Demographics
##
## CG FG
## 567 151##
## Female Male
## 462 254##
## Majority URM
## 632 86##
## Standard Plus
## 364 354##
## CG FG
## Standard 285 79
## Plus 282 72##
## Female Male
## Standard 228 134
## Plus 234 120##
## Majority URM
## Standard 320 44
## Plus 312 42## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 708 11.3 2.39 11.3 11.3 2.28 4.18 19.4 15.2 0.21 0.1 0.09## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 703 13.6 2.4 13.7 13.6 2.51 5.13 22 16.9 -0.02 0.06 0.09## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 708 1.1 0.51 1 1.11 0 0 2 2 0.15 0.58 0.02## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 698 1.11 0.44 1 1.07 0 0 2 2 0.54 1.69 0.02## Ctrl_v_NA StandardUV_v_NA PlusProUV_v_NA
## NA 0 0 0
## Ctrl 1 0 0
## StandardUV 0 1 0
## PlusProUV 0 0 1T test for quality Average
##
## Welch Two Sample t-test
##
## data: d$Code_quality_Ave by d$Condition
## t = -3, df = 708, p-value = 0.003
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1329 -0.0279
## sample estimates:
## mean in group Standard mean in group Plus
## 1.06 1.14
##
## Descriptive statistics by group
## group: Standard
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 360 1.06 0.36 1 1.07 0 0 2 2 -0.02 0.73 0.02
## ------------------------------------------------------------
## group: Plus
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 350 1.14 0.35 1 1.13 0 0 2 2 0.48 0.51 0.02T test for cognitive process Average
##
## Welch Two Sample t-test
##
## data: d$cogproc_Ave by d$Condition
## t = -7, df = 713, p-value = 0.000000000001
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.296 -0.742
## sample estimates:
## mean in group Standard mean in group Plus
## 12 13
##
## Descriptive statistics by group
## group: Standard
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 362 12 1.93 11.8 12 1.72 6.74 17.8 11 0.09 -0.03 0.1
## ------------------------------------------------------------
## group: Plus
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 353 13 1.84 12.9 13 1.85 7.52 18.2 10.7 -0.06 0.03 0.1Correlations between the two by group Average
##
## Call:
## lm(formula = cogproc_Ave ~ Condition * Code_quality_Ave + URM_vs_Maj +
## FG_vs_CG + Female_vs_Male, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.462 -1.200 -0.087 1.214 5.089
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 12.0975 0.2296 52.69
## ConditionPlus_vs_Standard 1.3931 0.4590 3.03
## Code_quality_Ave 0.3397 0.1979 1.72
## URM_vs_Maj -0.0255 0.2230 -0.11
## FG_vs_CG -0.1862 0.1768 -1.05
## Female_vs_Male -0.2828 0.1478 -1.91
## ConditionPlus_vs_Standard:Code_quality_Ave -0.3583 0.3953 -0.91
## Pr(>|t|)
## (Intercept) <0.0000000000000002 ***
## ConditionPlus_vs_Standard 0.0025 **
## Code_quality_Ave 0.0865 .
## URM_vs_Maj 0.9089
## FG_vs_CG 0.2927
## Female_vs_Male 0.0562 .
## ConditionPlus_vs_Standard:Code_quality_Ave 0.3650
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.86 on 701 degrees of freedom
## (10 observations deleted due to missingness)
## Multiple R-squared: 0.0807, Adjusted R-squared: 0.0729
## F-statistic: 10.3 on 6 and 701 DF, p-value: 0.0000000000665
T test for quality A1
##
## Welch Two Sample t-test
##
## data: d$Code_quality_A1 by d$Condition
## t = -2, df = 706, p-value = 0.05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.151977 -0.000692
## sample estimates:
## mean in group Standard mean in group Plus
## 1.06 1.14
##
## Descriptive statistics by group
## group: Standard
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 359 1.06 0.52 1 1.08 0 0 2 2 0.08 0.59 0.03
## ------------------------------------------------------------
## group: Plus
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 349 1.14 0.5 1 1.14 0 0 2 2 0.25 0.5 0.03T test for cognitive process A1
##
## Welch Two Sample t-test
##
## data: d$cogproc_A1 by d$Condition
## t = -6, df = 703, p-value = 0.00000004
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.322 -0.631
## sample estimates:
## mean in group Standard mean in group Plus
## 10.9 11.8
##
## Descriptive statistics by group
## group: Standard
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 359 10.9 2.45 10.8 10.8 2.4 4.18 18.3 14.1 0.3 0.12 0.13
## ------------------------------------------------------------
## group: Plus
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 349 11.8 2.23 11.8 11.8 2.31 4.66 19.4 14.7 0.25 0.15 0.12Correlations between the two by group A1
| Code_quality_A2 | cogproc_A2 | |
|---|---|---|
| Code_quality_A2 | ||
| cogproc_A2 | 0.10 |
| Code_quality_A2 | cogproc_A2 | |
|---|---|---|
| Code_quality_A2 | ||
| cogproc_A2 | 0.06 |
##
## Call:
## lm(formula = cogproc_A2 ~ Condition * Code_quality_A2, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.269 -1.654 0.115 1.614 7.820
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 13.101 0.244 53.69
## ConditionPlus_vs_Standard 1.239 0.488 2.54
## Code_quality_A2 0.442 0.205 2.16
## ConditionPlus_vs_Standard:Code_quality_A2 -0.205 0.410 -0.50
## Pr(>|t|)
## (Intercept) <0.0000000000000002 ***
## ConditionPlus_vs_Standard 0.011 *
## Code_quality_A2 0.031 *
## ConditionPlus_vs_Standard:Code_quality_A2 0.616
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.34 on 694 degrees of freedom
## (20 observations deleted due to missingness)
## Multiple R-squared: 0.0546, Adjusted R-squared: 0.0505
## F-statistic: 13.4 on 3 and 694 DF, p-value: 0.0000000176
T test for quality A2
##
## Welch Two Sample t-test
##
## data: d$Code_quality_A1 by d$Condition
## t = -2, df = 706, p-value = 0.05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.151977 -0.000692
## sample estimates:
## mean in group Standard mean in group Plus
## 1.06 1.14
##
## Descriptive statistics by group
## group: Standard
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 359 1.06 0.52 1 1.08 0 0 2 2 0.08 0.59 0.03
## ------------------------------------------------------------
## group: Plus
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 349 1.14 0.5 1 1.14 0 0 2 2 0.25 0.5 0.03T test for cognitive process A2
##
## Welch Two Sample t-test
##
## data: d$cogproc_A2 by d$Condition
## t = -6, df = 701, p-value = 0.000000007
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.386 -0.691
## sample estimates:
## mean in group Standard mean in group Plus
## 13.1 14.1
##
## Descriptive statistics by group
## group: Standard
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 355 13.1 2.39 13.2 13.1 2.54 7.25 20.5 13.2 0.05 -0.42 0.13
## ------------------------------------------------------------
## group: Plus
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 348 14.1 2.3 14.2 14.1 2.26 5.13 22 16.9 -0.05 0.73 0.12Correlations between the two by group A2
| Code_quality_A2 | cogproc_A2 | |
|---|---|---|
| Code_quality_A2 | ||
| cogproc_A2 | 0.10 |
| Code_quality_A2 | cogproc_A2 | |
|---|---|---|
| Code_quality_A2 | ||
| cogproc_A2 | 0.06 |
##
## Call:
## lm(formula = cogproc_A2 ~ Condition * Code_quality_A2, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.269 -1.654 0.115 1.614 7.820
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 13.101 0.244 53.69
## ConditionPlus_vs_Standard 1.239 0.488 2.54
## Code_quality_A2 0.442 0.205 2.16
## ConditionPlus_vs_Standard:Code_quality_A2 -0.205 0.410 -0.50
## Pr(>|t|)
## (Intercept) <0.0000000000000002 ***
## ConditionPlus_vs_Standard 0.011 *
## Code_quality_A2 0.031 *
## ConditionPlus_vs_Standard:Code_quality_A2 0.616
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.34 on 694 degrees of freedom
## (20 observations deleted due to missingness)
## Multiple R-squared: 0.0546, Adjusted R-squared: 0.0505
## F-statistic: 13.4 on 3 and 694 DF, p-value: 0.0000000176