Regressions for Shari: Sex as Covariate
##
## Attaching package: 'reghelper'## The following object is masked from 'package:base':
##
## betaOutcome Variable: FRONTAL_wmlM2
#Fit the full model
##
## Call:
## lm(formula = FRONTAL_wmlM2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -991.24 -255.32 -79.62 102.92 2895.52
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -727.031 302.083 -2.407 0.01691 *
## Age.scan 17.897 5.449 3.284 0.00119 **
## Race2 -64.977 458.506 -0.142 0.88743
## PovStat2 444.436 625.709 0.710 0.47827
## Sex2 104.932 63.444 1.654 0.09956 .
## Age.scan:Race2 3.256 8.323 0.391 0.69600
## Age.scan:PovStat2 -7.565 11.661 -0.649 0.51718
## Race2:PovStat2 -1559.357 846.401 -1.842 0.06676 .
## Age.scan:Race2:PovStat2 32.189 16.255 1.980 0.04891 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 473 on 222 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.1875, Adjusted R-squared: 0.1583
## F-statistic: 6.405 on 8 and 222 DF, p-value: 1.738e-07#Stepwise regression model
##
## Call:
## lm(formula = FRONTAL_wmlM2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -991.24 -255.32 -79.62 102.92 2895.52
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -727.031 302.083 -2.407 0.01691 *
## Age.scan 17.897 5.449 3.284 0.00119 **
## Race2 -64.977 458.506 -0.142 0.88743
## PovStat2 444.436 625.709 0.710 0.47827
## Sex2 104.932 63.444 1.654 0.09956 .
## Age.scan:Race2 3.256 8.323 0.391 0.69600
## Age.scan:PovStat2 -7.565 11.661 -0.649 0.51718
## Race2:PovStat2 -1559.357 846.401 -1.842 0.06676 .
## Age.scan:Race2:PovStat2 32.189 16.255 1.980 0.04891 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 473 on 222 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.1875, Adjusted R-squared: 0.1583
## F-statistic: 6.405 on 8 and 222 DF, p-value: 1.738e-07
Outcome Variable: WM_FA2
#Fit the full model
##
## Call:
## lm(formula = WM_FA2 ~ (Age.scan + Race + PovStat)^3 + Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.052535 -0.011433 0.000304 0.010841 0.100554
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2889752 0.0804900 3.590 0.000414 ***
## Age.scan 0.0031447 0.0014815 2.123 0.034989 *
## Race 0.0946886 0.0512839 1.846 0.066295 .
## PovStat 0.1272794 0.0589570 2.159 0.032035 *
## Sex -0.0034525 0.0028887 -1.195 0.233420
## Age.scan:Race -0.0020375 0.0009602 -2.122 0.035057 *
## Age.scan:PovStat -0.0026209 0.0011056 -2.371 0.018693 *
## Race:PovStat -0.0715182 0.0367354 -1.947 0.052933 .
## Age.scan:Race:PovStat 0.0014603 0.0007032 2.077 0.039088 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02059 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.09206, Adjusted R-squared: 0.05627
## F-statistic: 2.573 on 8 and 203 DF, p-value: 0.01076#Stepwise regression model
##
## Call:
## lm(formula = WM_FA2 ~ Age.scan + Race + PovStat + Age.scan:Race +
## Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.05416 -0.01128 0.00001 0.01123 0.10177
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2756618 0.0797991 3.454 0.000671 ***
## Age.scan 0.0032838 0.0014784 2.221 0.027441 *
## Race 0.1000686 0.0511395 1.957 0.051738 .
## PovStat 0.1330429 0.0588211 2.262 0.024763 *
## Age.scan:Race -0.0021389 0.0009575 -2.234 0.026577 *
## Age.scan:PovStat -0.0027175 0.0011038 -2.462 0.014646 *
## Race:PovStat -0.0752612 0.0366401 -2.054 0.041244 *
## Age.scan:Race:PovStat 0.0015314 0.0007014 2.183 0.030161 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02061 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.08567, Adjusted R-squared: 0.05429
## F-statistic: 2.73 on 7 and 204 DF, p-value: 0.009938
Outcome Variable: DEEP_WM_FA2
#Fit the full model
##
## Call:
## lm(formula = DEEP_WM_FA2 ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.135517 -0.013782 0.002252 0.015659 0.081369
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.282e-01 5.037e-02 12.471 <2e-16 ***
## Age.scan -1.471e-04 8.303e-04 -0.177 0.8596
## Race -5.393e-02 2.645e-02 -2.039 0.0427 *
## PovStat 4.403e-05 2.888e-02 0.002 0.9988
## Sex -1.610e-03 3.759e-03 -0.428 0.6688
## Age.scan:Race 4.349e-04 4.144e-04 1.050 0.2952
## Age.scan:PovStat -3.166e-04 4.575e-04 -0.692 0.4898
## Race:PovStat 1.063e-02 8.341e-03 1.275 0.2039
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02689 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1004, Adjusted R-squared: 0.06949
## F-statistic: 3.251 on 7 and 204 DF, p-value: 0.00271#Stepwise regression model
##
## Call:
## lm(formula = DEEP_WM_FA2 ~ Race, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.141974 -0.013346 0.002485 0.015829 0.075941
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.595890 0.005552 107.334 < 2e-16 ***
## Race -0.016598 0.003753 -4.423 1.56e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02672 on 210 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.08521, Adjusted R-squared: 0.08086
## F-statistic: 19.56 on 1 and 210 DF, p-value: 1.563e-05Outcome Variable: FRONTAL_WM_L_FA2
#Fit the full model
##
## Call:
## lm(formula = FRONTAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^2 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.06710 -0.01374 0.00135 0.01144 0.10661
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4352145 0.0437472 9.948 <2e-16 ***
## Age.scan 0.0001879 0.0007211 0.261 0.795
## Race 0.0025995 0.0229727 0.113 0.910
## PovStat 0.0074956 0.0250833 0.299 0.765
## Sex -0.0037100 0.0032643 -1.137 0.257
## Age.scan:Race -0.0003152 0.0003599 -0.876 0.382
## Age.scan:PovStat -0.0004344 0.0003974 -1.093 0.276
## Race:PovStat 0.0064857 0.0072438 0.895 0.372
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02335 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.127, Adjusted R-squared: 0.09706
## F-statistic: 4.24 on 7 and 204 DF, p-value: 0.0002159#Stepwise regression model
##
## Call:
## lm(formula = FRONTAL_WM_L_FA2 ~ Age.scan + Race + PovStat + Age.scan:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.070835 -0.013848 0.000327 0.012604 0.104930
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4340363 0.0282839 15.346 <2e-16 ***
## Age.scan -0.0001444 0.0005307 -0.272 0.786
## Race -0.0053421 0.0033824 -1.579 0.116
## PovStat 0.0237014 0.0202220 1.172 0.243
## Age.scan:PovStat -0.0005486 0.0003858 -1.422 0.157
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02337 on 207 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1133, Adjusted R-squared: 0.09612
## F-statistic: 6.609 on 4 and 207 DF, p-value: 5.034e-05Outcome Variable: FRONTAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = FRONTAL_WM_R_FA2 ~ (Age.scan + Race + PovStat)^2 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.065961 -0.014002 0.000283 0.013037 0.113296
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4197520 0.0462191 9.082 <2e-16 ***
## Age.scan 0.0006270 0.0007618 0.823 0.411
## Race 0.0094567 0.0242707 0.390 0.697
## PovStat 0.0176586 0.0265006 0.666 0.506
## Sex -0.0025391 0.0034487 -0.736 0.462
## Age.scan:Race -0.0004302 0.0003802 -1.131 0.259
## Age.scan:PovStat -0.0005423 0.0004198 -1.292 0.198
## Race:PovStat 0.0025220 0.0076531 0.330 0.742
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02467 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1096, Adjusted R-squared: 0.07908
## F-statistic: 3.588 on 7 and 204 DF, p-value: 0.001151#Stepwise regression model
##
## Call:
## lm(formula = FRONTAL_WM_R_FA2 ~ Age.scan + Race + PovStat + Age.scan:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.067924 -0.013968 -0.000235 0.013707 0.112231
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.383e-01 2.980e-02 14.705 < 2e-16 ***
## Age.scan 9.819e-05 5.592e-04 0.176 0.86078
## Race -9.850e-03 3.564e-03 -2.764 0.00623 **
## PovStat 2.651e-02 2.131e-02 1.244 0.21489
## Age.scan:PovStat -6.256e-04 4.065e-04 -1.539 0.12540
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02462 on 207 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1003, Adjusted R-squared: 0.0829
## F-statistic: 5.768 on 4 and 207 DF, p-value: 0.0002023Outcome Variable: TEMPORAL_WM_L_FA2
#Fit the full model
##
## Call:
## lm(formula = TEMPORAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.047989 -0.014655 -0.000037 0.013166 0.105225
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2714353 0.0833190 3.258 0.00132 **
## Age.scan 0.0031626 0.0015335 2.062 0.04045 *
## Race 0.1029552 0.0530864 1.939 0.05384 .
## PovStat 0.1346404 0.0610292 2.206 0.02849 *
## Sex -0.0056428 0.0029903 -1.887 0.06058 .
## Age.scan:Race -0.0020950 0.0009940 -2.108 0.03628 *
## Age.scan:PovStat -0.0026992 0.0011444 -2.359 0.01929 *
## Race:PovStat -0.0789720 0.0380266 -2.077 0.03908 *
## Age.scan:Race:PovStat 0.0015802 0.0007279 2.171 0.03111 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02132 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.07333, Adjusted R-squared: 0.03681
## F-statistic: 2.008 on 8 and 203 DF, p-value: 0.0471#Stepwise regression model
##
## Call:
## lm(formula = TEMPORAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.047989 -0.014655 -0.000037 0.013166 0.105225
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2714353 0.0833190 3.258 0.00132 **
## Age.scan 0.0031626 0.0015335 2.062 0.04045 *
## Race 0.1029552 0.0530864 1.939 0.05384 .
## PovStat 0.1346404 0.0610292 2.206 0.02849 *
## Sex -0.0056428 0.0029903 -1.887 0.06058 .
## Age.scan:Race -0.0020950 0.0009940 -2.108 0.03628 *
## Age.scan:PovStat -0.0026992 0.0011444 -2.359 0.01929 *
## Race:PovStat -0.0789720 0.0380266 -2.077 0.03908 *
## Age.scan:Race:PovStat 0.0015802 0.0007279 2.171 0.03111 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02132 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.07333, Adjusted R-squared: 0.03681
## F-statistic: 2.008 on 8 and 203 DF, p-value: 0.0471
## █████████████████████ While Race (2nd moderator) = 1.00 (1) ████████████████████
##
## JOHNSON-NEYMAN INTERVAL
##
## When PovStat is OUTSIDE the interval [-1.89, 1.35], the slope of Age.scan
## is p < .05.
##
## Note: The range of observed values of PovStat is [1.00, 2.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Age.scan when PovStat = 1.00 (1):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.00 0.00 -0.20 0.84
##
## Slope of Age.scan when PovStat = 2.00 (2):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.00 0.00 -2.65 0.01
##
## █████████████████████ While Race (2nd moderator) = 2.00 (2) ████████████████████
##
## JOHNSON-NEYMAN INTERVAL
##
## The Johnson-Neyman interval could not be found. Is the p value for your
## interaction term below the specified alpha?
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of Age.scan when PovStat = 1.00 (1):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.00 0.00 -1.92 0.06
##
## Slope of Age.scan when PovStat = 2.00 (2):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.00 0.00 -0.25 0.80
Outcome Variable: TEMPORAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = TEMPORAL_WM_R_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.057682 -0.014044 0.000046 0.011757 0.096960
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2847783 0.0897697 3.172 0.00175 **
## Age.scan 0.0029957 0.0016523 1.813 0.07130 .
## Race 0.0875031 0.0571964 1.530 0.12761
## PovStat 0.1314569 0.0657542 1.999 0.04692 *
## Sex -0.0044494 0.0032218 -1.381 0.16878
## Age.scan:Race -0.0018702 0.0010709 -1.746 0.08226 .
## Age.scan:PovStat -0.0026738 0.0012330 -2.169 0.03128 *
## Race:PovStat -0.0696113 0.0409706 -1.699 0.09084 .
## Age.scan:Race:PovStat 0.0014545 0.0007843 1.855 0.06510 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02297 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.06957, Adjusted R-squared: 0.0329
## F-statistic: 1.897 on 8 and 203 DF, p-value: 0.06209#Stepwise regression model
##
## Call:
## lm(formula = TEMPORAL_WM_R_FA2 ~ Age.scan + Race + PovStat +
## Age.scan:Race + Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.055569 -0.013985 -0.000533 0.011952 0.098533
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2676205 0.0891033 3.003 0.0030 **
## Age.scan 0.0031749 0.0016508 1.923 0.0558 .
## Race 0.0944367 0.0571022 1.654 0.0997 .
## PovStat 0.1388847 0.0656794 2.115 0.0357 *
## Age.scan:Race -0.0020008 0.0010691 -1.871 0.0627 .
## Age.scan:PovStat -0.0027983 0.0012325 -2.270 0.0242 *
## Race:PovStat -0.0744352 0.0409121 -1.819 0.0703 .
## Age.scan:Race:PovStat 0.0015460 0.0007832 1.974 0.0497 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02302 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.06083, Adjusted R-squared: 0.0286
## F-statistic: 1.887 on 7 and 204 DF, p-value: 0.07315
Outcome Variable: PARIETAL_WM_L_FA2
#Fit the full model
##
## Call:
## lm(formula = PARIETAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.058859 -0.011886 0.000404 0.013074 0.116413
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.326869 0.088590 3.690 0.000288 ***
## Age.scan 0.002631 0.001631 1.614 0.108139
## Race 0.077089 0.056445 1.366 0.173532
## PovStat 0.101830 0.064890 1.569 0.118143
## Sex -0.008717 0.003179 -2.742 0.006657 **
## Age.scan:Race -0.001816 0.001057 -1.718 0.087353 .
## Age.scan:PovStat -0.002218 0.001217 -1.823 0.069805 .
## Race:PovStat -0.059565 0.040432 -1.473 0.142241
## Age.scan:Race:PovStat 0.001287 0.000774 1.663 0.097899 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02266 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1114, Adjusted R-squared: 0.07636
## F-statistic: 3.18 on 8 and 203 DF, p-value: 0.002025#Stepwise regression model
##
## Call:
## lm(formula = PARIETAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.058859 -0.011886 0.000404 0.013074 0.116413
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.326869 0.088590 3.690 0.000288 ***
## Age.scan 0.002631 0.001631 1.614 0.108139
## Race 0.077089 0.056445 1.366 0.173532
## PovStat 0.101830 0.064890 1.569 0.118143
## Sex -0.008717 0.003179 -2.742 0.006657 **
## Age.scan:Race -0.001816 0.001057 -1.718 0.087353 .
## Age.scan:PovStat -0.002218 0.001217 -1.823 0.069805 .
## Race:PovStat -0.059565 0.040432 -1.473 0.142241
## Age.scan:Race:PovStat 0.001287 0.000774 1.663 0.097899 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02266 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1114, Adjusted R-squared: 0.07636
## F-statistic: 3.18 on 8 and 203 DF, p-value: 0.002025Outcome Variable: PARIETAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = PARIETAL_WM_R_FA2 ~ (Age.scan + Race + PovStat)^2 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.06509 -0.01481 -0.00035 0.01258 0.10612
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.660e-01 4.534e-02 10.276 <2e-16 ***
## Age.scan 5.211e-05 7.474e-04 0.070 0.944
## Race -1.591e-02 2.381e-02 -0.668 0.505
## PovStat -2.237e-03 2.600e-02 -0.086 0.932
## Sex -2.649e-03 3.383e-03 -0.783 0.435
## Age.scan:Race -5.234e-05 3.730e-04 -0.140 0.889
## Age.scan:PovStat -2.712e-04 4.119e-04 -0.658 0.511
## Race:PovStat 8.443e-03 7.508e-03 1.125 0.262
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02421 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.0534, Adjusted R-squared: 0.02092
## F-statistic: 1.644 on 7 and 204 DF, p-value: 0.1248#Stepwise regression model
##
## Call:
## lm(formula = PARIETAL_WM_R_FA2 ~ Age.scan + Race, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.066727 -0.013534 -0.001029 0.015123 0.101875
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4627633 0.0113932 40.617 <2e-16 ***
## Age.scan -0.0003712 0.0001804 -2.058 0.0409 *
## Race -0.0073334 0.0034279 -2.139 0.0336 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02414 on 209 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.0354, Adjusted R-squared: 0.02617
## F-statistic: 3.835 on 2 and 209 DF, p-value: 0.02314Outcome Variable: OCCIPITAL_WM_L_FA2
#Fit the full model
##
## Call:
## lm(formula = OCCIPITAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.070434 -0.014847 -0.000655 0.015311 0.125044
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2277629 0.0977239 2.331 0.0208 *
## Age.scan 0.0040156 0.0017987 2.233 0.0267 *
## Race 0.0972500 0.0622644 1.562 0.1199
## PovStat 0.1462892 0.0715805 2.044 0.0423 *
## Sex -0.0033594 0.0035072 -0.958 0.3393
## Age.scan:Race -0.0022939 0.0011658 -1.968 0.0505 .
## Age.scan:PovStat -0.0030617 0.0013423 -2.281 0.0236 *
## Race:PovStat -0.0779559 0.0446009 -1.748 0.0820 .
## Age.scan:Race:PovStat 0.0016342 0.0008538 1.914 0.0570 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.025 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1066, Adjusted R-squared: 0.07142
## F-statistic: 3.028 on 8 and 203 DF, p-value: 0.003092#Stepwise regression model
##
## Call:
## lm(formula = OCCIPITAL_WM_L_FA2 ~ Age.scan + Race + PovStat +
## Age.scan:Race + Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.07251 -0.01444 -0.00106 0.01459 0.12623
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2148084 0.0967639 2.220 0.0275 *
## Age.scan 0.0041509 0.0017927 2.315 0.0216 *
## Race 0.1024850 0.0620115 1.653 0.0999 .
## PovStat 0.1518973 0.0713262 2.130 0.0344 *
## Age.scan:Race -0.0023925 0.0011610 -2.061 0.0406 *
## Age.scan:PovStat -0.0031557 0.0013384 -2.358 0.0193 *
## Race:PovStat -0.0815980 0.0444295 -1.837 0.0677 .
## Age.scan:Race:PovStat 0.0017033 0.0008505 2.003 0.0465 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.025 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1026, Adjusted R-squared: 0.07179
## F-statistic: 3.331 on 7 and 204 DF, p-value: 0.002213Outcome Variable: OCCIPITAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = OCCIPITAL_WM_L_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.070434 -0.014847 -0.000655 0.015311 0.125044
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2277629 0.0977239 2.331 0.0208 *
## Age.scan 0.0040156 0.0017987 2.233 0.0267 *
## Race 0.0972500 0.0622644 1.562 0.1199
## PovStat 0.1462892 0.0715805 2.044 0.0423 *
## Sex -0.0033594 0.0035072 -0.958 0.3393
## Age.scan:Race -0.0022939 0.0011658 -1.968 0.0505 .
## Age.scan:PovStat -0.0030617 0.0013423 -2.281 0.0236 *
## Race:PovStat -0.0779559 0.0446009 -1.748 0.0820 .
## Age.scan:Race:PovStat 0.0016342 0.0008538 1.914 0.0570 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.025 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1066, Adjusted R-squared: 0.07142
## F-statistic: 3.028 on 8 and 203 DF, p-value: 0.003092#Stepwise regression model
##
## Call:
## lm(formula = OCCIPITAL_WM_L_FA2 ~ Age.scan + Race + PovStat +
## Age.scan:Race + Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.07251 -0.01444 -0.00106 0.01459 0.12623
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2148084 0.0967639 2.220 0.0275 *
## Age.scan 0.0041509 0.0017927 2.315 0.0216 *
## Race 0.1024850 0.0620115 1.653 0.0999 .
## PovStat 0.1518973 0.0713262 2.130 0.0344 *
## Age.scan:Race -0.0023925 0.0011610 -2.061 0.0406 *
## Age.scan:PovStat -0.0031557 0.0013384 -2.358 0.0193 *
## Race:PovStat -0.0815980 0.0444295 -1.837 0.0677 .
## Age.scan:Race:PovStat 0.0017033 0.0008505 2.003 0.0465 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.025 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1026, Adjusted R-squared: 0.07179
## F-statistic: 3.331 on 7 and 204 DF, p-value: 0.002213Outcome Variable: CORPUS_CALLOSUM_FA2
#Fit the full model
##
## Call:
## lm(formula = CORPUS_CALLOSUM_FA2 ~ (Age.scan + Race + PovStat)^3 +
## Sex, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.096226 -0.014525 0.004835 0.019002 0.064445
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3921155 0.1095745 3.579 0.000432 ***
## Age.scan 0.0050551 0.0020168 2.507 0.012977 *
## Race 0.1264459 0.0698149 1.811 0.071595 .
## PovStat 0.2012326 0.0802607 2.507 0.012952 *
## Sex -0.0053976 0.0039325 -1.373 0.171404
## Age.scan:Race -0.0026245 0.0013072 -2.008 0.045993 *
## Age.scan:PovStat -0.0041038 0.0015050 -2.727 0.006956 **
## Race:PovStat -0.1047821 0.0500095 -2.095 0.037389 *
## Age.scan:Race:PovStat 0.0020901 0.0009573 2.183 0.030160 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02803 on 203 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.07792, Adjusted R-squared: 0.04158
## F-statistic: 2.144 on 8 and 203 DF, p-value: 0.0333#Stepwise regression model
##
## Call:
## lm(formula = CORPUS_CALLOSUM_FA2 ~ Age.scan + Race + PovStat +
## Age.scan:Race + Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.099569 -0.015116 0.004834 0.018742 0.061018
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3713012 0.1087549 3.414 0.000772 ***
## Age.scan 0.0052725 0.0020149 2.617 0.009541 **
## Race 0.1348570 0.0696960 1.935 0.054381 .
## PovStat 0.2102434 0.0801649 2.623 0.009384 **
## Age.scan:Race -0.0027830 0.0013049 -2.133 0.034141 *
## Age.scan:PovStat -0.0042548 0.0015043 -2.829 0.005143 **
## Race:PovStat -0.1106340 0.0499352 -2.216 0.027828 *
## Age.scan:Race:PovStat 0.0022011 0.0009559 2.303 0.022312 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02809 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.06936, Adjusted R-squared: 0.03742
## F-statistic: 2.172 on 7 and 204 DF, p-value: 0.03808
Outcome Variable:Fx_L_FA
#Fit the full model
##
## Call:
## lm(formula = Fx_L_FA ~ (Age.scan + Race + PovStat)^2 + Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19902 -0.04179 0.00476 0.03998 0.26415
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3140029 0.0433036 7.251 6.51e-12 ***
## Age.scan -0.0012767 0.0007826 -1.631 0.10421
## Race2 -0.0102294 0.0593043 -0.172 0.86321
## PovStat2 0.0970629 0.0663086 1.464 0.14464
## Sex2 -0.0273378 0.0096937 -2.820 0.00523 **
## Age.scan:Race2 0.0001278 0.0010731 0.119 0.90529
## Age.scan:PovStat2 -0.0020294 0.0012152 -1.670 0.09630 .
## Race2:PovStat2 -0.0047373 0.0217868 -0.217 0.82806
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0728 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0864, Adjusted R-squared: 0.05811
## F-statistic: 3.053 on 7 and 226 DF, p-value: 0.00433#Stepwise regression model
##
## Call:
## lm(formula = Fx_L_FA ~ Age.scan + PovStat + Sex + Age.scan:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.197208 -0.043558 0.003096 0.041505 0.262492
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3097377 0.0343130 9.027 < 2e-16 ***
## Age.scan -0.0012200 0.0006182 -1.974 0.04963 *
## PovStat2 0.0848411 0.0600611 1.413 0.15914
## Sex2 -0.0272598 0.0096342 -2.829 0.00508 **
## Age.scan:PovStat2 -0.0018520 0.0011551 -1.603 0.11022
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07237 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0851, Adjusted R-squared: 0.06912
## F-statistic: 5.325 on 4 and 229 DF, p-value: 0.0004058Outcome Variable:Fx_R_FA
#Fit the full model
##
## Call:
## lm(formula = Fx_R_FA ~ (Age.scan + Race + PovStat)^2 + Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.217408 -0.035446 0.000137 0.033014 0.133646
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4047062 0.0306779 13.192 < 2e-16 ***
## Age.scan -0.0017786 0.0005544 -3.208 0.00153 **
## Race2 0.0072887 0.0420134 0.173 0.86243
## PovStat2 0.0046925 0.0469756 0.100 0.92052
## Sex2 -0.0167158 0.0068674 -2.434 0.01570 *
## Age.scan:Race2 -0.0003200 0.0007602 -0.421 0.67419
## Age.scan:PovStat2 -0.0002431 0.0008609 -0.282 0.77789
## Race2:PovStat2 0.0050609 0.0154346 0.328 0.74330
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05157 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.136, Adjusted R-squared: 0.1092
## F-statistic: 5.082 on 7 and 226 DF, p-value: 2.234e-05#Stepwise regression model
##
## Call:
## lm(formula = Fx_R_FA ~ Age.scan + Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.222854 -0.032001 0.002356 0.032440 0.125053
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4059766 0.0196110 20.702 < 2e-16 ***
## Age.scan -0.0019120 0.0003623 -5.277 3.02e-07 ***
## Sex2 -0.0157007 0.0067406 -2.329 0.0207 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05128 on 231 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1269, Adjusted R-squared: 0.1193
## F-statistic: 16.78 on 2 and 231 DF, p-value: 1.564e-07Outcome Variable:ALIC_L_FA
#Fit the full model
##
## Call:
## lm(formula = ALIC_L_FA ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.16656 -0.01544 0.00145 0.01835 0.06116
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3841831 0.0169234 22.701 <2e-16 ***
## Age.scan -0.0001562 0.0003059 -0.511 0.610
## Race2 0.0066215 0.0231766 0.286 0.775
## PovStat2 -0.0008750 0.0259139 -0.034 0.973
## Sex2 0.0019084 0.0037884 0.504 0.615
## Age.scan:Race2 -0.0003028 0.0004194 -0.722 0.471
## Age.scan:PovStat2 -0.0002057 0.0004749 -0.433 0.665
## Race2:PovStat2 0.0061181 0.0085144 0.719 0.473
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02845 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.05252, Adjusted R-squared: 0.02317
## F-statistic: 1.789 on 7 and 226 DF, p-value: 0.09035#Stepwise regression model
##
## Call:
## lm(formula = ALIC_L_FA ~ Age.scan + Race + PovStat, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.164600 -0.015471 0.001474 0.018771 0.061085
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3964512 0.0115595 34.297 <2e-16 ***
## Age.scan -0.0003833 0.0002055 -1.865 0.0634 .
## Race2 -0.0069778 0.0038444 -1.815 0.0708 .
## PovStat2 -0.0085828 0.0040713 -2.108 0.0361 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02833 on 230 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04401, Adjusted R-squared: 0.03154
## F-statistic: 3.53 on 3 and 230 DF, p-value: 0.01563Outcome Variable:ALIC_R_FA
#Fit the full model
##
## Call:
## lm(formula = ALIC_R_FA ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.146550 -0.012973 0.003371 0.014738 0.062521
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4400261 0.0166163 26.482 <2e-16 ***
## Age.scan -0.0004549 0.0003003 -1.515 0.1312
## Race2 -0.0159455 0.0227561 -0.701 0.4842
## PovStat2 0.0122705 0.0254437 0.482 0.6301
## Sex2 0.0042604 0.0037196 1.145 0.2533
## Age.scan:Race2 -0.0000356 0.0004118 -0.086 0.9312
## Age.scan:PovStat2 -0.0005317 0.0004663 -1.140 0.2553
## Race2:PovStat2 0.0210509 0.0083600 2.518 0.0125 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02793 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1181, Adjusted R-squared: 0.09073
## F-statistic: 4.322 on 7 and 226 DF, p-value: 0.0001641#Stepwise regression model
##
## Call:
## lm(formula = ALIC_R_FA ~ Age.scan + Race + PovStat + Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.148777 -0.011690 0.002866 0.015831 0.060464
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4509161 0.0114087 39.524 < 2e-16 ***
## Age.scan -0.0006161 0.0002047 -3.010 0.002902 **
## Race2 -0.0179517 0.0046698 -3.844 0.000157 ***
## PovStat2 -0.0168700 0.0054154 -3.115 0.002073 **
## Race2:PovStat2 0.0234865 0.0079864 2.941 0.003609 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02791 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1076, Adjusted R-squared: 0.09199
## F-statistic: 6.901 on 4 and 229 DF, p-value: 2.915e-05Outcome Variable:EC_L_FA
#Fit the full model
##
## Call:
## lm(formula = EC_L_FA ~ (Age.scan + Race + PovStat)^3 + Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.106380 -0.011930 0.000519 0.013639 0.052713
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2741931 0.0129033 21.250 <2e-16 ***
## Age.scan -0.0002792 0.0002331 -1.197 0.2324
## Race2 0.0171206 0.0192677 0.889 0.3752
## PovStat2 0.0346569 0.0260075 1.333 0.1840
## Sex2 -0.0004726 0.0027191 -0.174 0.8622
## Age.scan:Race2 -0.0005218 0.0003506 -1.488 0.1381
## Age.scan:PovStat2 -0.0008122 0.0004816 -1.686 0.0931 .
## Race2:PovStat2 -0.0592476 0.0355503 -1.667 0.0970 .
## Age.scan:Race2:PovStat2 0.0013097 0.0006816 1.921 0.0559 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02036 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1189, Adjusted R-squared: 0.08759
## F-statistic: 3.796 on 8 and 225 DF, p-value: 0.0003356#Stepwise regression model
##
## Call:
## lm(formula = EC_L_FA ~ Age.scan + Race + PovStat + Age.scan:Race +
## Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.106150 -0.012141 0.000713 0.013804 0.052843
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2738571 0.0127303 21.512 <2e-16 ***
## Age.scan -0.0002774 0.0002324 -1.194 0.2339
## Race2 0.0173129 0.0191946 0.902 0.3680
## PovStat2 0.0349326 0.0259034 1.349 0.1788
## Age.scan:Race2 -0.0005251 0.0003493 -1.503 0.1341
## Age.scan:PovStat2 -0.0008158 0.0004801 -1.699 0.0907 .
## Race2:PovStat2 -0.0597361 0.0353629 -1.689 0.0926 .
## Age.scan:Race2:PovStat2 0.0013190 0.0006780 1.945 0.0530 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02031 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1188, Adjusted R-squared: 0.0915
## F-statistic: 4.353 on 7 and 226 DF, p-value: 0.0001513Outcome Variable:EC_R_FA
#Fit the full model
##
## Call:
## lm(formula = EC_R_FA ~ (Age.scan + Race + PovStat)^3 + Sex, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.09239 -0.01343 0.00006 0.01812 0.06187
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3164475 0.0156538 20.215 <2e-16 ***
## Age.scan -0.0002515 0.0002828 -0.889 0.3749
## Race2 0.0014895 0.0233750 0.064 0.9492
## PovStat2 0.0477752 0.0315515 1.514 0.1314
## Sex2 0.0027273 0.0032987 0.827 0.4092
## Age.scan:Race2 -0.0002837 0.0004253 -0.667 0.5054
## Age.scan:PovStat2 -0.0010676 0.0005843 -1.827 0.0690 .
## Race2:PovStat2 -0.0827842 0.0431286 -1.919 0.0562 .
## Age.scan:Race2:PovStat2 0.0017850 0.0008269 2.159 0.0319 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0247 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1007, Adjusted R-squared: 0.06873
## F-statistic: 3.15 on 8 and 225 DF, p-value: 0.002123#Stepwise regression model
##
## Call:
## lm(formula = EC_R_FA ~ Age.scan + Race + PovStat + Age.scan:Race +
## Age.scan:PovStat + Race:PovStat + Age.scan:Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.093670 -0.013683 0.000078 0.018006 0.060486
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3183860 0.0154664 20.586 <2e-16 ***
## Age.scan -0.0002616 0.0002824 -0.927 0.3552
## Race2 0.0003797 0.0233201 0.016 0.9870
## PovStat2 0.0461842 0.0314707 1.468 0.1436
## Age.scan:Race2 -0.0002641 0.0004244 -0.622 0.5343
## Age.scan:PovStat2 -0.0010469 0.0005833 -1.795 0.0740 .
## Race2:PovStat2 -0.0799652 0.0429635 -1.861 0.0640 .
## Age.scan:Race2:PovStat2 0.0017312 0.0008238 2.102 0.0367 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02468 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.09798, Adjusted R-squared: 0.07004
## F-statistic: 3.507 on 7 and 226 DF, p-value: 0.001362Outcome Variable:CGC_L_FA
#Fit the full model
##
## Call:
## lm(formula = CGC_L_FA ~ (Age.scan + Race + PovStat)^3 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073020 -0.016488 0.000559 0.017840 0.065342
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3016438 0.0167491 18.010 <2e-16 ***
## Age.scan -0.0002948 0.0003026 -0.974 0.331
## Race2 0.0070351 0.0250104 0.281 0.779
## PovStat2 0.0077747 0.0337590 0.230 0.818
## Sex2 0.0023726 0.0035295 0.672 0.502
## Age.scan:Race2 -0.0002764 0.0004551 -0.607 0.544
## Age.scan:PovStat2 -0.0003661 0.0006252 -0.586 0.559
## Race2:PovStat2 -0.0470591 0.0461461 -1.020 0.309
## Age.scan:Race2:PovStat2 0.0012230 0.0008848 1.382 0.168
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02642 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.05309, Adjusted R-squared: 0.01942
## F-statistic: 1.577 on 8 and 225 DF, p-value: 0.1328#Stepwise regression model
##
## Call:
## lm(formula = CGC_L_FA ~ Age.scan + Race + PovStat + Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073949 -0.017634 0.001306 0.018513 0.064401
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3060402 0.0107655 28.428 <2e-16 ***
## Age.scan -0.0003537 0.0001931 -1.831 0.0683 .
## Race2 -0.0079590 0.0044065 -1.806 0.0722 .
## PovStat2 -0.0121376 0.0051101 -2.375 0.0184 *
## Race2:PovStat2 0.0146079 0.0075361 1.938 0.0538 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02634 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04231, Adjusted R-squared: 0.02558
## F-statistic: 2.529 on 4 and 229 DF, p-value: 0.0414#Re-run with only 2-way interactions
##
## Call:
## lm(formula = CGC_L_FA ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073013 -0.017318 0.001329 0.019652 0.063686
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.096e-01 1.575e-02 19.660 <2e-16 ***
## Age.scan -4.390e-04 2.846e-04 -1.542 0.1244
## Race2 -1.057e-02 2.157e-02 -0.490 0.6247
## PovStat2 -2.495e-02 2.412e-02 -1.034 0.3020
## Sex2 1.988e-03 3.526e-03 0.564 0.5734
## Age.scan:Race2 4.891e-05 3.903e-04 0.125 0.9004
## Age.scan:PovStat2 2.463e-04 4.420e-04 0.557 0.5779
## Race2:PovStat2 1.578e-02 7.924e-03 1.992 0.0476 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02648 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04505, Adjusted R-squared: 0.01547
## F-statistic: 1.523 on 7 and 226 DF, p-value: 0.1604##
## Call:
## lm(formula = CGC_L_FA ~ Age.scan + Race + PovStat + Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073949 -0.017634 0.001306 0.018513 0.064401
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3060402 0.0107655 28.428 <2e-16 ***
## Age.scan -0.0003537 0.0001931 -1.831 0.0683 .
## Race2 -0.0079590 0.0044065 -1.806 0.0722 .
## PovStat2 -0.0121376 0.0051101 -2.375 0.0184 *
## Race2:PovStat2 0.0146079 0.0075361 1.938 0.0538 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02634 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04231, Adjusted R-squared: 0.02558
## F-statistic: 2.529 on 4 and 229 DF, p-value: 0.0414Outcome Variable:CGC_R_FA
#Fit the full model
##
## Call:
## lm(formula = CGC_R_FA ~ (Age.scan + Race + PovStat)^3 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.121031 -0.016273 0.003231 0.017718 0.074064
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.971e-01 1.753e-02 16.945 <2e-16 ***
## Age.scan -3.667e-04 3.167e-04 -1.158 0.248
## Race2 1.428e-02 2.618e-02 0.545 0.586
## PovStat2 -1.660e-02 3.533e-02 -0.470 0.639
## Sex2 -8.572e-04 3.694e-03 -0.232 0.817
## Age.scan:Race2 -3.737e-04 4.763e-04 -0.784 0.434
## Age.scan:PovStat2 8.853e-05 6.544e-04 0.135 0.893
## Race2:PovStat2 -1.991e-02 4.830e-02 -0.412 0.681
## Age.scan:Race2:PovStat2 6.705e-04 9.261e-04 0.724 0.470
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02766 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04749, Adjusted R-squared: 0.01362
## F-statistic: 1.402 on 8 and 225 DF, p-value: 0.1965#Stepwise regression model
##
## Call:
## lm(formula = CGC_R_FA ~ Age.scan + Race + PovStat + Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.120267 -0.015757 0.003801 0.017831 0.074684
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2996896 0.0112451 26.651 <2e-16 ***
## Age.scan -0.0004235 0.0002017 -2.100 0.0369 *
## Race2 -0.0059142 0.0046028 -1.285 0.2001
## PovStat2 -0.0118036 0.0053377 -2.211 0.0280 *
## Race2:PovStat2 0.0135494 0.0078718 1.721 0.0866 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02751 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04055, Adjusted R-squared: 0.02379
## F-statistic: 2.42 on 4 and 229 DF, p-value: 0.04933#Re-run with only 2-way interactions
##
## Call:
## lm(formula = CGC_R_FA ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.121027 -0.015621 0.003505 0.018604 0.074211
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3014401 0.0164344 18.342 <2e-16 ***
## Age.scan -0.0004458 0.0002970 -1.501 0.1347
## Race2 0.0046269 0.0225069 0.206 0.8373
## PovStat2 -0.0345383 0.0251652 -1.372 0.1713
## Sex2 -0.0010679 0.0036789 -0.290 0.7719
## Age.scan:Race2 -0.0001953 0.0004073 -0.480 0.6320
## Age.scan:PovStat2 0.0004243 0.0004612 0.920 0.3586
## Race2:PovStat2 0.0145466 0.0082684 1.759 0.0799 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02763 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04527, Adjusted R-squared: 0.0157
## F-statistic: 1.531 on 7 and 226 DF, p-value: 0.1578##
## Call:
## lm(formula = CGC_R_FA ~ Age.scan + Race + PovStat + Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.120267 -0.015757 0.003801 0.017831 0.074684
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2996896 0.0112451 26.651 <2e-16 ***
## Age.scan -0.0004235 0.0002017 -2.100 0.0369 *
## Race2 -0.0059142 0.0046028 -1.285 0.2001
## PovStat2 -0.0118036 0.0053377 -2.211 0.0280 *
## Race2:PovStat2 0.0135494 0.0078718 1.721 0.0866 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02751 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04055, Adjusted R-squared: 0.02379
## F-statistic: 2.42 on 4 and 229 DF, p-value: 0.04933Outcome Variable:CGH_L_FA
#Fit the full model
##
## Call:
## lm(formula = CGH_L_FA ~ (Age.scan + Race + PovStat)^3 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.092978 -0.014347 0.001256 0.018037 0.060122
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2859156 0.0171478 16.674 <2e-16 ***
## Age.scan -0.0004641 0.0003098 -1.498 0.136
## Race2 0.0347083 0.0256058 1.355 0.177
## PovStat2 0.0198598 0.0345627 0.575 0.566
## Sex2 0.0006311 0.0036135 0.175 0.862
## Age.scan:Race2 -0.0006780 0.0004659 -1.455 0.147
## Age.scan:PovStat2 -0.0004224 0.0006401 -0.660 0.510
## Race2:PovStat2 -0.0506201 0.0472446 -1.071 0.285
## Age.scan:Race2:PovStat2 0.0009835 0.0009058 1.086 0.279
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02705 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.07144, Adjusted R-squared: 0.03843
## F-statistic: 2.164 on 8 and 225 DF, p-value: 0.03119#Stepwise regression model
##
## Call:
## lm(formula = CGH_L_FA ~ Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.094140 -0.014010 0.002205 0.019594 0.057792
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2988017 0.0101500 29.439 < 2e-16 ***
## Age.scan -0.0007245 0.0001895 -3.824 0.000169 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02682 on 232 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.05929, Adjusted R-squared: 0.05524
## F-statistic: 14.62 on 1 and 232 DF, p-value: 0.0001688#Re-run with only 2-way interactions
##
## Call:
## lm(formula = CGH_L_FA ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.091994 -0.015121 0.001464 0.018740 0.057788
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.923e-01 1.610e-02 18.160 <2e-16 ***
## Age.scan -5.801e-04 2.909e-04 -1.994 0.0474 *
## Race2 2.055e-02 2.205e-02 0.932 0.3522
## PovStat2 -6.455e-03 2.465e-02 -0.262 0.7937
## Sex2 3.220e-04 3.604e-03 0.089 0.9289
## Age.scan:Race2 -4.164e-04 3.989e-04 -1.044 0.2978
## Age.scan:PovStat2 7.009e-05 4.518e-04 0.155 0.8769
## Race2:PovStat2 -8.271e-05 8.100e-03 -0.010 0.9919
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02706 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.06658, Adjusted R-squared: 0.03767
## F-statistic: 2.303 on 7 and 226 DF, p-value: 0.02759##
## Call:
## lm(formula = CGH_L_FA ~ Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.094140 -0.014010 0.002205 0.019594 0.057792
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2988017 0.0101500 29.439 < 2e-16 ***
## Age.scan -0.0007245 0.0001895 -3.824 0.000169 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02682 on 232 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.05929, Adjusted R-squared: 0.05524
## F-statistic: 14.62 on 1 and 232 DF, p-value: 0.0001688Outcome Variable:CGH_R_FA
#Fit the full model
##
## Call:
## lm(formula = CGH_R_FA ~ (Age.scan + Race + PovStat)^3 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.094919 -0.016196 0.001752 0.018160 0.067863
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.210e-01 1.802e-02 17.807 <2e-16 ***
## Age.scan -6.930e-04 3.257e-04 -2.128 0.0344 *
## Race2 3.334e-02 2.691e-02 1.239 0.2168
## PovStat2 -1.338e-03 3.633e-02 -0.037 0.9707
## Sex2 -1.790e-03 3.798e-03 -0.471 0.6379
## Age.scan:Race2 -5.988e-04 4.897e-04 -1.223 0.2227
## Age.scan:PovStat2 -9.171e-05 6.728e-04 -0.136 0.8917
## Race2:PovStat2 -5.575e-02 4.966e-02 -1.123 0.2628
## Age.scan:Race2:PovStat2 1.194e-03 9.521e-04 1.254 0.2110
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02844 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0882, Adjusted R-squared: 0.05578
## F-statistic: 2.72 on 8 and 225 DF, p-value: 0.007021#Stepwise regression model
##
## Call:
## lm(formula = CGH_R_FA ~ Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.091785 -0.017328 0.001918 0.018241 0.069987
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3263559 0.0107156 30.456 < 2e-16 ***
## Age.scan -0.0008238 0.0002000 -4.119 5.3e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02831 on 232 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.06814, Adjusted R-squared: 0.06413
## F-statistic: 16.97 on 1 and 232 DF, p-value: 5.298e-05#Re-run with only 2-way interactions
##
## Call:
## lm(formula = CGH_R_FA ~ (Age.scan + Race + PovStat)^2 + Sex,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.094912 -0.017259 0.002782 0.018292 0.068153
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3287702 0.0169364 19.412 < 2e-16 ***
## Age.scan -0.0008339 0.0003061 -2.724 0.00694 **
## Race2 0.0161453 0.0231944 0.696 0.48709
## PovStat2 -0.0332953 0.0259338 -1.284 0.20051
## Sex2 -0.0021654 0.0037913 -0.571 0.56846
## Age.scan:Race2 -0.0002811 0.0004197 -0.670 0.50371
## Age.scan:PovStat2 0.0005064 0.0004753 1.065 0.28780
## Race2:PovStat2 0.0056295 0.0085210 0.661 0.50950
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02847 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.08182, Adjusted R-squared: 0.05338
## F-statistic: 2.877 on 7 and 226 DF, p-value: 0.00675##
## Call:
## lm(formula = CGH_R_FA ~ Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.091785 -0.017328 0.001918 0.018241 0.069987
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3263559 0.0107156 30.456 < 2e-16 ***
## Age.scan -0.0008238 0.0002000 -4.119 5.3e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02831 on 232 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.06814, Adjusted R-squared: 0.06413
## F-statistic: 16.97 on 1 and 232 DF, p-value: 5.298e-05