Regressions for Shari: Age as Covariate
## #refugeeswelcomeOutcome Variable: FRONTAL_wmlM2
#Fit the full model
##
## Call:
## lm(formula = FRONTAL_wmlM2 ~ (Sex + Race + PovStat)^3 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -763.2 -266.9 -101.9 110.3 3277.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -896.058 208.083 -4.306 2.49e-05 ***
## Sex2 20.845 95.445 0.218 0.827
## Race2 -11.738 115.949 -0.101 0.919
## PovStat2 29.526 121.131 0.244 0.808
## Age.scan 21.797 3.596 6.061 5.73e-09 ***
## Sex2:Race2 242.816 162.796 1.492 0.137
## Sex2:PovStat2 26.189 195.767 0.134 0.894
## Race2:PovStat2 114.454 178.930 0.640 0.523
## Sex2:Race2:PovStat2 -203.052 282.721 -0.718 0.473
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 479.3 on 222 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.1658, Adjusted R-squared: 0.1357
## F-statistic: 5.515 on 8 and 222 DF, p-value: 2.293e-06#Stepwise regression model
##
## Call:
## lm(formula = FRONTAL_wmlM2 ~ Race + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -687.3 -268.7 -100.0 105.9 3272.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -860.856 190.823 -4.511 1.03e-05 ***
## Race2 120.235 64.541 1.863 0.0638 .
## Age.scan 21.507 3.463 6.211 2.47e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 478 on 228 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.148, Adjusted R-squared: 0.1405
## F-statistic: 19.8 on 2 and 228 DF, p-value: 1.183e-08Outcome Variable: WM_FA2
#Fit the full model
##
## Call:
## lm(formula = WM_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.054619 -0.012269 0.001286 0.011125 0.095061
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4903873 0.0235330 20.838 < 2e-16 ***
## Sex -0.0089063 0.0112383 -0.792 0.42899
## Race -0.0236767 0.0135399 -1.749 0.08185 .
## PovStat -0.0106285 0.0127504 -0.834 0.40549
## Age.scan -0.0004335 0.0001591 -2.725 0.00698 **
## Sex:Race 0.0057085 0.0060226 0.948 0.34433
## Sex:PovStat -0.0022626 0.0063226 -0.358 0.72082
## Race:PovStat 0.0070001 0.0062821 1.114 0.26647
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02081 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.0683, Adjusted R-squared: 0.03633
## F-statistic: 2.137 on 7 and 204 DF, p-value: 0.04137#Stepwise regression model
##
## Call:
## lm(formula = WM_FA2 ~ Race + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.062533 -0.011970 0.000331 0.011151 0.093539
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4587308 0.0098125 46.750 < 2e-16 ***
## Race -0.0062640 0.0029523 -2.122 0.03504 *
## Age.scan -0.0004200 0.0001554 -2.703 0.00743 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02079 on 209 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.0471, Adjusted R-squared: 0.03798
## F-statistic: 5.165 on 2 and 209 DF, p-value: 0.006463Outcome Variable:DEEP_WM_FA2
#Fit the full model
##
## Call:
## lm(formula = DEEP_WM_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.139679 -0.012728 0.002443 0.015552 0.078112
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.084e-01 3.050e-02 19.949 <2e-16 ***
## Sex 3.569e-03 1.456e-02 0.245 0.8067
## Race -3.137e-02 1.755e-02 -1.788 0.0753 .
## PovStat -1.021e-02 1.652e-02 -0.618 0.5375
## Age.scan 7.567e-05 2.061e-04 0.367 0.7139
## Sex:Race 6.553e-04 7.805e-03 0.084 0.9332
## Sex:PovStat -4.510e-03 8.193e-03 -0.550 0.5826
## Race:PovStat 1.045e-02 8.141e-03 1.284 0.2005
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02697 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.09523, Adjusted R-squared: 0.06419
## F-statistic: 3.068 on 7 and 204 DF, p-value: 0.004301#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 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.069428 -0.013993 0.001734 0.010951 0.105567
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.5026232 0.0264887 18.975 < 2e-16 ***
## Sex -0.0085724 0.0126497 -0.678 0.4987
## Race -0.0280473 0.0152405 -1.840 0.0672 .
## PovStat -0.0162972 0.0143518 -1.136 0.2575
## Age.scan -0.0008327 0.0001790 -4.651 5.93e-06 ***
## Sex:Race 0.0062634 0.0067790 0.924 0.3566
## Sex:PovStat -0.0029421 0.0071167 -0.413 0.6797
## Race:PovStat 0.0105515 0.0070711 1.492 0.1372
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02342 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1218, Adjusted R-squared: 0.09171
## F-statistic: 4.044 on 7 and 204 DF, p-value: 0.0003582#Stepwise regression model
##
## Call:
## lm(formula = FRONTAL_WM_L_FA2 ~ Race + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.069284 -0.014497 0.001802 0.011487 0.102118
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4627276 0.0110747 41.782 < 2e-16 ***
## Race -0.0052044 0.0033321 -1.562 0.12
## Age.scan -0.0008165 0.0001754 -4.656 5.72e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02347 on 209 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.097, Adjusted R-squared: 0.08836
## F-statistic: 11.23 on 2 and 209 DF, p-value: 2.341e-05Outcome Variable:FRONTAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = FRONTAL_WM_R_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.068800 -0.015859 0.001273 0.014206 0.111360
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.5028083 0.0280083 17.952 < 2e-16 ***
## Sex -0.0055819 0.0133755 -0.417 0.67688
## Race -0.0312456 0.0161148 -1.939 0.05389 .
## PovStat -0.0088294 0.0151752 -0.582 0.56132
## Age.scan -0.0007019 0.0001893 -3.707 0.00027 ***
## Sex:Race 0.0079882 0.0071679 1.114 0.26640
## Sex:PovStat -0.0061548 0.0075250 -0.818 0.41436
## Race:PovStat 0.0078059 0.0074767 1.044 0.29771
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02477 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.1029, Adjusted R-squared: 0.07211
## F-statistic: 3.342 on 7 and 204 DF, p-value: 0.002152#Stepwise regression model
##
## Call:
## lm(formula = FRONTAL_WM_R_FA2 ~ Race + PovStat + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.071763 -0.014442 -0.000011 0.014466 0.112657
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4794981 0.0130840 36.648 < 2e-16 ***
## Race -0.0090424 0.0035369 -2.557 0.011284 *
## PovStat -0.0057913 0.0036761 -1.575 0.116684
## Age.scan -0.0007130 0.0001872 -3.808 0.000184 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0247 on 208 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.08999, Adjusted R-squared: 0.07687
## F-statistic: 6.857 on 3 and 208 DF, p-value: 0.0001995Outcome Variable: TEMPORAL_WM_L_FA2
#Fit the full model
##
## Call:
## lm(formula = TEMPORAL_WM_L_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.050345 -0.013947 -0.000062 0.011701 0.099995
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4687644 0.0243480 19.253 <2e-16 ***
## Sex -0.0109314 0.0116275 -0.940 0.3483
## Race -0.0155972 0.0140088 -1.113 0.2669
## PovStat -0.0074863 0.0131920 -0.567 0.5710
## Age.scan -0.0003729 0.0001646 -2.266 0.0245 *
## Sex:Race 0.0046379 0.0062312 0.744 0.4576
## Sex:PovStat -0.0012821 0.0065416 -0.196 0.8448
## Race:PovStat 0.0047388 0.0064996 0.729 0.4668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02153 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.05004, Adjusted R-squared: 0.01744
## F-statistic: 1.535 on 7 and 204 DF, p-value: 0.1571#Stepwise regression model
##
## Call:
## lm(formula = TEMPORAL_WM_L_FA2 ~ Sex + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.054720 -0.013922 -0.000226 0.011552 0.098994
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4436240 0.0094279 47.054 <2e-16 ***
## Sex -0.0057124 0.0029471 -1.938 0.0539 .
## Age.scan -0.0003403 0.0001581 -2.152 0.0325 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02139 on 209 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.03933, Adjusted R-squared: 0.03014
## F-statistic: 4.278 on 2 and 209 DF, p-value: 0.0151Outcome Variable: TEMPORAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = TEMPORAL_WM_L_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.050345 -0.013947 -0.000062 0.011701 0.099995
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4687644 0.0243480 19.253 <2e-16 ***
## Sex -0.0109314 0.0116275 -0.940 0.3483
## Race -0.0155972 0.0140088 -1.113 0.2669
## PovStat -0.0074863 0.0131920 -0.567 0.5710
## Age.scan -0.0003729 0.0001646 -2.266 0.0245 *
## Sex:Race 0.0046379 0.0062312 0.744 0.4576
## Sex:PovStat -0.0012821 0.0065416 -0.196 0.8448
## Race:PovStat 0.0047388 0.0064996 0.729 0.4668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02153 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.05004, Adjusted R-squared: 0.01744
## F-statistic: 1.535 on 7 and 204 DF, p-value: 0.1571#Stepwise regression model
##
## Call:
## lm(formula = TEMPORAL_WM_L_FA2 ~ Sex + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.054720 -0.013922 -0.000226 0.011552 0.098994
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4436240 0.0094279 47.054 <2e-16 ***
## Sex -0.0057124 0.0029471 -1.938 0.0539 .
## Age.scan -0.0003403 0.0001581 -2.152 0.0325 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02139 on 209 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.03933, Adjusted R-squared: 0.03014
## F-statistic: 4.278 on 2 and 209 DF, p-value: 0.0151Outcome Variable: PARIETAL_WM_L_FA2
#Fit the full model
##
## Call:
## lm(formula = PARIETAL_WM_L_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.062438 -0.013095 0.000394 0.013018 0.111973
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4869924 0.0257748 18.894 <2e-16 ***
## Sex -0.0058554 0.0123088 -0.476 0.635
## Race -0.0218973 0.0148298 -1.477 0.141
## PovStat -0.0108921 0.0139650 -0.780 0.436
## Age.scan -0.0004320 0.0001742 -2.480 0.014 *
## Sex:Race 0.0014101 0.0065963 0.214 0.831
## Sex:PovStat -0.0039918 0.0069249 -0.576 0.565
## Race:PovStat 0.0087561 0.0068805 1.273 0.205
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02279 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.09701, Adjusted R-squared: 0.06603
## F-statistic: 3.131 on 7 and 204 DF, p-value: 0.003669#Stepwise regression model
##
## Call:
## lm(formula = PARIETAL_WM_L_FA2 ~ Sex + Race + Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.062269 -0.013706 0.000708 0.013266 0.107875
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4689731 0.0116356 40.305 < 2e-16 ***
## Sex -0.0085021 0.0031344 -2.712 0.00724 **
## Race -0.0084644 0.0032304 -2.620 0.00944 **
## Age.scan -0.0004237 0.0001700 -2.492 0.01348 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02275 on 208 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.08283, Adjusted R-squared: 0.06961
## F-statistic: 6.262 on 3 and 208 DF, p-value: 0.000434Outcome Variable: PARIETAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = PARIETAL_WM_R_FA2 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.064845 -0.014457 -0.000719 0.013108 0.106453
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4936444 0.0274029 18.014 <2e-16 ***
## Sex -0.0047619 0.0130863 -0.364 0.7163
## Race -0.0224454 0.0157665 -1.424 0.1561
## PovStat -0.0185792 0.0148471 -1.251 0.2122
## Age.scan -0.0003727 0.0001852 -2.012 0.0455 *
## Sex:Race 0.0014013 0.0070130 0.200 0.8418
## Sex:PovStat 0.0001444 0.0073624 0.020 0.9844
## Race:PovStat 0.0099797 0.0073151 1.364 0.1740
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02423 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.05141, Adjusted R-squared: 0.01886
## F-statistic: 1.579 on 7 and 204 DF, p-value: 0.1431#Stepwise regression model
##
## Call:
## lm(formula = PARIETAL_WM_R_FA2 ~ Race + Age.scan, 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 ***
## Race -0.0073334 0.0034279 -2.139 0.0336 *
## Age.scan -0.0003712 0.0001804 -2.058 0.0409 *
## ---
## 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 ~ (Sex + Race + PovStat)^2 +
## Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.08052 -0.01559 -0.00027 0.01567 0.11922
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4778721 0.0285173 16.757 <2e-16 ***
## Sex -0.0188924 0.0136185 -1.387 0.1669
## Race -0.0403768 0.0164077 -2.461 0.0147 *
## PovStat -0.0225538 0.0154509 -1.460 0.1459
## Age.scan -0.0001732 0.0001928 -0.898 0.3701
## Sex:Race 0.0086992 0.0072982 1.192 0.2347
## Sex:PovStat 0.0021885 0.0076618 0.286 0.7754
## Race:PovStat 0.0107997 0.0076126 1.419 0.1575
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02522 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.08674, Adjusted R-squared: 0.05541
## F-statistic: 2.768 on 7 and 204 DF, p-value: 0.00906#Stepwise regression model
##
## Call:
## lm(formula = OCCIPITAL_WM_L_FA2 ~ Race, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.091645 -0.016365 -0.000445 0.016013 0.115125
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.415138 0.005238 79.257 < 2e-16 ***
## Race -0.012969 0.003540 -3.663 0.000316 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02521 on 210 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.06006, Adjusted R-squared: 0.05558
## F-statistic: 13.42 on 1 and 210 DF, p-value: 0.0003156Outcome Variable: OCCIPITAL_WM_R_FA2
#Fit the full model
##
## Call:
## lm(formula = OCCIPITAL_WM_R_FA2 ~ (Sex + Race + PovStat)^2 +
## Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.060739 -0.015736 -0.000344 0.012892 0.132120
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4460825 0.0283459 15.737 <2e-16 ***
## Sex -0.0315796 0.0135367 -2.333 0.0206 *
## Race -0.0239853 0.0163091 -1.471 0.1429
## PovStat -0.0123794 0.0153581 -0.806 0.4211
## Age.scan -0.0002364 0.0001916 -1.234 0.2187
## Sex:Race 0.0113631 0.0072543 1.566 0.1188
## Sex:PovStat 0.0048476 0.0076157 0.637 0.5251
## Race:PovStat 0.0021745 0.0075669 0.287 0.7741
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02506 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.06011, Adjusted R-squared: 0.02786
## F-statistic: 1.864 on 7 and 204 DF, p-value: 0.07715#Stepwise regression model
##
## Call:
## lm(formula = OCCIPITAL_WM_R_FA2 ~ Sex + Race + Sex:Race, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.063888 -0.016819 0.001375 0.013129 0.127644
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.416012 0.016088 25.858 <2e-16 ***
## Sex -0.024850 0.010401 -2.389 0.0178 *
## Race -0.020650 0.010847 -1.904 0.0583 .
## Sex:Race 0.011347 0.007036 1.613 0.1083
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02497 on 208 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.04913, Adjusted R-squared: 0.03541
## F-statistic: 3.582 on 3 and 208 DF, p-value: 0.01474Outcome Variable: CORPUS_CALLOSUM_FA2
#Fit the full model
##
## Call:
## lm(formula = CORPUS_CALLOSUM_FA2 ~ (Sex + Race + PovStat)^2 +
## Age.scan, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.111865 -0.014949 0.003682 0.020037 0.057822
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.544e-01 3.228e-02 20.271 <2e-16 ***
## Sex 3.557e-03 1.542e-02 0.231 0.818
## Race -1.188e-02 1.857e-02 -0.639 0.523
## PovStat -9.132e-03 1.749e-02 -0.522 0.602
## Age.scan -9.082e-05 2.182e-04 -0.416 0.678
## Sex:Race -1.185e-03 8.261e-03 -0.143 0.886
## Sex:PovStat -5.953e-03 8.673e-03 -0.686 0.493
## Race:PovStat 6.399e-03 8.617e-03 0.743 0.459
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02854 on 204 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.03933, Adjusted R-squared: 0.006366
## F-statistic: 1.193 on 7 and 204 DF, p-value: 0.3081#Stepwise regression model
##
## Call:
## lm(formula = CORPUS_CALLOSUM_FA2 ~ Sex + PovStat, data = dtidat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.115230 -0.013220 0.003857 0.019632 0.055828
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.644605 0.008912 72.330 <2e-16 ***
## Sex -0.005928 0.003965 -1.495 0.1364
## PovStat -0.008680 0.004174 -2.079 0.0388 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02839 on 209 degrees of freedom
## (26 observations deleted due to missingness)
## Multiple R-squared: 0.02648, Adjusted R-squared: 0.01717
## F-statistic: 2.843 on 2 and 209 DF, p-value: 0.06052Outcome Variable:Fx_L_FA
#Fit the full model
##
## Call:
## lm(formula = Fx_L_FA ~ (Sex + Race + PovStat)^3 + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.205993 -0.036960 0.005487 0.043302 0.251066
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3460505 0.0307526 11.253 < 2e-16 ***
## Sex2 -0.0287663 0.0143033 -2.011 0.045502 *
## Race2 -0.0217869 0.0170452 -1.278 0.202504
## PovStat2 -0.0127174 0.0179472 -0.709 0.479305
## Age.scan -0.0018558 0.0005308 -3.496 0.000569 ***
## Sex2:Race2 0.0375676 0.0241856 1.553 0.121756
## Sex2:PovStat2 0.0036535 0.0292645 0.125 0.900759
## Race2:PovStat2 0.0389518 0.0265046 1.470 0.143061
## Sex2:Race2:PovStat2 -0.0900612 0.0425346 -2.117 0.035327 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07215 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1065, Adjusted R-squared: 0.07474
## F-statistic: 3.353 on 8 and 225 DF, p-value: 0.001195#Stepwise regression model
##
## Call:
## lm(formula = Fx_L_FA ~ (Sex + Race + PovStat)^3 + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.205993 -0.036960 0.005487 0.043302 0.251066
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3460505 0.0307526 11.253 < 2e-16 ***
## Sex2 -0.0287663 0.0143033 -2.011 0.045502 *
## Race2 -0.0217869 0.0170452 -1.278 0.202504
## PovStat2 -0.0127174 0.0179472 -0.709 0.479305
## Age.scan -0.0018558 0.0005308 -3.496 0.000569 ***
## Sex2:Race2 0.0375676 0.0241856 1.553 0.121756
## Sex2:PovStat2 0.0036535 0.0292645 0.125 0.900759
## Race2:PovStat2 0.0389518 0.0265046 1.470 0.143061
## Sex2:Race2:PovStat2 -0.0900612 0.0425346 -2.117 0.035327 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07215 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1065, Adjusted R-squared: 0.07474
## F-statistic: 3.353 on 8 and 225 DF, p-value: 0.001195
Outcome Variable:Fx_R_FA
#Fit the full model
##
## Call:
## lm(formula = Fx_R_FA ~ (Sex + Race + PovStat)^2 + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.219448 -0.034760 0.001016 0.034853 0.125554
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4130593 0.0216607 19.070 < 2e-16 ***
## Sex2 -0.0099815 0.0095905 -1.041 0.299
## Race2 -0.0083648 0.0111165 -0.752 0.453
## PovStat2 -0.0012493 0.0115781 -0.108 0.914
## Age.scan -0.0019965 0.0003772 -5.293 2.84e-07 ***
## Sex2:Race2 -0.0031113 0.0141483 -0.220 0.826
## Sex2:PovStat2 -0.0179802 0.0150956 -1.191 0.235
## Race2:PovStat2 0.0068212 0.0148812 0.458 0.647
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05142 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.141, Adjusted R-squared: 0.1144
## F-statistic: 5.302 on 7 and 226 DF, p-value: 1.254e-05#Stepwise regression model
##
## Call:
## lm(formula = Fx_R_FA ~ Sex + Age.scan, 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 ***
## Sex2 -0.0157007 0.0067406 -2.329 0.0207 *
## Age.scan -0.0019120 0.0003623 -5.277 3.02e-07 ***
## ---
## 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 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.165983 -0.015349 0.000679 0.018357 0.060420
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3954921 0.0119932 32.976 <2e-16 ***
## Sex2 0.0006612 0.0053101 0.125 0.9010
## Race2 -0.0121518 0.0061550 -1.974 0.0496 *
## PovStat2 -0.0114076 0.0064106 -1.779 0.0765 .
## Age.scan -0.0003536 0.0002088 -1.693 0.0918 .
## Sex2:Race2 0.0048363 0.0078337 0.617 0.5376
## Sex2:PovStat2 -0.0024168 0.0083582 -0.289 0.7727
## Race2:PovStat2 0.0089466 0.0082395 1.086 0.2787
## ---
## 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: 0.05109, Adjusted R-squared: 0.02169
## F-statistic: 1.738 on 7 and 226 DF, p-value: 0.1012#Stepwise regression model
##
## Call:
## lm(formula = ALIC_L_FA ~ Race + PovStat + Age.scan, 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 ***
## Race2 -0.0069778 0.0038444 -1.815 0.0708 .
## PovStat2 -0.0085828 0.0040713 -2.108 0.0361 *
## Age.scan -0.0003833 0.0002055 -1.865 0.0634 .
## ---
## 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 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.144202 -0.012976 0.003258 0.015311 0.062646
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4487105 0.0117774 38.099 < 2e-16 ***
## Sex2 0.0042817 0.0052146 0.821 0.412458
## Race2 -0.0203437 0.0060443 -3.366 0.000897 ***
## PovStat2 -0.0139240 0.0062953 -2.212 0.027981 *
## Age.scan -0.0006157 0.0002051 -3.002 0.002983 **
## Sex2:Race2 0.0050374 0.0076928 0.655 0.513252
## Sex2:PovStat2 -0.0065700 0.0082078 -0.800 0.424284
## Race2:PovStat2 0.0241794 0.0080912 2.988 0.003115 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02796 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1164, Adjusted R-squared: 0.08908
## F-statistic: 4.255 on 7 and 226 DF, p-value: 0.0001953#Stepwise regression model
##
## Call:
## lm(formula = ALIC_R_FA ~ Race + PovStat + Age.scan + 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 ***
## Race2 -0.0179517 0.0046698 -3.844 0.000157 ***
## PovStat2 -0.0168700 0.0054154 -3.115 0.002073 **
## Age.scan -0.0006161 0.0002047 -3.010 0.002902 **
## 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 ~ (Sex + Race + PovStat)^2 + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.106376 -0.012649 0.000729 0.013770 0.060603
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2889899 0.0086355 33.465 < 2e-16 ***
## Sex2 -0.0001966 0.0038235 -0.051 0.959045
## Race2 -0.0106958 0.0044318 -2.413 0.016601 *
## PovStat2 -0.0082917 0.0046159 -1.796 0.073775 .
## Age.scan -0.0005554 0.0001504 -3.693 0.000278 ***
## Sex2:Race2 -0.0008080 0.0056406 -0.143 0.886218
## Sex2:PovStat2 -0.0011899 0.0060182 -0.198 0.843449
## Race2:PovStat2 0.0092617 0.0059327 1.561 0.119894
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0205 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1024, Adjusted R-squared: 0.07465
## F-statistic: 3.685 on 7 and 226 DF, p-value: 0.0008597#Stepwise regression model
##
## Call:
## lm(formula = EC_L_FA ~ Race + PovStat + Age.scan + Race:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.105881 -0.012649 0.000732 0.013559 0.061082
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2888293 0.0083268 34.687 < 2e-16 ***
## Race2 -0.0110888 0.0034083 -3.253 0.00131 **
## PovStat2 -0.0086525 0.0039525 -2.189 0.02960 *
## Age.scan -0.0005542 0.0001494 -3.710 0.00026 ***
## Race2:PovStat2 0.0093737 0.0058289 1.608 0.10918
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02037 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1017, Adjusted R-squared: 0.08605
## F-statistic: 6.484 on 4 and 229 DF, p-value: 5.841e-05Outcome Variable:EC_R_FA
#Fit the full model
##
## Call:
## lm(formula = EC_R_FA ~ (Sex + Race + PovStat)^2 + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.089045 -0.014948 0.000143 0.016541 0.063535
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3238882 0.0104677 30.942 <2e-16 ***
## Sex2 0.0057610 0.0046347 1.243 0.2152
## Race2 -0.0105963 0.0053721 -1.972 0.0498 *
## PovStat2 -0.0075588 0.0055952 -1.351 0.1781
## Age.scan -0.0004177 0.0001823 -2.291 0.0229 *
## Sex2:Race2 -0.0065197 0.0068373 -0.954 0.3413
## Sex2:PovStat2 -0.0029184 0.0072951 -0.400 0.6895
## Race2:PovStat2 0.0078522 0.0071915 1.092 0.2760
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02485 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0854, Adjusted R-squared: 0.05707
## F-statistic: 3.015 on 7 and 226 DF, p-value: 0.004775#Stepwise regression model
##
## Call:
## lm(formula = EC_R_FA ~ Race + PovStat + Age.scan, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.090513 -0.014912 -0.000441 0.017688 0.061695
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3277483 0.0101243 32.373 < 2e-16 ***
## Race2 -0.0108503 0.0033671 -3.222 0.00146 **
## PovStat2 -0.0054818 0.0035658 -1.537 0.12559
## Age.scan -0.0004545 0.0001800 -2.525 0.01224 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02481 on 230 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.07217, Adjusted R-squared: 0.06007
## F-statistic: 5.964 on 3 and 230 DF, p-value: 0.0006229Outcome Variable:CGC_L_FA
#Fit the full model
##
## Call:
## lm(formula = CGC_L_FA ~ (Sex + Race + PovStat)^3 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.072033 -0.016965 0.001182 0.019352 0.063677
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3052982 0.0112969 27.025 <2e-16 ***
## Sex2 0.0024480 0.0052543 0.466 0.6417
## Race2 -0.0086372 0.0062615 -1.379 0.1691
## PovStat2 -0.0126269 0.0065929 -1.915 0.0567 .
## Age.scan -0.0003631 0.0001950 -1.862 0.0639 .
## Sex2:Race2 0.0014757 0.0088846 0.166 0.8682
## Sex2:PovStat2 0.0027358 0.0107503 0.254 0.7994
## Race2:PovStat2 0.0187134 0.0097364 1.922 0.0559 .
## Sex2:Race2:PovStat2 -0.0117902 0.0156250 -0.755 0.4513
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02651 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04725, Adjusted R-squared: 0.01338
## F-statistic: 1.395 on 8 and 225 DF, p-value: 0.1997#Stepwise regression model
##
## Call:
## lm(formula = CGC_L_FA ~ Race + PovStat + Age.scan + 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 ***
## Race2 -0.0079590 0.0044065 -1.806 0.0722 .
## PovStat2 -0.0121376 0.0051101 -2.375 0.0184 *
## Age.scan -0.0003537 0.0001931 -1.831 0.0683 .
## 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 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073241 -0.017797 0.001362 0.018595 0.064325
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3039987 0.0111543 27.254 <2e-16 ***
## Sex2 0.0037916 0.0049387 0.768 0.4434
## Race2 -0.0067320 0.0057245 -1.176 0.2408
## PovStat2 -0.0105127 0.0059622 -1.763 0.0792 .
## Age.scan -0.0003517 0.0001942 -1.811 0.0715 .
## Sex2:Race2 -0.0023535 0.0072857 -0.323 0.7470
## Sex2:PovStat2 -0.0028616 0.0077735 -0.368 0.7131
## Race2:PovStat2 0.0141883 0.0076631 1.852 0.0654 .
## ---
## 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: 0.04484, Adjusted R-squared: 0.01526
## F-statistic: 1.516 on 7 and 226 DF, p-value: 0.1628##
## Call:
## lm(formula = CGC_L_FA ~ Race + PovStat + Age.scan + 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 ***
## Race2 -0.0079590 0.0044065 -1.806 0.0722 .
## PovStat2 -0.0121376 0.0051101 -2.375 0.0184 *
## Age.scan -0.0003537 0.0001931 -1.831 0.0683 .
## 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 ~ (Sex + Race + PovStat)^3 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.123479 -0.015383 0.002064 0.017432 0.074485
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2996817 0.0118035 25.389 <2e-16 ***
## Sex2 -0.0003671 0.0054899 -0.067 0.9467
## Race2 -0.0028857 0.0065423 -0.441 0.6596
## PovStat2 -0.0136641 0.0068885 -1.984 0.0485 *
## Age.scan -0.0004199 0.0002037 -2.061 0.0404 *
## Sex2:Race2 -0.0061833 0.0092830 -0.666 0.5060
## Sex2:PovStat2 0.0053978 0.0112323 0.481 0.6313
## Race2:PovStat2 0.0124386 0.0101730 1.223 0.2227
## Sex2:Race2:PovStat2 0.0005068 0.0163257 0.031 0.9753
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02769 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.04497, Adjusted R-squared: 0.01102
## F-statistic: 1.324 on 8 and 225 DF, p-value: 0.2323#Stepwise regression model
##
## Call:
## lm(formula = CGC_R_FA ~ Race + PovStat + Age.scan + 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 ***
## Race2 -0.0059142 0.0046028 -1.285 0.2001
## PovStat2 -0.0118036 0.0053377 -2.211 0.0280 *
## Age.scan -0.0004235 0.0002017 -2.100 0.0369 *
## 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 ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.123427 -0.015350 0.002092 0.017496 0.074457
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2997376 0.0116397 25.751 <2e-16 ***
## Sex2 -0.0004249 0.0051536 -0.082 0.9344
## Race2 -0.0029676 0.0059736 -0.497 0.6198
## PovStat2 -0.0137550 0.0062217 -2.211 0.0281 *
## Age.scan -0.0004204 0.0002027 -2.074 0.0392 *
## Sex2:Race2 -0.0060187 0.0076028 -0.792 0.4294
## Sex2:PovStat2 0.0056384 0.0081119 0.695 0.4877
## Race2:PovStat2 0.0126331 0.0079966 1.580 0.1156
## ---
## 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: 0.04497, Adjusted R-squared: 0.01539
## F-statistic: 1.52 on 7 and 226 DF, p-value: 0.1613##
## Call:
## lm(formula = CGC_R_FA ~ Race + PovStat + Age.scan + 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 ***
## Race2 -0.0059142 0.0046028 -1.285 0.2001
## PovStat2 -0.0118036 0.0053377 -2.211 0.0280 *
## Age.scan -0.0004235 0.0002017 -2.100 0.0369 *
## 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 ~ (Sex + Race + PovStat)^3 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.091005 -0.015374 0.001031 0.019236 0.057582
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3003308 0.0114484 26.234 < 2e-16 ***
## Sex2 0.0050907 0.0053247 0.956 0.340076
## Race2 0.0003207 0.0063455 0.051 0.959736
## PovStat2 -0.0022424 0.0066813 -0.336 0.737465
## Age.scan -0.0007727 0.0001976 -3.910 0.000122 ***
## Sex2:Race2 -0.0044716 0.0090037 -0.497 0.619924
## Sex2:PovStat2 0.0004729 0.0108944 0.043 0.965413
## Race2:PovStat2 0.0070267 0.0098670 0.712 0.477113
## Sex2:Race2:PovStat2 -0.0194187 0.0158345 -1.226 0.221348
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02686 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.08461, Adjusted R-squared: 0.05206
## F-statistic: 2.6 on 8 and 225 DF, p-value: 0.009769#Stepwise regression model
##
## Call:
## lm(formula = CGH_L_FA ~ Sex + Race + Age.scan + Sex:Race, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.092344 -0.014556 0.000524 0.019408 0.056322
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2971078 0.0107950 27.523 < 2e-16 ***
## Sex2 0.0055059 0.0045768 1.203 0.230216
## Race2 0.0035429 0.0048109 0.736 0.462215
## Age.scan -0.0007265 0.0001913 -3.797 0.000187 ***
## Sex2:Race2 -0.0121143 0.0071834 -1.686 0.093077 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02681 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.07202, Adjusted R-squared: 0.05581
## F-statistic: 4.443 on 4 and 229 DF, p-value: 0.001776#Re-run with only 2-way interactions
##
## Call:
## lm(formula = CGH_L_FA ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.093287 -0.014960 0.002744 0.018361 0.060416
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2981905 0.0113272 26.325 < 2e-16 ***
## Sex2 0.0073037 0.0050152 1.456 0.146699
## Race2 0.0034586 0.0058132 0.595 0.552467
## PovStat2 0.0012398 0.0060546 0.205 0.837940
## Age.scan -0.0007540 0.0001972 -3.823 0.000171 ***
## Sex2:Race2 -0.0107784 0.0073987 -1.457 0.146561
## Sex2:PovStat2 -0.0087460 0.0078940 -1.108 0.269072
## Race2:PovStat2 -0.0004262 0.0077819 -0.055 0.956369
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02689 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.07849, Adjusted R-squared: 0.04995
## F-statistic: 2.75 on 7 and 226 DF, p-value: 0.009263##
## Call:
## lm(formula = CGH_L_FA ~ Sex + Race + Age.scan + Sex:Race, data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.092344 -0.014556 0.000524 0.019408 0.056322
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2971078 0.0107950 27.523 < 2e-16 ***
## Sex2 0.0055059 0.0045768 1.203 0.230216
## Race2 0.0035429 0.0048109 0.736 0.462215
## Age.scan -0.0007265 0.0001913 -3.797 0.000187 ***
## Sex2:Race2 -0.0121143 0.0071834 -1.686 0.093077 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02681 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.07202, Adjusted R-squared: 0.05581
## F-statistic: 4.443 on 4 and 229 DF, p-value: 0.001776Outcome Variable:CGH_R_FA
#Fit the full model
##
## Call:
## lm(formula = CGH_R_FA ~ (Sex + Race + PovStat)^3 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.093127 -0.018029 0.001784 0.017271 0.070229
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3270000 0.0121355 26.946 < 2e-16 ***
## Sex2 0.0018706 0.0056443 0.331 0.741
## Race2 0.0015148 0.0067264 0.225 0.822
## PovStat2 -0.0024829 0.0070823 -0.351 0.726
## Age.scan -0.0008392 0.0002095 -4.006 8.38e-05 ***
## Sex2:Race2 -0.0010083 0.0095441 -0.106 0.916
## Sex2:PovStat2 -0.0096700 0.0115483 -0.837 0.403
## Race2:PovStat2 0.0060835 0.0104592 0.582 0.561
## Sex2:Race2:PovStat2 -0.0048396 0.0167849 -0.288 0.773
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02847 on 225 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.08583, Adjusted R-squared: 0.05333
## F-statistic: 2.641 on 8 and 225 DF, p-value: 0.008736#Stepwise regression model
##
## Call:
## lm(formula = CGH_R_FA ~ Sex + PovStat + Age.scan + Sex:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.092190 -0.017932 0.001368 0.017013 0.069779
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3290710 0.0115139 28.580 < 2e-16 ***
## Sex2 0.0014947 0.0045148 0.331 0.741
## PovStat2 0.0008885 0.0051524 0.172 0.863
## Age.scan -0.0008674 0.0002041 -4.249 3.12e-05 ***
## Sex2:PovStat2 -0.0123972 0.0081763 -1.516 0.131
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02828 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0819, Adjusted R-squared: 0.06587
## F-statistic: 5.107 on 4 and 229 DF, p-value: 0.0005846#Re-run with only 2-way interactions
##
## Call:
## lm(formula = CGH_R_FA ~ (Sex + Race + PovStat)^2 + Age.scan,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.093623 -0.017646 0.001793 0.017483 0.070494
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3264666 0.0119693 27.275 < 2e-16 ***
## Sex2 0.0024222 0.0052996 0.457 0.648
## Race2 0.0022968 0.0061428 0.374 0.709
## PovStat2 -0.0016151 0.0063979 -0.252 0.801
## Age.scan -0.0008346 0.0002084 -4.004 8.44e-05 ***
## Sex2:Race2 -0.0025801 0.0078181 -0.330 0.742
## Sex2:PovStat2 -0.0119676 0.0083416 -1.435 0.153
## Race2:PovStat2 0.0042261 0.0082231 0.514 0.608
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02841 on 226 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.08549, Adjusted R-squared: 0.05717
## F-statistic: 3.018 on 7 and 226 DF, p-value: 0.004733##
## Call:
## lm(formula = CGH_R_FA ~ Sex + PovStat + Age.scan + Sex:PovStat,
## data = mridat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.092190 -0.017932 0.001368 0.017013 0.069779
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3290710 0.0115139 28.580 < 2e-16 ***
## Sex2 0.0014947 0.0045148 0.331 0.741
## PovStat2 0.0008885 0.0051524 0.172 0.863
## Age.scan -0.0008674 0.0002041 -4.249 3.12e-05 ***
## Sex2:PovStat2 -0.0123972 0.0081763 -1.516 0.131
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02828 on 229 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0819, Adjusted R-squared: 0.06587
## F-statistic: 5.107 on 4 and 229 DF, p-value: 0.0005846