library(tidyr)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(stats)
library(nlme)
##
## Attaching package: 'nlme'
## The following object is masked from 'package:dplyr':
##
## collapse
setwd("C:/Users/Christina/Dropbox/UW Madison/Lupyan Lab")
data <- read.csv("HoutWithMemory.csv")
threeD_Mem1 <- lm(Mem1 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D + Vector.Distance._3D, data)
threeD_Mem2 <- lm(Mem2 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D + Vector.Distance._3D, data)
threeD_Mem4 <- lm(Mem4 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D + Vector.Distance._3D, data)
threeD_Mem8 <- lm(Mem8 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D + Vector.Distance._3D, data)
threeD_Mem16 <- lm(Mem16 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D + Vector.Distance._3D, data)
threeD_Slope <- lm(Slope ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D + Vector.Distance._3D, data)
summary(threeD_Mem1)
##
## Call:
## lm(formula = Mem1 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D +
## Vector.Distance._3D, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.60852 -0.12959 0.09598 0.11842 0.15330
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.447058 0.422151 3.428 0.000742 ***
## Stress_3D -0.457332 0.553782 -0.826 0.409908
## Weird.Mean._3D -0.279033 0.261889 -1.065 0.287985
## Proto.Distance._3D -0.007765 0.095329 -0.081 0.935167
## Vector.Distance._3D -0.307789 0.309190 -0.995 0.320742
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1716 on 195 degrees of freedom
## (40 observations deleted due to missingness)
## Multiple R-squared: 0.0143, Adjusted R-squared: -0.005918
## F-statistic: 0.7073 on 4 and 195 DF, p-value: 0.5878
summary(threeD_Mem2)
##
## Call:
## lm(formula = Mem2 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D +
## Vector.Distance._3D, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.5752 -0.1275 0.1069 0.1205 0.1644
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.20255 0.41071 2.928 0.00382 **
## Stress_3D -0.32895 0.53878 -0.611 0.54221
## Weird.Mean._3D -0.16334 0.25479 -0.641 0.52223
## Proto.Distance._3D 0.06966 0.09275 0.751 0.45354
## Vector.Distance._3D -0.21052 0.30081 -0.700 0.48487
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1669 on 195 degrees of freedom
## (40 observations deleted due to missingness)
## Multiple R-squared: 0.006253, Adjusted R-squared: -0.01413
## F-statistic: 0.3067 on 4 and 195 DF, p-value: 0.8732
summary(threeD_Mem4)
##
## Call:
## lm(formula = Mem4 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D +
## Vector.Distance._3D, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.5225 -0.1367 0.1084 0.1450 0.2038
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.36565 0.45690 2.989 0.00316 **
## Stress_3D -0.28008 0.59936 -0.467 0.64081
## Weird.Mean._3D -0.37967 0.28345 -1.339 0.18198
## Proto.Distance._3D -0.03782 0.10318 -0.367 0.71437
## Vector.Distance._3D -0.23415 0.33464 -0.700 0.48494
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1857 on 195 degrees of freedom
## (40 observations deleted due to missingness)
## Multiple R-squared: 0.0193, Adjusted R-squared: -0.0008186
## F-statistic: 0.9593 on 4 and 195 DF, p-value: 0.431
summary(threeD_Mem8)
##
## Call:
## lm(formula = Mem8 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D +
## Vector.Distance._3D, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.5939 -0.1363 0.1218 0.1825 0.2184
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.423485 0.528742 2.692 0.00772 **
## Stress_3D -0.673369 0.693610 -0.971 0.33284
## Weird.Mean._3D -0.075725 0.328016 -0.231 0.81767
## Proto.Distance._3D 0.005474 0.119399 0.046 0.96348
## Vector.Distance._3D -0.404500 0.387259 -1.045 0.29754
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2149 on 195 degrees of freedom
## (40 observations deleted due to missingness)
## Multiple R-squared: 0.008016, Adjusted R-squared: -0.01233
## F-statistic: 0.394 on 4 and 195 DF, p-value: 0.8128
summary(threeD_Mem16)
##
## Call:
## lm(formula = Mem16 ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D +
## Vector.Distance._3D, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.56881 -0.13530 -0.00571 0.18441 0.24391
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.12347 0.50077 2.243 0.026 *
## Stress_3D 0.05210 0.65692 0.079 0.937
## Weird.Mean._3D 0.25928 0.31066 0.835 0.405
## Proto.Distance._3D -0.05827 0.11308 -0.515 0.607
## Vector.Distance._3D -0.55050 0.36677 -1.501 0.135
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2035 on 195 degrees of freedom
## (40 observations deleted due to missingness)
## Multiple R-squared: 0.02327, Adjusted R-squared: 0.003231
## F-statistic: 1.161 on 4 and 195 DF, p-value: 0.3292
summary(threeD_Slope)
##
## Call:
## lm(formula = Slope ~ Stress_3D + Weird.Mean._3D + Proto.Distance._3D +
## Vector.Distance._3D, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -15.2175 -3.8401 0.8167 3.4068 12.6957
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.081 14.154 -0.288 0.773
## Stress_3D 6.528 18.567 0.352 0.726
## Weird.Mean._3D 11.661 8.781 1.328 0.186
## Proto.Distance._3D -1.620 3.196 -0.507 0.613
## Vector.Distance._3D -6.969 10.367 -0.672 0.502
##
## Residual standard error: 5.753 on 195 degrees of freedom
## (40 observations deleted due to missingness)
## Multiple R-squared: 0.01367, Adjusted R-squared: -0.00656
## F-statistic: 0.6758 on 4 and 195 DF, p-value: 0.6095