~2 | _dfbet~3 | _dfbet~4 | _dfbet~5 | _dfbet~6 | _dfbet~7 | | 1 | -5.449 | 0.002 | -0.243 | 0.006 | 0.023 | 0.117 | 0.063 | 0.126 | 0.005 | 0.044 | 0.053 | |--------------------------------------------------------------------------------------------------------------------| | _dfbet~8 | _dfbet~9 | | 0.042 | -0.026 | +--------------------------------------------------------------------------------------------------------------------+ +--------------------------------------------------------------------------------------------------------------------+ 1549. | wpc | delres | lev | dfit | cook | _dfbet~1 | _dfbet~2 | _dfbet~3 | _dfbet~4 | _dfbet~5 | _dfbet~6 | _dfbet~7 | | 1 | -5.028 | 0.002 | -0.243 | 0.006 | 0.119 | 0.085 | 0.069 | -0.131 | 0.018 | 0.051 | 0.037 | |--------------------------------------------------------------------------------------------------------------------| | _dfbet~8 | _dfbet~9 | | 0.028 | -0.021 | +--------------------------------------------------------------------------------------------------------------------+ . . *original final model . reg wpc_ln hs100_ctr hs100_ctr_sq parity1 aut_calv twin dyst rp##vag_disch Source | SS df MS Number of obs = 1,574 -------------+---------------------------------- F(9, 1564) = 18.05 Model | 86.9474063 9 9.66082293 Prob > F = 0.0000 Residual | 836.874538 1,564 .535086022 R-squared = 0.0941 -------------+---------------------------------- Adj R-squared = 0.0889 Total | 923.821945 1,573 .587299393 Root MSE = .7315 ------------------------------------------------------------------------------ wpc_ln | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- hs100_ctr | .343658 .0317233 10.83 0.000 .2814333 .4058827 hs100_ctr_sq | .2118728 .0456207 4.64 0.000 .1223885 .301357 parity1 | .0129844 .012586 1.03 0.302 -.0117028 .0376715 aut_calv | -.1371621 .0372127 -3.69 0.000 -.2101542 -.0641701 twin | .3927426 .1443661 2.72 0.007 .1095711 .6759141 dyst | .1109405 .0801013 1.39 0.166 -.0461768 .2680578 | rp | yes | .1123166 .0705612 1.59 0.112 -.0260878 .250721 | vag_disch | yes | -.0260135 .1050122 -0.25 0.804 -.231993 .1799661 | rp#vag_disch | yes#yes | .4136999 .183531 2.25 0.024 .0537072 .7736926 | _cons | 3.888587 .0386257 100.67 0.000 3.812823 3.96435 ------------------------------------------------------------------------------ . estimate store ln . . *re-fit without outliers/influential obs . reg wpc_ln hs100_ctr hs100_ctr_sq parity1 aut_calv twin dyst rp##vag_disch if wpc~=1 Source | SS df MS Number of obs = 1,572 -------------+---------------------------------- F(9, 1562) = 18.15 Model | 84.5110938 9 9.39012153 Prob > F = 0.0000 Residual | 807.934865 1,562 .517243831 R-squared = 0.0947 -------------+---------------------------------- Adj R-squared = 0.0895 Total | 892.445959 1,571 .568075085 Root MSE = .7192 ------------------------------------------------------------------------------ wpc_ln | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- hs100_ctr | .3391632 .031199 10.87 0.000 .2779669 .4003596 hs100_ctr_sq | .2026965 .0448706 4.52 0.000 .1146836 .2907094 parity1 | .0113333 .0123763 0.92 0.360 -.0129427 .0356093 aut_calv | -.1369515 .0366092 -3.74 0.000 -.2087598 -.0651432 twin | .3894441 .1419397 2.74 0.006 .1110316 .6678566 dyst | .1033889 .0787611 1.31 0.189 -.0510998 .2578777 | rp | yes | .1060341 .0693799 1.53 0.127 -.0300535 .2421216 | vag_disch | yes | -.0332815 .1032512 -0.32 0.747 -.2358071 .1692441 | rp#vag_disch | yes#yes | .4223009 .1804488 2.34 0.019 .0683535 .7762484 | _cons | 3.901024 .0380169 102.61 0.000 3.826455 3.975594 ------------------------------------------------------------------------------ . estimate store ln_noout . estat hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of wpc_ln chi2(1) = 16.22 Prob > chi2 = 0.0001 . estat imtest Cameron & Trivedi's decomposition of IM-test --------------------------------------------------- Source | chi2 df p ---------------------+----------------------------- Heteroskedasticity | 71.76 44 0.0051 Skewness | 14.82 9 0.0960 Kurtosis | 9.69 1 0.0019 ---------------------+----------------------------- Total | 96.27 54 0.0004 --------------------------------------------------- . . drop fit - dfit . drop _dfbeta* . capture drop fit_group . . predict fit if e(sample), xb (2 missing values generated) . predict stdres if e(sample), rstandard (2 missing values generated) . predict delres if e(sample), rstudent (2 missing values generated) . predict dfit if e(sample), dfit (2 missing values generated) . predict cook if e(sample), cook (2 missing values generated) . scalar nobs=1572 . scalar nparam=10 . . ** formatting several variables at once to show only 3 decimals - advanced command - ignore for now . foreach var in fit stdres delres cook dfit { 2. format `var' %5.3f 3. } . hist stdres (bin=31, start=-3.6900551, width=.20143648) . egen fit_group=cut(fit), group(10) (2 missing values generated) . tabstat stdres, statistics( mean sd count ) by(fit_group) Summary for variables: stdres by categories of: fit_group fit_group | mean sd N ----------+------------------------------ 0 | -.0798362 .9912713 151 1 | -.0052168 1.078422 158 2 | .0429111 1.119622 160 3 | -.0532808 1.040071 125 4 | .0708433 1.016679 191 5 | .078308 .9893025 153 6 | -.0311166 1.100208 133 7 | -.0623551 .9994817 185 8 | .0161114 .8454157 138 9 | .0035924 .8149584 178 ----------+------------------------------ Total | .0000171 1.000335 1572 ----------------------------------------- . sort delres . list cow wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres cook dfit in 1/10 +------------------------------------------------------------------------------------------------------------------------------+ | cow wpc wpc_ln fit aut_calv herd_s~e parity1 twin dyst rp vag_di~h stdres delres cook dfit | |------------------------------------------------------------------------------------------------------------------------------| 1. | 403 3 1.099 3.749 yes 235 3 no no no no -3.690 -3.705 0.004 -0.190 | 2. | 983 4 1.386 3.816 no 201 3 no no no no -3.383 -3.394 0.003 -0.176 | 3. | 1062 4 1.386 3.645 yes 201 0 no no no no -3.146 -3.155 0.003 -0.176 | 4. | 1130 5 1.609 3.827 no 201 4 no no no no -3.090 -3.098 0.004 -0.191 | 5. | 1049 5 1.609 3.782 no 201 0 no no no no -3.025 -3.033 0.003 -0.165 | |------------------------------------------------------------------------------------------------------------------------------| 6. | 2281 7 1.946 3.945 no 263 0 no no no no -2.783 -2.789 0.002 -0.145 | 7. | 5006 7 1.946 3.777 no 185 1 no no no no -2.549 -2.553 0.002 -0.125 | 8. | 4 9 2.197 3.993 yes 294 4 no no no no -2.501 -2.505 0.002 -0.142 | 9. | 249 10 2.303 4.096 no 294 1 no no no no -2.495 -2.500 0.001 -0.106 | 10. | 157 9 2.197 3.970 yes 294 2 no no no no -2.467 -2.471 0.001 -0.107 | +------------------------------------------------------------------------------------------------------------------------------+ . * outlier test based on deletion residuals . summ delres, d Studentized residuals ------------------------------------------------------------- Percentiles Smallest 1% -2.146736 -3.705058 5% -1.581073 -3.394443 10% -1.259347 -3.154713 Obs 1,572 25% -.7280966 -3.098353 Sum of Wgt. 1,572 50% -.0183825 Mean .0000118 Largest Std. Dev. 1.000858 75% .7256545 2.402748 90% 1.349921 2.404035 Variance 1.001716 95% 1.645225 2.495872 Skewness -.0172075 99% 2.184024 2.559009 Kurtosis 2.632243 . display invttail(nobs-nparam-1,.025/nobs) /* values >= abs(4.17) outliers*/ 4.1723589 . count if abs(delres) & delres!=. >=4.17 0 . . sort dfit . list cow wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres cook dfit in 1/10 +----------------------------------------------------------------------------------------------------------------------+ 1. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 444 | 14 | 2.639 | 4.127 | yes | 235 | 2 | yes | no | no | no | -2.111 | -2.113 | 0.018 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.427 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 2. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2498 | 11 | 2.398 | 4.026 | no | 263 | 1 | no | yes | no | yes | -2.295 | -2.298 | 0.015 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.382 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 3. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2307 | 11 | 2.398 | 3.878 | yes | 263 | 0 | no | yes | no | yes | -2.087 | -2.089 | 0.012 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.352 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 4. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 713 | 38 | 3.638 | 4.750 | no | 333 | 4 | yes | no | no | no | -1.581 | -1.582 | 0.011 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.335 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 5. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2480 | 25 | 3.219 | 4.451 | no | 263 | 1 | no | no | yes | yes | -1.744 | -1.745 | 0.011 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.332 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 6. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 5029 | 23 | 3.135 | 4.121 | yes | 185 | 0 | yes | yes | no | no | -1.406 | -1.407 | 0.010 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.322 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 7. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2394 | 31 | 3.434 | 4.485 | no | 263 | 4 | no | no | yes | yes | -1.489 | -1.489 | 0.008 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.288 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 8. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 1122 | 45 | 3.807 | 4.575 | yes | 201 | 4 | yes | no | yes | yes | -1.104 | -1.104 | 0.008 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.288 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 9. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 5015 | 14 | 2.639 | 3.836 | no | 185 | 0 | no | yes | no | yes | -1.687 | -1.688 | 0.008 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.281 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 10. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 1036 | 32 | 3.466 | 4.255 | yes | 201 | 1 | yes | yes | yes | no | -1.128 | -1.128 | 0.007 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.265 | +----------------------------------------------------------------------------------------------------------------------+ . sort cook . list cow wpc wpc_ln fit aut_calv herd_size parity1 twin dyst rp vag_disch stdres delres cook dfit in -10/-1 +----------------------------------------------------------------------------------------------------------------------+ 1565. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 238 | 229 | 5.434 | 3.925 | yes | 294 | 1 | no | no | no | yes | 2.120 | 2.122 | 0.010 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | 0.314 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1566. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 5029 | 23 | 3.135 | 4.121 | yes | 185 | 0 | yes | yes | no | no | -1.406 | -1.407 | 0.010 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.322 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1567. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2480 | 25 | 3.219 | 4.451 | no | 263 | 1 | no | no | yes | yes | -1.744 | -1.745 | 0.011 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.332 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1568. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 713 | 38 | 3.638 | 4.750 | no | 333 | 4 | yes | no | no | no | -1.581 | -1.582 | 0.011 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.335 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1569. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2307 | 11 | 2.398 | 3.878 | yes | 263 | 0 | no | yes | no | yes | -2.087 | -2.089 | 0.012 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.352 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1570. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 1238 | 205 | 5.323 | 3.762 | no | 125 | 0 | no | no | no | yes | 2.201 | 2.204 | 0.014 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | 0.374 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1571. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2498 | 11 | 2.398 | 4.026 | no | 263 | 1 | no | yes | no | yes | -2.295 | -2.298 | 0.015 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.382 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1572. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 444 | 14 | 2.639 | 4.127 | yes | 235 | 2 | yes | no | no | no | -2.111 | -2.113 | 0.018 | |----------------------------------------------------------------------------------------------------------------------| | dfit | | -0.427 | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1573. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 2272 | 1 | 0.000 | . | no | 263 | 1 | no | no | no | no | . | . | . | |----------------------------------------------------------------------------------------------------------------------| | dfit | | . | +----------------------------------------------------------------------------------------------------------------------+ +----------------------------------------------------------------------------------------------------------------------+ 1574. | cow | wpc | wpc_ln | fit | aut_calv | herd_s~e | parity1 | twin | dyst | rp | vag_di~h | stdres | delres | cook | | 1032 | 1 | 0.000 | . | yes | 201 | 1 | no | no | no | no | . | . | . | |----------------------------------------------------------------------------------------------------------------------| | dfit | | . | +----------------------------------------------------------------------------------------------------------------------+ . *the two outliers don't have the highest infl. values . . estimate table ln ln_noout, //models are very similar since outliers did not have much influence ---------------------------------------- Variable | ln ln_noout -------------+-------------------------- hs100_ctr | .34365799 .33916323 hs100_ctr_sq | .21187276 .20269649 parity1 | .01298436 .0113333 aut_calv | -.13716214 -.13695147 twin | .39274261 .3894441 dyst | .1109405 .10338895 | rp | yes | .11231661 .10603408 | vag_disch | yes | -.02601346 -.03328151 | rp#vag_disch | yes#yes | .41369992 .42230092 | _cons | 3.8885867 3.9010244 ---------------------------------------- . estimate table ln ln_noout, se //now with SE's ---------------------------------------- Variable | ln ln_noout -------------+-------------------------- hs100_ctr | .34365799 .33916323 | .03172331 .031199 hs100_ctr_sq | .21187276 .20269649 | .04562075 .04487057 parity1 | .01298436 .0113333 | .01258597 .01237635 aut_calv | -.13716214 -.13695147 | .0372127 .03660917 twin | .39274261 .3894441 | .14436609 .14193974 dyst | .1109405 .10338895 | .08010133 .07876115 | rp | yes | .11231661 .10603408 | .07056115 .0693799 | vag_disch | yes | -.02601346 -.03328151 | .10501221 .10325122 | rp#vag_disch | yes#yes | .41369992 .42230092 | .18353098 .18044883 | _cons | 3.8885867 3.9010244 | .03862574 .03801689 ---------------------------------------- legend: b/se . end of do-file . log close name: log: C:\vhm812-data\l2b_linear_reg_diag.txt log type: text closed on: 19 Jan 2021, 09:29:44 -------------------------------------------------------------------------------------------------------------------------------------