------------------------------------------------------------------------------- log: C:\~SLJF\makeverifyfiles\spostverify\done\fitstatverify.log log type: text opened on: 25 Mar 2001, 14:22:52 . * fitstat: version 1.6.3 12/12/00 . * verified: 2/22/01 . which fitstat c:\stata\ado\stbplus\f\fitstat.ado *! version 1.6.6 3/10/01 fix dif/diff bug . . * compute fit statistics for a single model and look at r() results . use binlfp2, clear (PSID 1976 / T Mroz) . logit lfp k5 k618 age wc hc lwg inc, nolog Logit estimates Number of obs = 753 LR chi2(7) = 124.48 Prob > chi2 = 0.0000 Log likelihood = -452.63296 Pseudo R2 = 0.1209 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.462913 .1970006 -7.43 0.000 -1.849027 -1.076799 k618 | -.0645707 .0680008 -0.95 0.342 -.1978499 .0687085 age | -.0628706 .0127831 -4.92 0.000 -.0879249 -.0378162 wc | .8072738 .2299799 3.51 0.000 .3565215 1.258026 hc | .1117336 .2060397 0.54 0.588 -.2920969 .515564 lwg | .6046931 .1508176 4.01 0.000 .3090961 .9002901 inc | -.0344464 .0082084 -4.20 0.000 -.0505346 -.0183583 _cons | 3.18214 .6443751 4.94 0.000 1.919188 4.445092 ------------------------------------------------------------------------------ . fitstat Measures of Fit for logit of lfp Log-Lik Intercept Only: -514.873 Log-Lik Full Model: -452.633 D(745): 905.266 LR(7): 124.480 Prob > LR: 0.000 McFadden's R2: 0.121 McFadden's Adj R2: 0.105 Maximum Likelihood R2: 0.152 Cragg & Uhler's R2: 0.204 McKelvey and Zavoina's R2: 0.217 Efron's R2: 0.155 Variance of y*: 4.203 Variance of error: 3.290 Count R2: 0.693 Adj Count R2: 0.289 AIC: 1.223 AIC*n: 921.266 BIC: -4029.663 BIC': -78.112 . di "AIC: " r(aic) AIC: 1.2234607 . di "AIC*N: " r(aic_n) AIC*N: 921.26592 . di "BIC: " r(bic) BIC: -4029.6627 . di "BIC': " r(bic_p) BIC': -78.112037 . di "deviance: " r(dev) deviance: 905.26592 . di "df deviance: " r(dev_df) df deviance: 745 . di "ll full model: " r(ll) ll full model: -452.63296 . di "ll intercept: " r(ll_0) ll intercept: -514.8732 . di "lr chi-square: " r(lrx2) lr chi-square: 124.48049 . di " df: " r(lrx2_df) df: 7 . di " prob: : " r(lrx2_p) prob: : 8.923e-24 . di "# of obs: " r(N) # of obs: 753 . di "# of parameters: " r(n_parm) # of parameters: 8 . di "# of rhs variables: " r(n_rhs) # of rhs variables: 7 . di "R^2 for LRM: " r(r2) R^2 for LRM: . . di "adjusted R^2 for LRM: " r(r2_adj) adjusted R^2 for LRM: . . di "count R^2: " r(r2_ct) count R^2: .69322709 . di "adjusted count R^2: " r(r2_ctadj) adjusted count R^2: .28923077 . di "Cragg & Uhler's R^2: " r(r2_cu) Cragg & Uhler's R^2: .20445312 . di "Efron's R^2: " r(r2_ef) Efron's R^2: .15493519 . di "M & Z's R^2: " r(r2_mz) M & Z's R^2: .2171939 . di "McFadden's R^2: " r(r2_mf) McFadden's R^2: .12088461 . di "McFadden's adj R^2: " r(r2_mfadj) McFadden's adj R^2: .1053468 . di "maximum likelihood R^2: " r(r2_ml) maximum likelihood R^2: .15237143 . di "variance of error term: " r(v_error) variance of error term: 3.2898681 . di "variance of y*: " r(v_ystar) variance of y*: 4.2026603 . . * compute fit statistics for a single model and save fit measures . logit lfp k5 k618 age wc hc lwg inc, nolog Logit estimates Number of obs = 753 LR chi2(7) = 124.48 Prob > chi2 = 0.0000 Log likelihood = -452.63296 Pseudo R2 = 0.1209 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.462913 .1970006 -7.43 0.000 -1.849027 -1.076799 k618 | -.0645707 .0680008 -0.95 0.342 -.1978499 .0687085 age | -.0628706 .0127831 -4.92 0.000 -.0879249 -.0378162 wc | .8072738 .2299799 3.51 0.000 .3565215 1.258026 hc | .1117336 .2060397 0.54 0.588 -.2920969 .515564 lwg | .6046931 .1508176 4.01 0.000 .3090961 .9002901 inc | -.0344464 .0082084 -4.20 0.000 -.0505346 -.0183583 _cons | 3.18214 .6443751 4.94 0.000 1.919188 4.445092 ------------------------------------------------------------------------------ . fitstat, saving(mod1) Measures of Fit for logit of lfp Log-Lik Intercept Only: -514.873 Log-Lik Full Model: -452.633 D(745): 905.266 LR(7): 124.480 Prob > LR: 0.000 McFadden's R2: 0.121 McFadden's Adj R2: 0.105 Maximum Likelihood R2: 0.152 Cragg & Uhler's R2: 0.204 McKelvey and Zavoina's R2: 0.217 Efron's R2: 0.155 Variance of y*: 4.203 Variance of error: 3.290 Count R2: 0.693 Adj Count R2: 0.289 AIC: 1.223 AIC*n: 921.266 BIC: -4029.663 BIC': -78.112 (Indices saved in matrix fs_mod1) . mat list fs_mod1 fs_mod1[1,26] N ll_0 ll dev dev_df lrx2 logit 753 -514.8732 -452.63296 905.26592 745 124.48049 lrx2_df lrx2_p r2_mf r2_mfadj r2_ml r2_cu logit 7 8.923e-24 .12088461 .1053468 .15237143 .20445312 r2_mz r2_ef v_ystar v_error r2_ct r2_ctadj logit .2171939 .15493519 4.2026603 3.2898681 .69322709 .28923077 r2 r2_adj aic aic_n bic bic_p logit -9999 -9999 1.2234607 921.26592 -4029.6627 -78.112037 n_parm n_rhs logit 8 7 . . * compare saved model to current model . gen age2 = age*age . logit lfp k5 age age2 wc inc, nolog Logit estimates Number of obs = 753 LR chi2(5) = 106.44 Prob > chi2 = 0.0000 Log likelihood = -461.65276 Pseudo R2 = 0.1034 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.379839 .1954677 -7.06 0.000 -1.762949 -.9967297 age | .0568824 .11411 0.50 0.618 -.166769 .2805339 age2 | -.0012928 .001294 -1.00 0.318 -.0038291 .0012434 wc | 1.093673 .1987386 5.50 0.000 .7041522 1.483193 inc | -.0323176 .0077281 -4.18 0.000 -.0474645 -.0171707 _cons | .9791676 2.458098 0.40 0.690 -3.838616 5.796951 ------------------------------------------------------------------------------ . fitstat, using(mod1) saving(mod2) Measures of Fit for logit of lfp Current Saved Difference Model: logit logit N: 753 753 0 Log-Lik Intercept Only: -514.873 -514.873 0.000 Log-Lik Full Model: -461.653 -452.633 -9.020 D: 923.306(747) 905.266(745) 18.040(2) LR: 106.441(5) 124.480(7) -18.040(-2) Prob > LR: 0.000 0.000 0.000 McFadden's R2: 0.103 0.121 -0.018 McFadden's Adj R2: 0.092 0.105 -0.014 Maximum Likelihood R2: 0.132 0.152 -0.021 Cragg & Uhler's R2: 0.177 0.204 -0.028 McKelvey and Zavoina's R2: 0.182 0.217 -0.035 Efron's R2: 0.135 0.155 -0.020 Variance of y*: 4.023 4.203 -0.180 Variance of error: 3.290 3.290 0.000 Count R2: 0.677 0.693 -0.016 Adj Count R2: 0.252 0.289 -0.037 AIC: 1.242 1.223 0.019 AIC*n: 935.306 921.266 14.040 BIC: -4024.871 -4029.663 4.791 BIC': -73.321 -78.112 4.791 Difference of 4.791 in BIC' provides positive support for saved model. (Indices saved in matrix fs_mod2) . mat list fs_mod2 fs_mod2[1,26] N ll_0 ll dev dev_df lrx2 logit 753 -514.8732 -461.65276 923.30552 747 106.44089 lrx2_df lrx2_p r2_mf r2_mfadj r2_ml r2_cu logit 5 2.314e-21 .10336612 .09171276 .13181961 .17687654 r2_mz r2_ef v_ystar v_error r2_ct r2_ctadj logit .18219232 .13522126 4.0227895 3.2898681 .67729084 .25230769 r2 r2_adj aic aic_n bic bic_p logit -9999 -9999 1.2421056 935.30552 -4024.8712 -73.32056 n_parm n_rhs logit 6 5 . . * compare models with bic statistics . logit lfp k5 age age2 wc inc, nolog Logit estimates Number of obs = 753 LR chi2(5) = 106.44 Prob > chi2 = 0.0000 Log likelihood = -461.65276 Pseudo R2 = 0.1034 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.379839 .1954677 -7.06 0.000 -1.762949 -.9967297 age | .0568824 .11411 0.50 0.618 -.166769 .2805339 age2 | -.0012928 .001294 -1.00 0.318 -.0038291 .0012434 wc | 1.093673 .1987386 5.50 0.000 .7041522 1.483193 inc | -.0323176 .0077281 -4.18 0.000 -.0474645 -.0171707 _cons | .9791676 2.458098 0.40 0.690 -3.838616 5.796951 ------------------------------------------------------------------------------ . fitstat, using(mod1) bic Current Saved Difference Model: logit logit N: 753 753 0 AIC: 1.242 1.223 0.019 AIC*n: 935.306 921.266 14.040 BIC: -4024.871 -4029.663 4.791 BIC': -73.321 -78.112 4.791 Difference of 4.791 in BIC' provides positive support for saved model. . . * use force to compare different types of models . logit lfp k5 k618 age wc hc lwg inc, nolog Logit estimates Number of obs = 753 LR chi2(7) = 124.48 Prob > chi2 = 0.0000 Log likelihood = -452.63296 Pseudo R2 = 0.1209 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.462913 .1970006 -7.43 0.000 -1.849027 -1.076799 k618 | -.0645707 .0680008 -0.95 0.342 -.1978499 .0687085 age | -.0628706 .0127831 -4.92 0.000 -.0879249 -.0378162 wc | .8072738 .2299799 3.51 0.000 .3565215 1.258026 hc | .1117336 .2060397 0.54 0.588 -.2920969 .515564 lwg | .6046931 .1508176 4.01 0.000 .3090961 .9002901 inc | -.0344464 .0082084 -4.20 0.000 -.0505346 -.0183583 _cons | 3.18214 .6443751 4.94 0.000 1.919188 4.445092 ------------------------------------------------------------------------------ . fitstat, saving(mod1) Measures of Fit for logit of lfp Log-Lik Intercept Only: -514.873 Log-Lik Full Model: -452.633 D(745): 905.266 LR(7): 124.480 Prob > LR: 0.000 McFadden's R2: 0.121 McFadden's Adj R2: 0.105 Maximum Likelihood R2: 0.152 Cragg & Uhler's R2: 0.204 McKelvey and Zavoina's R2: 0.217 Efron's R2: 0.155 Variance of y*: 4.203 Variance of error: 3.290 Count R2: 0.693 Adj Count R2: 0.289 AIC: 1.223 AIC*n: 921.266 BIC: -4029.663 BIC': -78.112 (Indices saved in matrix fs_mod1) . probit lfp k5 age age2 wc inc, nolog Probit estimates Number of obs = 753 LR chi2(5) = 106.14 Prob > chi2 = 0.0000 Log likelihood = -461.80378 Pseudo R2 = 0.1031 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -.8328657 .1141048 -7.30 0.000 -1.056507 -.6092244 age | .0386768 .0692493 0.56 0.576 -.0970494 .1744031 age2 | -.0008304 .0007871 -1.05 0.291 -.0023731 .0007123 wc | .6560069 .1172043 5.60 0.000 .4262908 .885723 inc | -.019542 .0045326 -4.31 0.000 -.0284257 -.0106583 _cons | .504902 1.486525 0.34 0.734 -2.408634 3.418438 ------------------------------------------------------------------------------ . fitstat, using(mod1) saving(mod2) force Measures of Fit for probit of lfp Warning: Current model estimated by probit, but saved model estimated by logit Current Saved Difference Model: probit logit N: 753 753 0 Log-Lik Intercept Only: -514.873 -514.873 0.000 Log-Lik Full Model: -461.804 -452.633 -9.171 D: 923.608(747) 905.266(745) 18.342(2) LR: 106.139(5) 124.480(7) -18.342(-2) Prob > LR: 0.000 0.000 0.000 McFadden's R2: 0.103 0.121 -0.018 McFadden's Adj R2: 0.091 0.105 -0.014 Maximum Likelihood R2: 0.131 0.152 -0.021 Cragg & Uhler's R2: 0.176 0.204 -0.028 McKelvey and Zavoina's R2: 0.211 0.217 -0.006 Efron's R2: 0.135 0.155 -0.020 Variance of y*: 1.267 4.203 -2.936 Variance of error: 1.000 3.290 -2.290 Count R2: 0.679 0.693 -0.015 Adj Count R2: 0.255 0.289 -0.034 AIC: 1.243 1.223 0.019 AIC*n: 935.608 921.266 14.342 BIC: -4024.569 -4029.663 5.094 BIC': -73.019 -78.112 5.094 Difference of 5.094 in BIC' provides positive support for saved model. (Indices saved in matrix fs_mod2) . . * use force to compare different N's . logit lfp k5 k618 age wc hc lwg inc, nolog Logit estimates Number of obs = 753 LR chi2(7) = 124.48 Prob > chi2 = 0.0000 Log likelihood = -452.63296 Pseudo R2 = 0.1209 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.462913 .1970006 -7.43 0.000 -1.849027 -1.076799 k618 | -.0645707 .0680008 -0.95 0.342 -.1978499 .0687085 age | -.0628706 .0127831 -4.92 0.000 -.0879249 -.0378162 wc | .8072738 .2299799 3.51 0.000 .3565215 1.258026 hc | .1117336 .2060397 0.54 0.588 -.2920969 .515564 lwg | .6046931 .1508176 4.01 0.000 .3090961 .9002901 inc | -.0344464 .0082084 -4.20 0.000 -.0505346 -.0183583 _cons | 3.18214 .6443751 4.94 0.000 1.919188 4.445092 ------------------------------------------------------------------------------ . fitstat, saving(mod1) Measures of Fit for logit of lfp Log-Lik Intercept Only: -514.873 Log-Lik Full Model: -452.633 D(745): 905.266 LR(7): 124.480 Prob > LR: 0.000 McFadden's R2: 0.121 McFadden's Adj R2: 0.105 Maximum Likelihood R2: 0.152 Cragg & Uhler's R2: 0.204 McKelvey and Zavoina's R2: 0.217 Efron's R2: 0.155 Variance of y*: 4.203 Variance of error: 3.290 Count R2: 0.693 Adj Count R2: 0.289 AIC: 1.223 AIC*n: 921.266 BIC: -4029.663 BIC': -78.112 (Indices saved in matrix fs_mod1) . logit lfp k5 age age2 wc inc if k5<3, nolog Logit estimates Number of obs = 750 LR chi2(5) = 101.73 Prob > chi2 = 0.0000 Log likelihood = -461.48131 Pseudo R2 = 0.0993 ------------------------------------------------------------------------------ lfp | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- k5 | -1.364425 .1981586 -6.89 0.000 -1.752809 -.9760414 age | .0590581 .1142023 0.52 0.605 -.1647742 .2828905 age2 | -.0013144 .0012949 -1.02 0.310 -.0038524 .0012236 wc | 1.095142 .198722 5.51 0.000 .7056536 1.484629 inc | -.0322525 .0077429 -4.17 0.000 -.0474283 -.0170766 _cons | .9228921 2.460473 0.38 0.708 -3.899547 5.745331 ------------------------------------------------------------------------------ . fitstat, using(mod1) saving(mod2) force Measures of Fit for logit of lfp Warning: N's do not match. Current Saved Difference Model: logit logit N: 750 753 -3 Log-Lik Intercept Only: -512.345 -514.873 2.529 Log-Lik Full Model: -461.481 -452.633 -8.848 D: 922.963(744) 905.266(745) 17.697(-1) LR: 101.727(5) 124.480(7) -22.754(-2) Prob > LR: 0.000 0.000 0.000 McFadden's R2: 0.099 0.121 -0.022 McFadden's Adj R2: 0.088 0.105 -0.018 Maximum Likelihood R2: 0.127 0.152 -0.026 Cragg & Uhler's R2: 0.170 0.204 -0.034 McKelvey and Zavoina's R2: 0.171 0.217 -0.046 Efron's R2: 0.131 0.155 -0.024 Variance of y*: 3.970 4.203 -0.233 Variance of error: 3.290 3.290 0.000 Count R2: 0.677 0.693 -0.016 Adj Count R2: 0.248 0.289 -0.041 AIC: 1.247 1.223 0.023 AIC*n: 934.963 921.266 13.697 BIC: -4002.372 -4029.663 27.291 BIC': -68.626 -78.112 9.486 (Indices saved in matrix fs_mod2) . . log close log: C:\~SLJF\makeverifyfiles\spostverify\done\fitstatverify.log log type: text closed on: 25 Mar 2001, 14:22:53 -------------------------------------------------------------------------------