Police repression Study 3 analysis
Siwar Hasan-Aslih
2022-10-04
Demographics
##
## Female Male
## 499 434##
## Asian / Asian-American Black / African-American Latino / Hispanic
## 47 86 55
## Other White / Caucasian
## 12 733##
## Democrat Independent Other (please specify)
## 370 194 19
## Republican
## 350Correlations between variables
Effect on perceived repression (manipulation check)
##
## Call:
## lm(formula = Suppression_sc ~ Cond.dum + gender_dum + race_dum +
## incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -70.51 -13.15 -6.14 16.47 88.07
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.99735 4.70378 1.913 0.05608 .
## Cond.dum 53.44800 1.69339 31.563 < 2e-16 ***
## gender_dum 3.41023 1.70618 1.999 0.04593 *
## race_dum 1.96686 2.11221 0.931 0.35200
## incomeN -0.72104 0.26464 -2.725 0.00656 **
## educationN 3.01955 0.98188 3.075 0.00216 **
## age -0.10872 0.06893 -1.577 0.11509
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 25.82 on 926 degrees of freedom
## Multiple R-squared: 0.5217, Adjusted R-squared: 0.5186
## F-statistic: 168.3 on 6 and 926 DF, p-value: < 2.2e-16##
## Call:
## lm(formula = Suppression_sc ~ Cond.dum * ideology + gender_dum +
## race_dum + incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -69.856 -13.323 -5.744 16.200 91.026
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.1084 5.1711 0.794 0.42711
## Cond.dum 62.4626 3.8131 16.381 < 2e-16 ***
## ideology 1.3969 0.6160 2.268 0.02357 *
## gender_dum 3.2396 1.7027 1.903 0.05739 .
## race_dum 2.1777 2.1168 1.029 0.30387
## incomeN -0.7425 0.2650 -2.802 0.00518 **
## educationN 3.0196 0.9845 3.067 0.00222 **
## age -0.1201 0.0695 -1.728 0.08431 .
## Cond.dum:ideology -2.2781 0.8664 -2.629 0.00869 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 25.75 on 924 degrees of freedom
## Multiple R-squared: 0.5255, Adjusted R-squared: 0.5214
## F-statistic: 127.9 on 8 and 924 DF, p-value: < 2.2e-16Outcomes
Trust in the police
##
## Call:
## lm(formula = zTrustPolice_sc ~ Cond.dum * zideology + gender_dum +
## race_dum + incomeN + educationN + age, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.70696 -0.64854 0.08303 0.65445 2.17387
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.119462 0.157689 -0.758 0.44890
## Cond.dum -0.644195 0.056702 -11.361 < 2e-16 ***
## zideology 0.362199 0.040352 8.976 < 2e-16 ***
## gender_dum 0.095064 0.057158 1.663 0.09662 .
## race_dum -0.127769 0.071062 -1.798 0.07250 .
## incomeN 0.029336 0.008895 3.298 0.00101 **
## educationN -0.048526 0.033050 -1.468 0.14237
## age 0.009372 0.002333 4.017 6.38e-05 ***
## Cond.dum:zideology -0.101063 0.056757 -1.781 0.07530 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8644 on 924 degrees of freedom
## Multiple R-squared: 0.2592, Adjusted R-squared: 0.2528
## F-statistic: 40.42 on 8 and 924 DF, p-value: < 2.2e-16##
## Call:
## lm(formula = zTrustPolice_sc ~ Cond.dum, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.84227 -0.79110 0.04376 0.76076 1.92104
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.32607 0.04405 7.402 3e-13 ***
## Cond.dum -0.64591 0.06200 -10.418 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9469 on 931 degrees of freedom
## Multiple R-squared: 0.1044, Adjusted R-squared: 0.1034
## F-statistic: 108.5 on 1 and 931 DF, p-value: < 2.2e-16Trust int the government
##
## Call:
## lm(formula = zTrustGov_sc ~ Cond.dum + zideology + gender_dum +
## race_dum + incomeN + educationN + age, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.41746 -0.73314 0.05541 0.67222 2.12586
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.362972 0.170239 -2.132 0.03326 *
## Cond.dum -0.520281 0.061270 -8.492 < 2e-16 ***
## zideology 0.163471 0.031397 5.207 2.37e-07 ***
## gender_dum 0.161789 0.061715 2.622 0.00890 **
## race_dum -0.097999 0.076778 -1.276 0.20214
## incomeN 0.029062 0.009611 3.024 0.00256 **
## educationN 0.018149 0.035702 0.508 0.61134
## age 0.007139 0.002520 2.833 0.00471 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.934 on 925 degrees of freedom
## Multiple R-squared: 0.1341, Adjusted R-squared: 0.1276
## F-statistic: 20.47 on 7 and 925 DF, p-value: < 2.2e-16Policy support
##
## Call:
## lm(formula = zPolicySupport ~ Cond.dum + zideology + gender_dum +
## race_dum + incomeN + educationN + age, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.37989 -0.60447 -0.07432 0.57803 2.81209
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.039308 0.159498 0.246 0.805392
## Cond.dum 0.303055 0.057404 5.279 1.62e-07 ***
## zideology -0.399540 0.029416 -13.582 < 2e-16 ***
## gender_dum -0.066246 0.057821 -1.146 0.252213
## race_dum 0.118016 0.071934 1.641 0.101216
## incomeN -0.024835 0.009004 -2.758 0.005927 **
## educationN 0.099039 0.033449 2.961 0.003146 **
## age -0.008668 0.002361 -3.671 0.000255 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8751 on 925 degrees of freedom
## Multiple R-squared: 0.24, Adjusted R-squared: 0.2342
## F-statistic: 41.72 on 7 and 925 DF, p-value: < 2.2e-16Mechanisms
##
## Call:
## lm(formula = zHarm_sc ~ Cond.dum + zideology + gender_dum + race_dum +
## incomeN + educationN + age, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.9164 -0.3937 -0.1460 0.4421 2.4111
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.772349 0.129624 -5.958 3.62e-09 ***
## Cond.dum 1.396542 0.046652 29.935 < 2e-16 ***
## zideology 0.007636 0.023907 0.319 0.749475
## gender_dum 0.043230 0.046991 0.920 0.357833
## race_dum 0.085263 0.058461 1.458 0.145054
## incomeN -0.024346 0.007318 -3.327 0.000912 ***
## educationN 0.108975 0.027184 4.009 6.60e-05 ***
## age -0.004636 0.001919 -2.416 0.015891 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7112 on 925 degrees of freedom
## Multiple R-squared: 0.498, Adjusted R-squared: 0.4942
## F-statistic: 131.1 on 7 and 925 DF, p-value: < 2.2e-16##
## Call:
## lm(formula = zMorality_sc ~ Cond.dum + zideology + gender_dum +
## race_dum + incomeN + educationN + age, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.25133 -0.65193 0.03573 0.68558 2.02585
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.465835 0.153193 3.041 0.00243 **
## Cond.dum -1.082810 0.055135 -19.639 < 2e-16 ***
## zideology 0.036410 0.028253 1.289 0.19783
## gender_dum -0.035047 0.055535 -0.631 0.52815
## race_dum -0.051704 0.069090 -0.748 0.45444
## incomeN 0.011297 0.008648 1.306 0.19179
## educationN -0.037956 0.032127 -1.181 0.23773
## age 0.004007 0.002268 1.767 0.07757 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8405 on 925 degrees of freedom
## Multiple R-squared: 0.2989, Adjusted R-squared: 0.2935
## F-statistic: 56.32 on 7 and 925 DF, p-value: < 2.2e-16##
## Call:
## lm(formula = zLegitimate_sc ~ Cond.dum + zideology + gender_dum +
## race_dum + incomeN + educationN + age, data = SS3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3496 -0.6582 0.0840 0.6070 1.8874
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.544412 0.148838 3.658 0.000269 ***
## Cond.dum -1.149395 0.053567 -21.457 < 2e-16 ***
## zideology 0.048459 0.027450 1.765 0.077838 .
## gender_dum -0.034329 0.053957 -0.636 0.524778
## race_dum -0.070779 0.067126 -1.054 0.291966
## incomeN 0.015266 0.008402 1.817 0.069558 .
## educationN -0.039821 0.031214 -1.276 0.202358
## age 0.002549 0.002203 1.157 0.247595
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8166 on 925 degrees of freedom
## Multiple R-squared: 0.3382, Adjusted R-squared: 0.3331
## F-statistic: 67.52 on 7 and 925 DF, p-value: < 2.2e-16Plot effect sizes
## List of 2
## $ legend.position: chr "none"
## $ plot.title :List of 11
## ..$ family : NULL
## ..$ face : chr "bold"
## ..$ colour : NULL
## ..$ size : NULL
## ..$ hjust : NULL
## ..$ vjust : NULL
## ..$ angle : NULL
## ..$ lineheight : NULL
## ..$ margin : NULL
## ..$ debug : NULL
## ..$ inherit.blank: logi FALSE
## ..- attr(*, "class")= chr [1:2] "element_text" "element"
## - attr(*, "class")= chr [1:2] "theme" "gg"
## - attr(*, "complete")= logi FALSE
## - attr(*, "validate")= logi TRUEMediation
##
## ********************** PROCESS for R Version 4.1 **********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 6
## Y : zTrustPolice_sc
## X : Cond.dum
## M1 : zHarm_sc
## M2 : zImmorality_sc
##
## Sample size: 933
##
## Random seed: 451671
##
##
## ***********************************************************************
## Outcome Variable: zHarm_sc
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6940 0.4817 0.5189 865.1888 1.0000 931.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant -0.7004 0.0335 -20.8990 0.0000 -0.7662 -0.6346
## Cond.dum 1.3874 0.0472 29.4141 0.0000 1.2948 1.4800
##
## ***********************************************************************
## Outcome Variable: zImmorality_sc
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7330 0.5373 0.4637 539.8623 2.0000 930.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant -0.0620 0.0384 -1.6140 0.1069 -0.1373 0.0134
## Cond.dum 0.1228 0.0619 1.9822 0.0477 0.0012 0.2443
## zHarm_sc 0.6890 0.0310 22.2380 0.0000 0.6282 0.7498
##
## ***********************************************************************
## Outcome Variable: zTrustPolice_sc
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6696 0.4483 0.5534 251.6644 3.0000 929.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant -0.1213 0.0420 -2.8869 0.0040 -0.2037 -0.0388
## Cond.dum 0.2402 0.0678 3.5431 0.0004 0.1072 0.3733
## zHarm_sc -0.1729 0.0419 -4.1265 0.0000 -0.2551 -0.0907
## zImmorality_sc -0.5992 0.0358 -16.7260 0.0000 -0.6695 -0.5289
##
## ***********************************************************************
## Bootstrapping progress:
##
|
| | 0%
|
| | 1%
|
|> | 1%
|
|> | 2%
|
|>> | 2%
|
|>> | 3%
|
|>> | 4%
|
|>>> | 4%
|
|>>> | 5%
|
|>>> | 6%
|
|>>>> | 6%
|
|>>>> | 7%
|
|>>>>> | 7%
|
|>>>>> | 8%
|
|>>>>> | 9%
|
|>>>>>> | 9%
|
|>>>>>> | 10%
|
|>>>>>>> | 10%
|
|>>>>>>> | 11%
|
|>>>>>>> | 12%
|
|>>>>>>>> | 12%
|
|>>>>>>>> | 13%
|
|>>>>>>>> | 14%
|
|>>>>>>>>> | 14%
|
|>>>>>>>>> | 15%
|
|>>>>>>>>>> | 15%
|
|>>>>>>>>>> | 16%
|
|>>>>>>>>>> | 17%
|
|>>>>>>>>>>> | 17%
|
|>>>>>>>>>>> | 18%
|
|>>>>>>>>>>> | 19%
|
|>>>>>>>>>>>> | 19%
|
|>>>>>>>>>>>> | 20%
|
|>>>>>>>>>>>>> | 20%
|
|>>>>>>>>>>>>> | 21%
|
|>>>>>>>>>>>>> | 22%
|
|>>>>>>>>>>>>>> | 22%
|
|>>>>>>>>>>>>>> | 23%
|
|>>>>>>>>>>>>>>> | 23%
|
|>>>>>>>>>>>>>>> | 24%
|
|>>>>>>>>>>>>>>> | 25%
|
|>>>>>>>>>>>>>>>> | 25%
|
|>>>>>>>>>>>>>>>> | 26%
|
|>>>>>>>>>>>>>>>> | 27%
|
|>>>>>>>>>>>>>>>>> | 27%
|
|>>>>>>>>>>>>>>>>> | 28%
|
|>>>>>>>>>>>>>>>>>> | 28%
|
|>>>>>>>>>>>>>>>>>> | 29%
|
|>>>>>>>>>>>>>>>>>> | 30%
|
|>>>>>>>>>>>>>>>>>>> | 30%
|
|>>>>>>>>>>>>>>>>>>> | 31%
|
|>>>>>>>>>>>>>>>>>>>> | 31%
|
|>>>>>>>>>>>>>>>>>>>> | 32%
|
|>>>>>>>>>>>>>>>>>>>> | 33%
|
|>>>>>>>>>>>>>>>>>>>>> | 33%
|
|>>>>>>>>>>>>>>>>>>>>> | 34%
|
|>>>>>>>>>>>>>>>>>>>>> | 35%
|
|>>>>>>>>>>>>>>>>>>>>>> | 35%
|
|>>>>>>>>>>>>>>>>>>>>>> | 36%
|
|>>>>>>>>>>>>>>>>>>>>>>> | 36%
|
|>>>>>>>>>>>>>>>>>>>>>>> | 37%
|
|>>>>>>>>>>>>>>>>>>>>>>> | 38%
|
|>>>>>>>>>>>>>>>>>>>>>>>> | 38%
|
|>>>>>>>>>>>>>>>>>>>>>>>> | 39%
|
|>>>>>>>>>>>>>>>>>>>>>>>> | 40%
|
|>>>>>>>>>>>>>>>>>>>>>>>>> | 40%
|
|>>>>>>>>>>>>>>>>>>>>>>>>> | 41%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>> | 41%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>> | 42%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>> | 43%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>> | 43%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>> | 44%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 44%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 45%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 46%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 46%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 47%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 48%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 48%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 49%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 49%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 50%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 51%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 51%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 52%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 52%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 53%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 54%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 54%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 55%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 56%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 56%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 57%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 57%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 58%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 59%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 59%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 60%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 60%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 61%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 62%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 62%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 63%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 64%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 64%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 65%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 65%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 66%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 67%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 67%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 68%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 69%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 69%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 70%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 70%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 71%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 72%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 72%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 73%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 73%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 74%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 75%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 75%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 76%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 77%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 77%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 78%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 78%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 79%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 80%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 80%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 81%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 81%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 82%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 83%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 83%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 84%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 85%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 85%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 86%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 86%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 87%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 88%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 88%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 89%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 90%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 90%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 91%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 91%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 92%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 93%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 93%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 94%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 94%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 95%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 96%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 96%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 97%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 98%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 98%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 99%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 99%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%
##
## **************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.2402 0.0678 3.5431 0.0004 0.1072 0.3733
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## TOTAL -0.8862 0.0610 -1.0069 -0.7643
## Ind1 -0.2398 0.0671 -0.3725 -0.1102
## Ind2 -0.0736 0.0423 -0.1601 0.0061
## Ind3 -0.5728 0.0518 -0.6798 -0.4758
##
## Indirect effect key:
## Ind1 Cond.dum -> zHarm_sc -> zTrustPolice_sc
## Ind2 Cond.dum -> zImmorality_sc -> zTrustPolice_sc
## Ind3 Cond.dum -> zHarm_sc -> zImmorality_sc -> zTrustPolice_sc
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 5000##
## ********************** PROCESS for R Version 4.1 **********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 6
## Y : zPolicySupport
## X : Cond.dum
## M1 : zHarm_sc
## M2 : zImmorality_sc
## M3 : zTrustPolice_sc
##
## Covariates:
## gender_dum race_dum incomeN educationN age
##
## Sample size: 933
##
## Random seed: 122937
##
##
## ***********************************************************************
## Outcome Variable: zHarm_sc
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7057 0.4979 0.5053 153.0696 6.0000 926.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant -0.7738 0.1295 -5.9756 0.0000 -1.0279 -0.5196
## Cond.dum 1.3962 0.0466 29.9507 0.0000 1.3047 1.4877
## gender_dum 0.0432 0.0470 0.9187 0.3585 -0.0490 0.1353
## race_dum 0.0834 0.0581 1.4346 0.1517 -0.0307 0.1975
## incomeN -0.0241 0.0073 -3.3133 0.0010 -0.0384 -0.0098
## educationN 0.1081 0.0270 3.9989 0.0001 0.0550 0.1611
## age -0.0045 0.0019 -2.3960 0.0168 -0.0083 -0.0008
##
## ***********************************************************************
## Outcome Variable: zImmorality_sc
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7337 0.5384 0.4651 154.1030 7.0000 925.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.0767 0.1266 0.6060 0.5447 -0.1717 0.3252
## Cond.dum 0.1177 0.0628 1.8754 0.0611 -0.0055 0.2408
## zHarm_sc 0.6925 0.0315 21.9641 0.0000 0.6306 0.7544
## gender_dum 0.0055 0.0451 0.1229 0.9022 -0.0829 0.0940
## race_dum 0.0028 0.0558 0.0494 0.9606 -0.1068 0.1124
## incomeN 0.0044 0.0070 0.6292 0.5294 -0.0094 0.0182
## educationN -0.0327 0.0262 -1.2491 0.2119 -0.0840 0.0187
## age -0.0013 0.0018 -0.7032 0.4821 -0.0049 0.0023
##
## ***********************************************************************
## Outcome Variable: zTrustPolice_sc
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6954 0.4836 0.5209 108.1501 8.0000 924.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant -0.5726 0.1340 -4.2733 0.0000 -0.8356 -0.3097
## Cond.dum 0.1861 0.0665 2.7972 0.0053 0.0555 0.3167
## zHarm_sc -0.1410 0.0412 -3.4272 0.0006 -0.2218 -0.0603
## zImmorality_sc -0.5977 0.0348 -17.1767 0.0000 -0.6660 -0.5294
## gender_dum 0.1231 0.0477 2.5803 0.0100 0.0295 0.2167
## race_dum -0.1574 0.0591 -2.6624 0.0079 -0.2733 -0.0414
## incomeN 0.0273 0.0074 3.6652 0.0003 0.0127 0.0419
## educationN -0.0429 0.0277 -1.5485 0.1219 -0.0973 0.0115
## age 0.0098 0.0019 5.0951 0.0000 0.0061 0.0136
##
## ***********************************************************************
## Outcome Variable: zPolicySupport
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5683 0.3230 0.6836 48.9312 9.0000 923.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant -0.0258 0.1550 -0.1666 0.8677 -0.3301 0.2784
## Cond.dum 0.0420 0.0765 0.5484 0.5835 -0.1082 0.1922
## zHarm_sc 0.1640 0.0474 3.4555 0.0006 0.0708 0.2571
## zImmorality_sc -0.3260 0.0458 -7.1206 0.0000 -0.4159 -0.2362
## zTrustPolice_sc -0.6141 0.0377 -16.2959 0.0000 -0.6881 -0.5402
## gender_dum 0.0012 0.0549 0.0221 0.9824 -0.1064 0.1089
## race_dum 0.0948 0.0680 1.3946 0.1635 -0.0386 0.2282
## incomeN -0.0124 0.0086 -1.4497 0.1475 -0.0293 0.0044
## educationN 0.0902 0.0318 2.8393 0.0046 0.0279 0.1526
## age -0.0060 0.0022 -2.6580 0.0080 -0.0104 -0.0016
##
## ***********************************************************************
## Bootstrapping progress:
##
|
| | 0%
|
| | 1%
|
|> | 1%
|
|> | 2%
|
|>> | 2%
|
|>> | 3%
|
|>> | 4%
|
|>>> | 4%
|
|>>> | 5%
|
|>>> | 6%
|
|>>>> | 6%
|
|>>>> | 7%
|
|>>>>> | 7%
|
|>>>>> | 8%
|
|>>>>> | 9%
|
|>>>>>> | 9%
|
|>>>>>> | 10%
|
|>>>>>>> | 10%
|
|>>>>>>> | 11%
|
|>>>>>>> | 12%
|
|>>>>>>>> | 12%
|
|>>>>>>>> | 13%
|
|>>>>>>>> | 14%
|
|>>>>>>>>> | 14%
|
|>>>>>>>>> | 15%
|
|>>>>>>>>>> | 15%
|
|>>>>>>>>>> | 16%
|
|>>>>>>>>>> | 17%
|
|>>>>>>>>>>> | 17%
|
|>>>>>>>>>>> | 18%
|
|>>>>>>>>>>> | 19%
|
|>>>>>>>>>>>> | 19%
|
|>>>>>>>>>>>> | 20%
|
|>>>>>>>>>>>>> | 20%
|
|>>>>>>>>>>>>> | 21%
|
|>>>>>>>>>>>>> | 22%
|
|>>>>>>>>>>>>>> | 22%
|
|>>>>>>>>>>>>>> | 23%
|
|>>>>>>>>>>>>>>> | 23%
|
|>>>>>>>>>>>>>>> | 24%
|
|>>>>>>>>>>>>>>> | 25%
|
|>>>>>>>>>>>>>>>> | 25%
|
|>>>>>>>>>>>>>>>> | 26%
|
|>>>>>>>>>>>>>>>> | 27%
|
|>>>>>>>>>>>>>>>>> | 27%
|
|>>>>>>>>>>>>>>>>> | 28%
|
|>>>>>>>>>>>>>>>>>> | 28%
|
|>>>>>>>>>>>>>>>>>> | 29%
|
|>>>>>>>>>>>>>>>>>> | 30%
|
|>>>>>>>>>>>>>>>>>>> | 30%
|
|>>>>>>>>>>>>>>>>>>> | 31%
|
|>>>>>>>>>>>>>>>>>>>> | 31%
|
|>>>>>>>>>>>>>>>>>>>> | 32%
|
|>>>>>>>>>>>>>>>>>>>> | 33%
|
|>>>>>>>>>>>>>>>>>>>>> | 33%
|
|>>>>>>>>>>>>>>>>>>>>> | 34%
|
|>>>>>>>>>>>>>>>>>>>>> | 35%
|
|>>>>>>>>>>>>>>>>>>>>>> | 35%
|
|>>>>>>>>>>>>>>>>>>>>>> | 36%
|
|>>>>>>>>>>>>>>>>>>>>>>> | 36%
|
|>>>>>>>>>>>>>>>>>>>>>>> | 37%
|
|>>>>>>>>>>>>>>>>>>>>>>> | 38%
|
|>>>>>>>>>>>>>>>>>>>>>>>> | 38%
|
|>>>>>>>>>>>>>>>>>>>>>>>> | 39%
|
|>>>>>>>>>>>>>>>>>>>>>>>> | 40%
|
|>>>>>>>>>>>>>>>>>>>>>>>>> | 40%
|
|>>>>>>>>>>>>>>>>>>>>>>>>> | 41%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>> | 41%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>> | 42%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>> | 43%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>> | 43%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>> | 44%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 44%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 45%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 46%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 46%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 47%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 48%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 48%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 49%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 49%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 50%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 51%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 51%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 52%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 52%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 53%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 54%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 54%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 55%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 56%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 56%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 57%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 57%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 58%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 59%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 59%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 60%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 60%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 61%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 62%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 62%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 63%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 64%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 64%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 65%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 65%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 66%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 67%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 67%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 68%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 69%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 69%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 70%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 70%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 71%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 72%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 72%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 73%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 73%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 74%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 75%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 75%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 76%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 77%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 77%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 78%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 78%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 79%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 80%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 80%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 81%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 81%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 82%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 83%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 83%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 84%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 85%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 85%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 86%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 86%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 87%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 88%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 88%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 89%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 90%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 90%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 91%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 91%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 92%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 93%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 93%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 94%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 94%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 95%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 96%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 96%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 97%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 98%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 98%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> | 99%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 99%
|
|>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%
##
## **************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.0420 0.0765 0.5484 0.5835 -0.1082 0.1922
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## TOTAL 0.2801 0.0722 0.1397 0.4212
## Ind1 0.2289 0.0786 0.0740 0.3848
## Ind2 -0.0384 0.0245 -0.0901 0.0071
## Ind3 -0.1143 0.0402 -0.1976 -0.0382
## Ind4 -0.3152 0.0521 -0.4225 -0.2167
## Ind5 0.1209 0.0406 0.0422 0.2048
## Ind6 0.0432 0.0264 -0.0085 0.0958
## Ind7 0.3549 0.0424 0.2787 0.4442
##
## Indirect effect key:
## Ind1 Cond.dum -> zHarm_sc -> zPolicySupport
## Ind2 Cond.dum -> zImmorality_sc -> zPolicySupport
## Ind3 Cond.dum -> zTrustPolice_sc -> zPolicySupport
## Ind4 Cond.dum -> zHarm_sc -> zImmorality_sc -> zPolicySupport
## Ind5 Cond.dum -> zHarm_sc -> zTrustPolice_sc -> zPolicySupport
## Ind6 Cond.dum -> zImmorality_sc -> zTrustPolice_sc -> zPolicySupport
## Ind7 Cond.dum -> zHarm_sc -> zImmorality_sc -> zTrustPolice_sc -> zPolicySupport
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 5000Moderators
Political ideology
##
## Call:
## lm(formula = TrustPolice_sc ~ Cond.dum * ideology + gender_dum +
## race_dum + incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -86.834 -20.804 2.663 20.993 69.733
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 21.30868 5.56850 3.827 0.000139 ***
## Cond.dum -14.10853 4.10616 -3.436 0.000617 ***
## ideology 5.95373 0.66330 8.976 < 2e-16 ***
## gender_dum 3.04945 1.83351 1.663 0.096616 .
## race_dum -4.09856 2.27951 -1.798 0.072503 .
## incomeN 0.94104 0.28532 3.298 0.001010 **
## educationN -1.55661 1.06016 -1.468 0.142369
## age 0.30062 0.07484 4.017 6.38e-05 ***
## Cond.dum:ideology -1.66125 0.93295 -1.781 0.075300 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 27.73 on 924 degrees of freedom
## Multiple R-squared: 0.2592, Adjusted R-squared: 0.2528
## F-statistic: 40.42 on 8 and 924 DF, p-value: < 2.2e-16## JOHNSON-NEYMAN INTERVAL
##
## When ideology is INSIDE the interval [-1.80, 125.54], the slope of Cond.dum
## is p < .05.
##
## Note: The range of observed values of ideology is [1.00, 7.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Cond.dum when ideology = 1.994927 (- 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -17.42 2.57 -6.77 0.00
##
## Slope of Cond.dum when ideology = 3.946409 (Mean):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -20.66 1.82 -11.36 0.00
##
## Slope of Cond.dum when ideology = 5.897892 (+ 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -23.91 2.57 -9.29 0.00## # Effect Size for ANOVA (Type I)
##
## Parameter | Eta2 (partial) | 95% CI
## -------------------------------------------------
## Cond.dum | 0.12 | [0.09, 1.00]
## ideology | 0.14 | [0.11, 1.00]
## gender_dum | 5.25e-03 | [0.00, 1.00]
## race_dum | 7.75e-03 | [0.00, 1.00]
## incomeN | 8.88e-03 | [0.00, 1.00]
## educationN | 1.63e-03 | [0.00, 1.00]
## age | 0.02 | [0.01, 1.00]
## Cond.dum:ideology | 3.42e-03 | [0.00, 1.00]
##
## - One-sided CIs: upper bound fixed at (1).
##
## Call:
## lm(formula = TrustGov_sc ~ Cond.dum * ideology + gender_dum +
## race_dum + incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -70.183 -21.107 1.569 19.385 61.640
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24.95161 5.41972 4.604 4.73e-06 ***
## Cond.dum -13.97900 3.99645 -3.498 0.000491 ***
## ideology 2.54991 0.64557 3.950 8.42e-05 ***
## gender_dum 4.65180 1.78452 2.607 0.009288 **
## race_dum -2.82057 2.21860 -1.271 0.203932
## incomeN 0.83847 0.27769 3.019 0.002602 **
## educationN 0.51693 1.03183 0.501 0.616505
## age 0.20557 0.07284 2.822 0.004875 **
## Cond.dum:ideology -0.26512 0.90802 -0.292 0.770374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 26.99 on 924 degrees of freedom
## Multiple R-squared: 0.1342, Adjusted R-squared: 0.1267
## F-statistic: 17.91 on 8 and 924 DF, p-value: < 2.2e-16## # Effect Size for ANOVA (Type I)
##
## Parameter | Eta2 (partial) | 95% CI
## -------------------------------------------------
## Cond.dum | 0.07 | [0.05, 1.00]
## ideology | 0.04 | [0.02, 1.00]
## gender_dum | 9.01e-03 | [0.00, 1.00]
## race_dum | 3.82e-03 | [0.00, 1.00]
## incomeN | 0.01 | [0.00, 1.00]
## educationN | 4.53e-04 | [0.00, 1.00]
## age | 8.60e-03 | [0.00, 1.00]
## Cond.dum:ideology | 9.23e-05 | [0.00, 1.00]
##
## - One-sided CIs: upper bound fixed at (1).
##
## Call:
## lm(formula = PolicySupport ~ Cond.dum * ideology + gender_dum +
## race_dum + incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -52.021 -13.315 -1.635 12.954 61.126
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 73.24157 3.84181 19.064 < 2e-16 ***
## Cond.dum 3.15828 2.83292 1.115 0.265204
## ideology -4.91152 0.45762 -10.733 < 2e-16 ***
## gender_dum -1.38086 1.26497 -1.092 0.275288
## race_dum 2.54953 1.57268 1.621 0.105329
## incomeN -0.54051 0.19685 -2.746 0.006153 **
## educationN 2.18988 0.73143 2.994 0.002827 **
## age -0.18758 0.05164 -3.633 0.000296 ***
## Cond.dum:ideology 0.87932 0.64366 1.366 0.172232
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 19.13 on 924 degrees of freedom
## Multiple R-squared: 0.2415, Adjusted R-squared: 0.2349
## F-statistic: 36.77 on 8 and 924 DF, p-value: < 2.2e-16## # Effect Size for ANOVA (Type I)
##
## Parameter | Eta2 (partial) | 95% CI
## -------------------------------------------------
## Cond.dum | 0.03 | [0.01, 1.00]
## ideology | 0.20 | [0.16, 1.00]
## gender_dum | 2.88e-03 | [0.00, 1.00]
## race_dum | 6.35e-03 | [0.00, 1.00]
## incomeN | 3.22e-03 | [0.00, 1.00]
## educationN | 8.33e-03 | [0.00, 1.00]
## age | 0.01 | [0.00, 1.00]
## Cond.dum:ideology | 2.02e-03 | [0.00, 1.00]
##
## - One-sided CIs: upper bound fixed at (1).
##
## Call:
## lm(formula = Harm_sc ~ Cond.dum * ideology + gender_dum + race_dum +
## incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -66.644 -14.237 -5.275 16.812 90.262
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.07963 5.20686 1.360 0.17426
## Cond.dum 59.59265 3.83949 15.521 < 2e-16 ***
## ideology 1.21065 0.62022 1.952 0.05124 .
## gender_dum 1.41307 1.71443 0.824 0.41003
## race_dum 3.19465 2.13147 1.499 0.13427
## incomeN -0.89658 0.26679 -3.361 0.00081 ***
## educationN 3.92518 0.99131 3.960 8.08e-05 ***
## age -0.17438 0.06998 -2.492 0.01289 *
## Cond.dum:ideology -2.16400 0.87236 -2.481 0.01329 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 25.93 on 924 degrees of freedom
## Multiple R-squared: 0.5013, Adjusted R-squared: 0.497
## F-statistic: 116.1 on 8 and 924 DF, p-value: < 2.2e-16## JOHNSON-NEYMAN INTERVAL
##
## When ideology is OUTSIDE the interval [17.05, 116.97], the slope of
## Cond.dum is p < .05.
##
## Note: The range of observed values of ideology is [1.00, 7.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Cond.dum when ideology = 1.994927 (- 1 SD):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## 55.28 2.41 22.97 0.00
##
## Slope of Cond.dum when ideology = 3.946409 (Mean):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## 51.05 1.70 30.02 0.00
##
## Slope of Cond.dum when ideology = 5.897892 (+ 1 SD):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## 46.83 2.41 19.46 0.00## # Effect Size for ANOVA (Type I)
##
## Parameter | Eta2 (partial) | 95% CI
## -------------------------------------------------
## Cond.dum | 0.49 | [0.46, 1.00]
## ideology | 6.73e-04 | [0.00, 1.00]
## gender_dum | 2.79e-04 | [0.00, 1.00]
## race_dum | 4.59e-03 | [0.00, 1.00]
## incomeN | 4.28e-03 | [0.00, 1.00]
## educationN | 0.02 | [0.01, 1.00]
## age | 6.31e-03 | [0.00, 1.00]
## Cond.dum:ideology | 6.62e-03 | [0.00, 1.00]
##
## - One-sided CIs: upper bound fixed at (1).
##
## Call:
## lm(formula = Morality_sc ~ Cond.dum * ideology + gender_dum +
## race_dum + incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -74.967 -22.033 0.676 24.275 72.130
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 69.21813 5.75176 12.034 <2e-16 ***
## Cond.dum -45.27519 4.24130 -10.675 <2e-16 ***
## ideology -0.40105 0.68513 -0.585 0.5584
## gender_dum -1.03397 1.89385 -0.546 0.5852
## race_dum -1.84095 2.35453 -0.782 0.4345
## incomeN 0.39209 0.29471 1.330 0.1837
## educationN -1.23899 1.09505 -1.131 0.2582
## age 0.14159 0.07731 1.832 0.0673 .
## Cond.dum:ideology 2.10421 0.96365 2.184 0.0292 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.64 on 924 degrees of freedom
## Multiple R-squared: 0.3025, Adjusted R-squared: 0.2964
## F-statistic: 50.08 on 8 and 924 DF, p-value: < 2.2e-16## JOHNSON-NEYMAN INTERVAL
##
## When ideology is OUTSIDE the interval [13.10, 177.61], the slope of
## Cond.dum is p < .05.
##
## Note: The range of observed values of ideology is [1.00, 7.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Cond.dum when ideology = 1.994927 (- 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -41.08 2.66 -15.45 0.00
##
## Slope of Cond.dum when ideology = 3.946409 (Mean):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -36.97 1.88 -19.68 0.00
##
## Slope of Cond.dum when ideology = 5.897892 (+ 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -32.86 2.66 -12.36 0.00## # Effect Size for ANOVA (Type I)
##
## Parameter | Eta2 (partial) | 95% CI
## -------------------------------------------------
## Cond.dum | 0.29 | [0.26, 1.00]
## ideology | 3.84e-03 | [0.00, 1.00]
## gender_dum | 1.89e-04 | [0.00, 1.00]
## race_dum | 1.37e-03 | [0.00, 1.00]
## incomeN | 8.77e-04 | [0.00, 1.00]
## educationN | 1.31e-03 | [0.00, 1.00]
## age | 3.38e-03 | [0.00, 1.00]
## Cond.dum:ideology | 5.13e-03 | [0.00, 1.00]
##
## - One-sided CIs: upper bound fixed at (1).
Attitudes towards the police and the protesters
##
## Call:
## lm(formula = TrustPolice_sc ~ Cond.dum * PoliceView_sc + ideology +
## gender_dum + race_dum + incomeN + educationN + age, data = S3,
## na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -83.134 -11.029 1.904 13.298 67.660
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10.69131 4.50469 2.373 0.017830 *
## Cond.dum -9.65495 3.36559 -2.869 0.004215 **
## PoliceView_sc 0.80899 0.04023 20.109 < 2e-16 ***
## ideology -0.24758 0.44879 -0.552 0.581319
## gender_dum -0.16518 1.47273 -0.112 0.910719
## race_dum 1.09215 1.83808 0.594 0.552538
## incomeN 0.11035 0.23147 0.477 0.633670
## educationN 0.35056 0.85333 0.411 0.681305
## age -0.05469 0.06196 -0.883 0.377611
## Cond.dum:PoliceView_sc -0.18640 0.04934 -3.778 0.000168 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 22.18 on 923 degrees of freedom
## Multiple R-squared: 0.5265, Adjusted R-squared: 0.5219
## F-statistic: 114.1 on 9 and 923 DF, p-value: < 2.2e-16
## JOHNSON-NEYMAN INTERVAL
##
## When PoliceView_sc is OUTSIDE the interval [-176.26, -11.09], the slope of
## Cond.dum is p < .05.
##
## Note: The range of observed values of PoliceView_sc is [0.00, 100.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Cond.dum when PoliceView_sc = 32.00840 (- 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -15.62 2.06 -7.59 0.00
##
## Slope of Cond.dum when PoliceView_sc = 61.55556 (Mean):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -21.13 1.46 -14.52 0.00
##
## Slope of Cond.dum when PoliceView_sc = 91.10271 (+ 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -26.64 2.06 -12.92 0.00##
## Call:
## lm(formula = TrustPolice_sc ~ Cond.dum * ActivistView_sc + ideology +
## gender_dum + race_dum + incomeN + educationN + age, data = S3,
## na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -87.231 -19.925 2.486 21.136 70.056
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23.30069 5.40280 4.313 1.79e-05 ***
## Cond.dum -18.16227 2.88230 -6.301 4.56e-10 ***
## ActivistView_sc 0.08042 0.04300 1.870 0.061769 .
## ideology 4.45050 0.66010 6.742 2.75e-11 ***
## gender_dum 3.31536 1.83460 1.807 0.071067 .
## race_dum -4.44099 2.28704 -1.942 0.052465 .
## incomeN 0.98489 0.28666 3.436 0.000617 ***
## educationN -1.57141 1.06088 -1.481 0.138886
## age 0.30345 0.07489 4.052 5.51e-05 ***
## Cond.dum:ActivistView_sc -0.05750 0.05062 -1.136 0.256236
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 27.74 on 923 degrees of freedom
## Multiple R-squared: 0.2595, Adjusted R-squared: 0.2523
## F-statistic: 35.94 on 9 and 923 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = TrustGov_sc ~ Cond.dum * PoliceView_sc + ideology +
## gender_dum + race_dum + incomeN + educationN + age, data = S3,
## na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -67.695 -16.163 1.796 16.714 59.539
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 17.41116 4.83757 3.599 0.000336 ***
## Cond.dum -11.66523 3.61430 -3.228 0.001293 **
## PoliceView_sc 0.57977 0.04320 13.420 < 2e-16 ***
## ideology -1.68407 0.48195 -3.494 0.000498 ***
## gender_dum 2.13322 1.58156 1.349 0.177730
## race_dum 1.06373 1.97391 0.539 0.590090
## incomeN 0.18579 0.24857 0.747 0.455002
## educationN 2.02083 0.91639 2.205 0.027685 *
## age -0.07124 0.06654 -1.071 0.284595
## Cond.dum:PoliceView_sc -0.06033 0.05299 -1.139 0.255192
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 23.82 on 923 degrees of freedom
## Multiple R-squared: 0.3263, Adjusted R-squared: 0.3197
## F-statistic: 49.67 on 9 and 923 DF, p-value: < 2.2e-16
## JOHNSON-NEYMAN INTERVAL
##
## When PoliceView_sc is INSIDE the interval [-29.11, 410.71], the slope of
## Cond.dum is p < .05.
##
## Note: The range of observed values of PoliceView_sc is [0.00, 100.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Cond.dum when PoliceView_sc = 32.00840 (- 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -13.60 2.21 -6.15 0.00
##
## Slope of Cond.dum when PoliceView_sc = 61.55556 (Mean):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -15.38 1.56 -9.84 0.00
##
## Slope of Cond.dum when PoliceView_sc = 91.10271 (+ 1 SD):
##
## Est. S.E. t val. p
## -------- ------ -------- ------
## -17.16 2.21 -7.75 0.00##
## Call:
## lm(formula = TrustGov_sc ~ Cond.dum * ActivistView_sc + ideology +
## gender_dum + race_dum + incomeN + educationN + age, data = S3,
## na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -71.42 -21.25 1.75 19.28 63.36
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 25.11234 5.25434 4.779 2.05e-06 ***
## Cond.dum -14.04978 2.80310 -5.012 6.45e-07 ***
## ActivistView_sc 0.05502 0.04182 1.316 0.18860
## ideology 1.84829 0.64196 2.879 0.00408 **
## gender_dum 4.78010 1.78419 2.679 0.00751 **
## race_dum -3.05905 2.22420 -1.375 0.16936
## incomeN 0.87226 0.27878 3.129 0.00181 **
## educationN 0.49093 1.03173 0.476 0.63431
## age 0.20662 0.07283 2.837 0.00466 **
## Cond.dum:ActivistView_sc -0.02281 0.04922 -0.463 0.64325
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 26.98 on 923 degrees of freedom
## Multiple R-squared: 0.1359, Adjusted R-squared: 0.1275
## F-statistic: 16.13 on 9 and 923 DF, p-value: < 2.2e-16
Additional patterns
Perceived extremity of protesters
##
## Call:
## lm(formula = ExtremeProtesters_sc ~ Cond.dum + ideology + gender_dum +
## race_dum + incomeN + educationN + age, data = S3, na.action = na.omit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -57.782 -25.528 0.735 22.662 65.060
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 47.84482 5.38864 8.879 < 2e-16 ***
## Cond.dum 4.53330 1.83774 2.467 0.0138 *
## ideology -2.53966 0.48257 -5.263 1.76e-07 ***
## gender_dum 3.71539 1.85110 2.007 0.0450 *
## race_dum -1.29008 2.30291 -0.560 0.5755
## incomeN -0.03791 0.28826 -0.132 0.8954
## educationN 1.47892 1.07085 1.381 0.1676
## age -0.05622 0.07559 -0.744 0.4572
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.02 on 925 degrees of freedom
## Multiple R-squared: 0.04474, Adjusted R-squared: 0.03751
## F-statistic: 6.189 on 7 and 925 DF, p-value: 4.255e-07