Loading packages
library(psych)
library(lm.beta)Loading Data
library(haven)
Teacher_Cost <- read_sav("~/Dropbox/Teacher Cost Project/Data/Teacher_Cost_3_15_19.sav")Making variables
Teacher_Cost$years <- ifelse(Teacher_Cost$Yrs_Exp == 1, 1, 0)
Teacher_Cost$urban <- ifelse(Teacher_Cost$Urban_vs_NonUrban == 1, 1, 0)
Teacher_Cost$high_school <- ifelse(Teacher_Cost$HS_vs_Younger == 1, 1, 0)
Teacher_Cost$years <- ifelse(Teacher_Cost$years_teaching > 4.5, 1, 0)Regressions predicting teaching satisfaction
M1 <- lm(teach_satisfaction ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_te_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_te_overall*years,
data = Teacher_Cost)
summary(M1)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_te_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How satisfied are you with your choice to become a teacher?
## Min 1Q Median 3Q Max
## -3.3950 -0.3111 0.1326 0.5424 1.9056
##
## Labels:
## value label
## 1 Not at all satisfied
## 2 Unsatisfied
## 3 Somewhat unsatisfied
## 4 Neither satisfied or unsatisfied
## 5 Somewhat satisfied
## 6 Satisfied
## 7 Extremely satisfied
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.505167 0.895944 1.680 0.09506 .
## years -0.125877 0.170988 -0.736 0.46278
## male 0.061522 0.216702 0.284 0.77688
## urban 0.070953 0.169566 0.418 0.67623
## high_school 0.138040 0.226746 0.609 0.54359
## Value 0.864817 0.133779 6.465 1.37e-09 ***
## eff_is_overall -0.289661 0.121187 -2.390 0.01809 *
## eff_cm_overall 0.005458 0.093685 0.058 0.95362
## eff_se_overall 0.260606 0.119720 2.177 0.03107 *
## cost_te_overall -0.187663 0.062009 -3.026 0.00292 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9883 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.4082, Adjusted R-squared: 0.3725
## F-statistic: 11.42 on 9 and 149 DF, p-value: 1.676e-13lm.beta(M1)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_te_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 -0.05007398 0.01910255 0.02689361 0.04227762
## Value eff_is_overall eff_cm_overall eff_se_overall cost_te_overall
## 0.49594667 -0.19804601 0.00499837 0.20712110 -0.20507820M2 <- lm(teach_satisfaction ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_oe_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_oe_overall*years,
data = Teacher_Cost)
summary(M2)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_oe_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How satisfied are you with your choice to become a teacher?
## Min 1Q Median 3Q Max
## -3.5326 -0.3572 0.1287 0.5731 1.8740
##
## Labels:
## value label
## 1 Not at all satisfied
## 2 Unsatisfied
## 3 Somewhat unsatisfied
## 4 Neither satisfied or unsatisfied
## 5 Somewhat satisfied
## 6 Satisfied
## 7 Extremely satisfied
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.46098 0.90629 1.612 0.10907
## years -0.06855 0.17113 -0.401 0.68932
## male 0.14232 0.21400 0.665 0.50704
## urban 0.06316 0.17023 0.371 0.71117
## high_school 0.14605 0.22826 0.640 0.52324
## Value 0.84945 0.13500 6.292 3.3e-09 ***
## eff_is_overall -0.32837 0.12112 -2.711 0.00749 **
## eff_cm_overall 0.00926 0.09405 0.098 0.92170
## eff_se_overall 0.27447 0.11989 2.289 0.02346 *
## cost_oe_overall -0.18248 0.06547 -2.787 0.00601 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9927 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.403, Adjusted R-squared: 0.3669
## F-statistic: 11.18 on 9 and 149 DF, p-value: 3.096e-13lm.beta(M2)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_oe_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.000000000 -0.027267893 0.044190393 0.023938217 0.044731547
## Value eff_is_overall eff_cm_overall eff_se_overall cost_oe_overall
## 0.487136669 -0.224511251 0.008480024 0.218141632 -0.190343310M3 <- lm(teach_satisfaction ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_lv_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_lv_overall*years,
data = Teacher_Cost)
summary(M3)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_lv_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How satisfied are you with your choice to become a teacher?
## Min 1Q Median 3Q Max
## -3.3277 -0.3881 0.1720 0.5847 2.0420
##
## Labels:
## value label
## 1 Not at all satisfied
## 2 Unsatisfied
## 3 Somewhat unsatisfied
## 4 Neither satisfied or unsatisfied
## 5 Somewhat satisfied
## 6 Satisfied
## 7 Extremely satisfied
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.58106 0.88661 1.783 0.07658 .
## years -0.08865 0.16931 -0.524 0.60133
## male 0.10024 0.21284 0.471 0.63836
## urban 0.02115 0.16855 0.125 0.90032
## high_school 0.09716 0.22443 0.433 0.66570
## Value 0.83920 0.13366 6.279 3.54e-09 ***
## eff_is_overall -0.30205 0.12007 -2.516 0.01294 *
## eff_cm_overall 0.01563 0.09272 0.169 0.86638
## eff_se_overall 0.27496 0.11853 2.320 0.02172 *
## cost_lv_overall -0.19324 0.05803 -3.330 0.00109 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9823 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.4154, Adjusted R-squared: 0.3801
## F-statistic: 11.76 on 9 and 149 DF, p-value: 7.195e-14lm.beta(M3)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_lv_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.000000000 -0.035265533 0.031123088 0.008015913 0.029757170
## Value eff_is_overall eff_cm_overall eff_se_overall cost_lv_overall
## 0.481254057 -0.206519261 0.014310775 0.218526000 -0.217583939M4 <- lm(teach_satisfaction ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_em_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_em_overall*years,
data = Teacher_Cost)
summary(M4)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_em_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How satisfied are you with your choice to become a teacher?
## Min 1Q Median 3Q Max
## -3.4638 -0.3585 0.1104 0.6176 2.0388
##
## Labels:
## value label
## 1 Not at all satisfied
## 2 Unsatisfied
## 3 Somewhat unsatisfied
## 4 Neither satisfied or unsatisfied
## 5 Somewhat satisfied
## 6 Satisfied
## 7 Extremely satisfied
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.21936 0.95910 1.271 0.2056
## years -0.11229 0.17459 -0.643 0.5211
## male 0.12411 0.21993 0.564 0.5734
## urban 0.03610 0.17283 0.209 0.8348
## high_school 0.07090 0.23007 0.308 0.7584
## Value 0.88327 0.13618 6.486 1.22e-09 ***
## eff_is_overall -0.31304 0.12317 -2.542 0.0121 *
## eff_cm_overall 0.01802 0.09560 0.188 0.8508
## eff_se_overall 0.27971 0.12187 2.295 0.0231 *
## cost_em_overall -0.13310 0.07505 -1.773 0.0782 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.008 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.3849, Adjusted R-squared: 0.3477
## F-statistic: 10.36 on 9 and 149 DF, p-value: 2.465e-12lm.beta(M4)##
## Call:
## lm(formula = teach_satisfaction ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_em_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 -0.04466821 0.03853753 0.01368145 0.02171405
## Value eff_is_overall eff_cm_overall eff_se_overall cost_em_overall
## 0.50653161 -0.21402937 0.01650089 0.22230423 -0.12077484Regressions predicting to what extent do you think you’ll leave education
M5 <- lm(teach_leave ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_te_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_te_overall*years,
data = Teacher_Cost)
summary(M5)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_te_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: To what extent do you think you will leave the field of education altogether?
## Min 1Q Median 3Q Max
## -2.9834 -1.0040 -0.2175 0.9852 3.3975
##
## Labels:
## value label
## 1 Definitely won't
## 2 Probably won't
## 3 Possibly won't
## 4 Unsure
## 5 Possibly will
## 6 Probably will
## 7 Definitely will
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.82750 1.25775 4.633 7.79e-06 ***
## years -0.11210 0.24004 -0.467 0.64116
## male 0.21503 0.30421 0.707 0.48077
## urban 0.08576 0.23804 0.360 0.71915
## high_school 0.67340 0.31831 2.116 0.03605 *
## Value -0.77056 0.18780 -4.103 6.69e-05 ***
## eff_is_overall 0.10140 0.17013 0.596 0.55204
## eff_cm_overall 0.04260 0.13152 0.324 0.74646
## eff_se_overall -0.18823 0.16807 -1.120 0.26451
## cost_te_overall 0.28958 0.08705 3.327 0.00111 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.387 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.3023, Adjusted R-squared: 0.2601
## F-statistic: 7.173 on 9 and 149 DF, p-value: 1.302e-08lm.beta(M5)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_te_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 -0.03449394 0.05164355 0.02514366 0.15952688
## Value eff_is_overall eff_cm_overall eff_se_overall cost_te_overall
## -0.34179955 0.05362710 0.03017409 -0.11571606 0.24477497M6 <- lm(teach_leave ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_oe_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_oe_overall*years,
data = Teacher_Cost)
summary(M6)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_oe_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: To what extent do you think you will leave the field of education altogether?
## Min 1Q Median 3Q Max
## -2.8673 -0.9573 -0.2135 0.8761 3.2392
##
## Labels:
## value label
## 1 Definitely won't
## 2 Probably won't
## 3 Possibly won't
## 4 Unsure
## 5 Possibly will
## 6 Probably will
## 7 Definitely will
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.59944 1.25813 4.451 1.67e-05 ***
## years -0.20373 0.23756 -0.858 0.392507
## male 0.10413 0.29708 0.351 0.726441
## urban 0.09361 0.23632 0.396 0.692592
## high_school 0.64075 0.31687 2.022 0.044955 *
## Value -0.73443 0.18741 -3.919 0.000135 ***
## eff_is_overall 0.16170 0.16814 0.962 0.337757
## eff_cm_overall 0.04492 0.13056 0.344 0.731281
## eff_se_overall -0.20283 0.16643 -1.219 0.224901
## cost_oe_overall 0.33077 0.09089 3.639 0.000376 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.378 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.3117, Adjusted R-squared: 0.2701
## F-statistic: 7.496 on 9 and 149 DF, p-value: 5.268e-09lm.beta(M6)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_oe_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 -0.06268604 0.02500948 0.02744410 0.15179063
## Value eff_is_overall eff_cm_overall eff_se_overall cost_oe_overall
## -0.32577168 0.08551466 0.03181837 -0.12468562 0.26686964M7 <- lm(teach_leave ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_lv_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_lv_overall*years,
data = Teacher_Cost)
summary(M7)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_lv_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: To what extent do you think you will leave the field of education altogether?
## Min 1Q Median 3Q Max
## -3.2045 -1.0120 -0.1897 0.9130 3.3279
##
## Labels:
## value label
## 1 Definitely won't
## 2 Probably won't
## 3 Possibly won't
## 4 Unsure
## 5 Possibly will
## 6 Probably will
## 7 Definitely will
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.86670 1.25195 4.686 6.23e-06 ***
## years -0.17062 0.23908 -0.714 0.476549
## male 0.14334 0.30054 0.477 0.634100
## urban 0.15922 0.23801 0.669 0.504553
## high_school 0.73987 0.31691 2.335 0.020897 *
## Value -0.73825 0.18874 -3.911 0.000139 ***
## eff_is_overall 0.12363 0.16955 0.729 0.467043
## eff_cm_overall 0.02383 0.13093 0.182 0.855829
## eff_se_overall -0.21355 0.16738 -1.276 0.203984
## cost_lv_overall 0.27342 0.08194 3.337 0.001070 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.387 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.3026, Adjusted R-squared: 0.2605
## F-statistic: 7.183 on 9 and 149 DF, p-value: 1.266e-08lm.beta(M7)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_lv_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 -0.05249982 0.03442592 0.04668021 0.17527265
## Value eff_is_overall eff_cm_overall eff_se_overall cost_lv_overall
## -0.32746840 0.06538224 0.01687847 -0.13128078 0.23812467M8 <- lm(teach_leave ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_em_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_em_overall*years,
data = Teacher_Cost)
summary(M8)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_em_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: To what extent do you think you will leave the field of education altogether?
## Min 1Q Median 3Q Max
## -3.1899 -1.0180 -0.1473 0.9046 3.4230
##
## Labels:
## value label
## 1 Definitely won't
## 2 Probably won't
## 3 Possibly won't
## 4 Unsure
## 5 Possibly will
## 6 Probably will
## 7 Definitely will
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.27758 1.35196 4.643 7.47e-06 ***
## years -0.13341 0.24611 -0.542 0.5886
## male 0.11771 0.31002 0.380 0.7047
## urban 0.13943 0.24362 0.572 0.5680
## high_school 0.77701 0.32431 2.396 0.0178 *
## Value -0.79917 0.19196 -4.163 5.29e-05 ***
## eff_is_overall 0.13762 0.17362 0.793 0.4293
## eff_cm_overall 0.02299 0.13476 0.171 0.8648
## eff_se_overall -0.21792 0.17179 -1.269 0.2066
## cost_em_overall 0.20399 0.10580 1.928 0.0557 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.42 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.2687, Adjusted R-squared: 0.2245
## F-statistic: 6.084 on 9 and 149 DF, p-value: 2.918e-07lm.beta(M8)##
## Call:
## lm(formula = teach_leave ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_em_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 -0.04105010 0.02827079 0.04087760 0.18407125
## Value eff_is_overall eff_cm_overall eff_se_overall cost_em_overall
## -0.35449094 0.07277819 0.01628339 -0.13396804 0.14316709Regressions predicting how sure are you that you’ll stay in teaching
M9 <- lm(teach_profession ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_te_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_te_overall*years,
data = Teacher_Cost)
summary(M9)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_te_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How sure are you that you will stay in the teaching profession?
## Min 1Q Median 3Q Max
## -3.9319 -0.5537 0.1821 0.8350 2.6302
##
## Labels:
## value label
## 1 Not at all sure
## 2 Unsure
## 3 Somewhat unsure
## 4 Neither sure or unsure
## 5 Somewhat sure
## 6 Sure
## 7 Extremely sure
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.01423 1.16977 2.577 0.0109 *
## years 0.31781 0.22325 1.424 0.1567
## male -0.07544 0.28293 -0.267 0.7901
## urban -0.11888 0.22139 -0.537 0.5921
## high_school -0.06856 0.29604 -0.232 0.8172
## Value 0.72571 0.17466 4.155 5.46e-05 ***
## eff_is_overall -0.23184 0.15822 -1.465 0.1450
## eff_cm_overall -0.06947 0.12232 -0.568 0.5709
## eff_se_overall 0.20687 0.15631 1.323 0.1877
## cost_te_overall -0.32799 0.08096 -4.051 8.17e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.29 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.2831, Adjusted R-squared: 0.2398
## F-statistic: 6.537 on 9 and 149 DF, p-value: 7.921e-08lm.beta(M9)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_te_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 0.10658262 -0.01974748 -0.03798826 -0.01770255
## Value eff_is_overall eff_cm_overall eff_se_overall cost_te_overall
## 0.35085394 -0.13363209 -0.05362900 0.13860870 -0.30216623M10 <- lm(teach_profession ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_oe_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_oe_overall*years,
data = Teacher_Cost)
summary(M10)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_oe_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How sure are you that you will stay in the teaching profession?
## Min 1Q Median 3Q Max
## -4.6366 -0.6049 0.2203 0.7935 2.5607
##
## Labels:
## value label
## 1 Not at all sure
## 2 Unsure
## 3 Somewhat unsure
## 4 Neither sure or unsure
## 5 Somewhat sure
## 6 Sure
## 7 Extremely sure
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.99999 1.18371 2.534 0.012297 *
## years 0.41868 0.22351 1.873 0.062999 .
## male 0.06284 0.27951 0.225 0.822410
## urban -0.13162 0.22234 -0.592 0.554763
## high_school -0.05024 0.29813 -0.169 0.866393
## Value 0.69622 0.17632 3.949 0.000121 ***
## eff_is_overall -0.29961 0.15819 -1.894 0.060169 .
## eff_cm_overall -0.06456 0.12284 -0.526 0.599946
## eff_se_overall 0.22966 0.15659 1.467 0.144580
## cost_oe_overall -0.32939 0.08551 -3.852 0.000174 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.297 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.2762, Adjusted R-squared: 0.2325
## F-statistic: 6.317 on 9 and 149 DF, p-value: 1.488e-07lm.beta(M10)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_oe_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 0.14041066 0.01645044 -0.04205846 -0.01297292
## Value eff_is_overall eff_cm_overall eff_se_overall cost_oe_overall
## 0.33659572 -0.17269589 -0.04984303 0.15387699 -0.28965074M11 <- lm(teach_profession ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_lv_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_lv_overall*years,
data = Teacher_Cost)
summary(M11)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_lv_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How sure are you that you will stay in the teaching profession?
## Min 1Q Median 3Q Max
## -3.8567 -0.5432 0.2293 0.8889 2.8830
##
## Labels:
## value label
## 1 Not at all sure
## 2 Unsure
## 3 Somewhat unsure
## 4 Neither sure or unsure
## 5 Somewhat sure
## 6 Sure
## 7 Extremely sure
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.933299 1.166647 2.514 0.012989 *
## years 0.384344 0.222789 1.725 0.086574 .
## male 0.008551 0.280062 0.031 0.975683
## urban -0.201289 0.221792 -0.908 0.365576
## high_school -0.144634 0.295315 -0.490 0.625021
## Value 0.690810 0.175879 3.928 0.000131 ***
## eff_is_overall -0.257739 0.157998 -1.631 0.104943
## eff_cm_overall -0.047487 0.122006 -0.389 0.697671
## eff_se_overall 0.236290 0.155973 1.515 0.131904
## cost_lv_overall -0.303889 0.076357 -3.980 0.000107 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.293 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.2806, Adjusted R-squared: 0.2371
## F-statistic: 6.457 on 9 and 149 DF, p-value: 9.962e-08lm.beta(M11)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_lv_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 0.12889459 0.00223836 -0.06432082 -0.03734443
## Value eff_is_overall eff_cm_overall eff_se_overall cost_lv_overall
## 0.33397929 -0.14856167 -0.03666045 0.15832017 -0.28845951M12 <- lm(teach_profession ~ years + male + urban + high_school +
Value + eff_is_overall + eff_cm_overall + eff_se_overall + cost_em_overall,
#Value*years + eff_is_overall*years + eff_cm_overall*years +
#eff_se_overall*years + cost_em_overall*years,
data = Teacher_Cost)
summary(M12)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_em_overall, data = Teacher_Cost)
##
## Residuals:
## <Labelled double>: How sure are you that you will stay in the teaching profession?
## Min 1Q Median 3Q Max
## -4.0902 -0.6005 0.2961 0.8748 2.8143
##
## Labels:
## value label
## 1 Not at all sure
## 2 Unsure
## 3 Somewhat unsure
## 4 Neither sure or unsure
## 5 Somewhat sure
## 6 Sure
## 7 Extremely sure
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.004302 1.253077 2.398 0.01774 *
## years 0.323277 0.228108 1.417 0.15851
## male -0.005634 0.287341 -0.020 0.98438
## urban -0.186388 0.225802 -0.825 0.41044
## high_school -0.185830 0.300589 -0.618 0.53737
## Value 0.750957 0.177920 4.221 4.22e-05 ***
## eff_is_overall -0.265142 0.160921 -1.648 0.10153
## eff_cm_overall -0.059858 0.124906 -0.479 0.63248
## eff_se_overall 0.228832 0.159229 1.437 0.15278
## cost_em_overall -0.308628 0.098057 -3.147 0.00199 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.316 on 149 degrees of freedom
## (110 observations deleted due to missingness)
## Multiple R-squared: 0.2537, Adjusted R-squared: 0.2086
## F-statistic: 5.628 on 9 and 149 DF, p-value: 1.095e-06lm.beta(M12)##
## Call:
## lm(formula = teach_profession ~ years + male + urban + high_school +
## Value + eff_is_overall + eff_cm_overall + eff_se_overall +
## cost_em_overall, data = Teacher_Cost)
##
## Standardized Coefficients::
## (Intercept) years male urban high_school
## 0.00000000 0.10841522 -0.00147471 -0.05955924 -0.04798112
## Value eff_is_overall eff_cm_overall eff_se_overall cost_em_overall
## 0.36305794 -0.15282844 -0.04621116 0.15332281 -0.23608476