ADNP_VEP
tl
2025-03-13
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 8.562683 | 3.202443 | 12 |
| ASD | 7.582391 | 2.855948 | 46 |
| TD | 7.028068 | 2.912711 | 19 |
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 17.4 8.675 1.015 0.367
## Residuals 74 632.6 8.548| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 36.89524 | 14.50650 | 12 |
| ASD | 56.57209 | 32.41736 | 46 |
| TD | 111.94444 | 13.18409 | 19 |
##
## Pearson's Chi-squared test
##
## data: av$DX and av$Gender
## X-squared = 30.914, df = 2, p-value = 1.937e-07## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 51911 25956 36.77 1.21e-11 ***
## Residuals 70 49407 706
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 5.772500 | 4.933933 | 12 |
| ASD | 7.252609 | 5.055430 | 46 |
| TD | 9.837368 | 6.967723 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = P60_N75_Amp_1m ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.6053 -3.4334 -0.6965 2.4296 13.7196
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.8435 2.3839 0.354 0.72448
## DXASD 2.0444 1.7436 1.172 0.24481
## DXTD 4.9482 1.9961 2.479 0.01548 *
## Age_VEP 0.5756 0.2123 2.711 0.00836 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.341 on 73 degrees of freedom
## Multiple R-squared: 0.1439, Adjusted R-squared: 0.1087
## F-statistic: 4.091 on 3 and 73 DF, p-value: 0.009656## Analysis of Variance Table
##
## Response: P60_N75_Amp_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 140.46 70.232 2.4623 0.092288 .
## Age_VEP 1 209.60 209.604 7.3487 0.008361 **
## Residuals 73 2082.14 28.523
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Call:
## lm(formula = P60_N75_Amp_1m ~ DX + Age_VEP + Gender, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.1685 -3.3765 -0.8055 2.5452 13.5631
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.6452 2.4717 0.261 0.79482
## DXASD 2.2444 1.8548 1.210 0.23022
## DXTD 4.7534 2.0923 2.272 0.02608 *
## Age_VEP 0.5704 0.2142 2.663 0.00956 **
## Gender 0.5836 1.7569 0.332 0.74072
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.373 on 72 degrees of freedom
## Multiple R-squared: 0.1452, Adjusted R-squared: 0.09775
## F-statistic: 3.059 on 4 and 72 DF, p-value: 0.02192| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 14.20833 | 5.286721 | 12 |
| ASD | 18.45978 | 10.134040 | 46 |
| TD | 28.45368 | 14.201859 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = n75_p100_amp_1m ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -18.784 -7.081 -1.760 5.107 33.259
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 13.2643 4.8312 2.746 0.00760 **
## DXASD 4.3595 3.5337 1.234 0.22127
## DXTD 14.4146 4.0452 3.563 0.00065 ***
## Age_VEP 0.1103 0.4303 0.256 0.79851
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.82 on 73 degrees of freedom
## Multiple R-squared: 0.1796, Adjusted R-squared: 0.1459
## F-statistic: 5.326 on 3 and 73 DF, p-value: 0.002249## Analysis of Variance Table
##
## Response: n75_p100_amp_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 1864.1 932.07 7.9565 0.0007483 ***
## Age_VEP 1 7.7 7.69 0.0656 0.7985135
## Residuals 73 8551.7 117.15
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 53.15833 | 11.053462 | 12 |
| ASD | 47.25000 | 5.100142 | 46 |
| TD | 45.49474 | 5.598856 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = P60_L_1m ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.9897 -3.3397 0.2316 3.0567 24.2211
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 57.5965 2.8176 20.441 < 2e-16 ***
## DXASD -6.4164 2.0609 -3.113 0.002641 **
## DXTD -8.4590 2.3593 -3.585 0.000605 ***
## Age_VEP -0.5183 0.2510 -2.065 0.042460 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.312 on 73 degrees of freedom
## Multiple R-squared: 0.1778, Adjusted R-squared: 0.144
## F-statistic: 5.262 on 3 and 73 DF, p-value: 0.002422## Analysis of Variance Table
##
## Response: P60_L_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 459.13 229.564 5.7612 0.004751 **
## Age_VEP 1 169.94 169.940 4.2649 0.042460 *
## Residuals 73 2908.79 39.846
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 69.91667 | 8.722576 | 12 |
| ASD | 65.35000 | 6.231417 | 46 |
| TD | 64.47895 | 3.569093 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = N75_L_1m ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.9158 -3.3393 0.4727 2.4682 21.6982
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 69.80073 2.77109 25.189 <2e-16 ***
## DXASD -4.55339 2.02685 -2.247 0.0277 *
## DXTD -5.41694 2.32027 -2.335 0.0223 *
## Age_VEP 0.01354 0.24684 0.055 0.9564
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.208 on 73 degrees of freedom
## Multiple R-squared: 0.08034, Adjusted R-squared: 0.04255
## F-statistic: 2.126 on 3 and 73 DF, p-value: 0.1043## Analysis of Variance Table
##
## Response: N75_L_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 245.67 122.834 3.1871 0.04709 *
## Age_VEP 1 0.12 0.116 0.0030 0.95641
## Residuals 73 2813.47 38.541
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 98.25000 | 10.384648 | 12 |
| ASD | 95.10217 | 6.267641 | 46 |
| TD | 100.33158 | 9.674081 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = P100_L_1m ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17.255 -5.066 -1.062 4.224 28.265
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 99.6536 3.5516 28.059 <2e-16 ***
## DXASD -3.3085 2.5977 -1.274 0.207
## DXTD 1.8300 2.9738 0.615 0.540
## Age_VEP -0.1639 0.3164 -0.518 0.606
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.957 on 73 degrees of freedom
## Multiple R-squared: 0.08172, Adjusted R-squared: 0.04398
## F-statistic: 2.165 on 3 and 73 DF, p-value: 0.0994## Analysis of Variance Table
##
## Response: P100_L_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 394.3 197.134 3.1138 0.05038 .
## Age_VEP 1 17.0 16.997 0.2685 0.60592
## Residuals 73 4621.6 63.309
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.3763723 | 0.1410606 | 12 |
| ASD | 0.3556196 | 0.1730498 | 46 |
| TD | 0.5106053 | 0.1701724 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32msc_b1 ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.28143 -0.10597 -0.03065 0.10604 0.41513
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.259841 0.073337 3.543 0.000694 ***
## DXASD -0.007412 0.053641 -0.138 0.890484
## DXTD 0.155118 0.061406 2.526 0.013703 *
## Age_VEP 0.013609 0.006533 2.083 0.040726 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1643 on 73 degrees of freedom
## Multiple R-squared: 0.1846, Adjusted R-squared: 0.1511
## F-statistic: 5.51 on 3 and 73 DF, p-value: 0.001816## Analysis of Variance Table
##
## Response: ck32msc_b1
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.32909 0.164545 6.0956 0.003563 **
## Age_VEP 1 0.11716 0.117157 4.3401 0.040726 *
## Residuals 73 1.97056 0.026994
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.2869690 | 0.1688171 | 12 |
| ASD | 0.4050299 | 0.1737464 | 46 |
| TD | 0.4994934 | 0.1999146 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32msc_b2 ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.29758 -0.12347 -0.02959 0.10661 0.46573
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.12553 0.07690 1.632 0.106891
## DXASD 0.13654 0.05624 2.428 0.017662 *
## DXTD 0.24146 0.06439 3.750 0.000351 ***
## Age_VEP 0.01885 0.00685 2.753 0.007455 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1723 on 73 degrees of freedom
## Multiple R-squared: 0.2053, Adjusted R-squared: 0.1727
## F-statistic: 6.288 on 3 and 73 DF, p-value: 0.0007445## Analysis of Variance Table
##
## Response: ck32msc_b2
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.33495 0.167474 5.6431 0.005262 **
## Age_VEP 1 0.22485 0.224855 7.5766 0.007455 **
## Residuals 73 2.16647 0.029678
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.1856859 | 0.1253029 | 12 |
| ASD | 0.2008587 | 0.1458467 | 46 |
| TD | 0.2945704 | 0.1695182 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32msc_b3 ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19225 -0.08447 -0.04001 0.03763 0.49128
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.083982 0.065208 1.288 0.2018
## DXASD 0.026816 0.047695 0.562 0.5757
## DXTD 0.127112 0.054600 2.328 0.0227 *
## Age_VEP 0.011878 0.005808 2.045 0.0445 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1461 on 73 degrees of freedom
## Multiple R-squared: 0.1265, Adjusted R-squared: 0.09063
## F-statistic: 3.525 on 3 and 73 DF, p-value: 0.01907## Analysis of Variance Table
##
## Response: ck32msc_b3
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.13644 0.068218 3.1965 0.04669 *
## Age_VEP 1 0.08924 0.089239 4.1815 0.04447 *
## Residuals 73 1.55793 0.021342
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.1354398 | 0.0801958 | 12 |
| ASD | 0.1315652 | 0.0719190 | 46 |
| TD | 0.1372632 | 0.0845606 | 19 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32msc_b4 ~ DX + Age_VEP, data = av)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.10912 -0.05835 -0.01854 0.03883 0.18787
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.118378 0.034246 3.457 0.000915 ***
## DXASD -0.001921 0.025049 -0.077 0.939072
## DXTD 0.004881 0.028675 0.170 0.865301
## Age_VEP 0.001993 0.003050 0.653 0.515671
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07672 on 73 degrees of freedom
## Multiple R-squared: 0.006928, Adjusted R-squared: -0.03388
## F-statistic: 0.1697 on 3 and 73 DF, p-value: 0.9165## Analysis of Variance Table
##
## Response: ck32msc_b4
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.00049 0.0002430 0.0413 0.9596
## Age_VEP 1 0.00251 0.0025116 0.4267 0.5157
## Residuals 73 0.42970 0.0058863
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 9.904167 | 8.766786 | 12 |
| ASD | 10.093261 | 7.948050 | 46 |
| TD | 13.526000 | 8.960001 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = P60_N75_Amp_2s ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.976 -5.599 -2.437 4.490 21.394
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.6097 3.5760 1.289 0.2014
## DXASD 0.6599 2.6627 0.248 0.8049
## DXTD 4.4838 3.0192 1.485 0.1418
## Age_VEP 0.6375 0.3233 1.972 0.0524 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.181 on 74 degrees of freedom
## Multiple R-squared: 0.08156, Adjusted R-squared: 0.04433
## F-statistic: 2.19 on 3 and 74 DF, p-value: 0.09628## Analysis of Variance Table
##
## Response: P60_N75_Amp_2s
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 179.6 89.801 1.3416 0.26771
## Age_VEP 1 260.3 260.256 3.8882 0.05237 .
## Residuals 74 4953.2 66.936
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 22.39750 | 10.71956 | 12 |
| ASD | 22.38087 | 11.34465 | 46 |
| TD | 28.21900 | 17.26674 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = n75_p100_amp_2s ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.594 -8.607 -2.381 6.658 47.502
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24.0431 5.7249 4.200 7.36e-05 ***
## DXASD -0.1630 4.2628 -0.038 0.970
## DXTD 5.5536 4.8336 1.149 0.254
## Age_VEP -0.1981 0.5176 -0.383 0.703
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13.1 on 74 degrees of freedom
## Multiple R-squared: 0.04018, Adjusted R-squared: 0.001268
## F-statistic: 1.033 on 3 and 74 DF, p-value: 0.3832## Analysis of Variance Table
##
## Response: n75_p100_amp_2s
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 506.3 253.146 1.4756 0.2353
## Age_VEP 1 25.1 25.142 0.1466 0.7029
## Residuals 74 12695.1 171.555## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 56.24167 | 9.635017 | 12 |
| ASD | 51.21957 | 6.625158 | 46 |
| TD | 49.32500 | 7.710818 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = P60_L_2s ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -22.7817 -4.1953 -0.5373 3.3182 19.0784
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60.9946 3.1797 19.183 < 2e-16 ***
## DXASD -5.4448 2.3677 -2.300 0.02429 *
## DXTD -7.6905 2.6847 -2.865 0.00543 **
## Age_VEP -0.5723 0.2875 -1.991 0.05020 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.275 on 74 degrees of freedom
## Multiple R-squared: 0.1286, Adjusted R-squared: 0.09323
## F-statistic: 3.639 on 3 and 74 DF, p-value: 0.01655## Analysis of Variance Table
##
## Response: P60_L_2s
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 368.0 184.014 3.4770 0.03604 *
## Age_VEP 1 209.7 209.740 3.9631 0.05020 .
## Residuals 74 3916.3 52.923
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 73.41667 | 10.121609 | 12 |
| ASD | 69.51304 | 7.077338 | 46 |
| TD | 69.01500 | 4.790591 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = N75_L_2s ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.379 -3.473 -1.258 1.374 26.488
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 75.0533 3.1289 23.987 <2e-16 ***
## DXASD -4.0492 2.3298 -1.738 0.0864 .
## DXTD -4.6681 2.6418 -1.767 0.0813 .
## Age_VEP -0.1971 0.2829 -0.697 0.4882
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.159 on 74 degrees of freedom
## Multiple R-squared: 0.04897, Adjusted R-squared: 0.01041
## F-statistic: 1.27 on 3 and 74 DF, p-value: 0.2909## Analysis of Variance Table
##
## Response: N75_L_2s
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 170.4 85.190 1.6624 0.1967
## Age_VEP 1 24.9 24.869 0.4853 0.4882
## Residuals 74 3792.1 51.244## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 102.75000 | 10.788251 | 12 |
| ASD | 97.58261 | 6.804649 | 46 |
| TD | 96.25500 | 5.664894 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = P100_L_2s ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -16.8166 -4.8078 -0.4171 3.3142 22.1933
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 104.5790 3.1903 32.780 <2e-16 ***
## DXASD -5.3300 2.3756 -2.244 0.0278 *
## DXTD -6.7928 2.6937 -2.522 0.0138 *
## Age_VEP -0.2202 0.2884 -0.764 0.4476
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.299 on 74 degrees of freedom
## Multiple R-squared: 0.08593, Adjusted R-squared: 0.04887
## F-statistic: 2.319 on 3 and 74 DF, p-value: 0.08236## Analysis of Variance Table
##
## Response: P100_L_2s
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 339.6 169.778 3.1867 0.04704 *
## Age_VEP 1 31.1 31.058 0.5829 0.44759
## Residuals 74 3942.6 53.278
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.3917292 | 0.1571592 | 12 |
| ASD | 0.3014239 | 0.1221147 | 46 |
| TD | 0.3794875 | 0.1205072 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32smsc_b1 ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.26941 -0.09414 -0.01268 0.08854 0.27698
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.339655 0.055508 6.119 4.1e-08 ***
## DXASD -0.085674 0.041332 -2.073 0.0417 *
## DXTD -0.003764 0.046866 -0.080 0.9362
## Age_VEP 0.006270 0.005018 1.249 0.2154
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.127 on 74 degrees of freedom
## Multiple R-squared: 0.1151, Adjusted R-squared: 0.07922
## F-statistic: 3.208 on 3 and 74 DF, p-value: 0.02788## Analysis of Variance Table
##
## Response: ck32smsc_b1
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.13005 0.065025 4.0318 0.02178 *
## Age_VEP 1 0.02518 0.025177 1.5611 0.21545
## Residuals 74 1.19347 0.016128
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.3298437 | 0.1989379 | 12 |
| ASD | 0.3443356 | 0.1324750 | 46 |
| TD | 0.3793687 | 0.1583703 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32smsc_b2 ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.23378 -0.12039 -0.00236 0.07494 0.38294
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.277183 0.065776 4.214 7e-05 ***
## DXASD 0.019175 0.048978 0.391 0.697
## DXTD 0.058099 0.055536 1.046 0.299
## Age_VEP 0.006341 0.005947 1.066 0.290
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1505 on 74 degrees of freedom
## Multiple R-squared: 0.02855, Adjusted R-squared: -0.01083
## F-statistic: 0.725 on 3 and 74 DF, p-value: 0.5403## Analysis of Variance Table
##
## Response: ck32smsc_b2
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.02351 0.011755 0.5190 0.5972
## Age_VEP 1 0.02575 0.025748 1.1369 0.2898
## Residuals 74 1.67587 0.022647## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.1728889 | 0.0912998 | 12 |
| ASD | 0.1960326 | 0.1103896 | 46 |
| TD | 0.2479517 | 0.1741343 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32smsc_b3 ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.20355 -0.08374 -0.01897 0.04086 0.41512
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.087394 0.054448 1.605 0.1127
## DXASD 0.030747 0.040543 0.758 0.4506
## DXTD 0.088982 0.045971 1.936 0.0567 .
## Age_VEP 0.010294 0.004922 2.091 0.0399 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1246 on 74 degrees of freedom
## Multiple R-squared: 0.09517, Adjusted R-squared: 0.05849
## F-statistic: 2.595 on 3 and 74 DF, p-value: 0.05885## Analysis of Variance Table
##
## Response: ck32smsc_b3
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.05292 0.026461 1.7052 0.18880
## Age_VEP 1 0.06786 0.067864 4.3732 0.03994 *
## Residuals 74 1.14832 0.015518
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## `geom_smooth()` using formula = 'y ~ x'
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 0.1490833 | 0.0553816 | 12 |
| ASD | 0.1126092 | 0.0592631 | 46 |
| TD | 0.1472000 | 0.1020883 | 20 |
## **Multiple regression including Dx and Age, Reference is ADNP**##
## Call:
## lm(formula = ck32smsc_b4 ~ DX + Age_VEP, data = avs)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.09815 -0.04701 -0.01569 0.03646 0.36811
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.110174 0.031145 3.537 0.000702 ***
## DXASD -0.033014 0.023191 -1.424 0.158783
## DXTD 0.004451 0.026297 0.169 0.866041
## Age_VEP 0.004685 0.002816 1.664 0.100380
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07126 on 74 degrees of freedom
## Multiple R-squared: 0.09095, Adjusted R-squared: 0.0541
## F-statistic: 2.468 on 3 and 74 DF, p-value: 0.06867## Analysis of Variance Table
##
## Response: ck32smsc_b4
## Df Sum Sq Mean Sq F value Pr(>F)
## DX 2 0.02354 0.0117693 2.3179 0.1056
## Age_VEP 1 0.01406 0.0140563 2.7683 0.1004
## Residuals 74 0.37575 0.0050776## `geom_smooth()` using formula = 'y ~ x'
methylation
| DX | Mean | Standard Deviation | Sample Size |
|---|---|---|---|
| ADNP | 5.7725 | 4.933933 | 12 |
##
## Call:
## lm(formula = P60_N75_Amp_1m ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.415 -3.405 0.218 1.738 10.797
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.3253 4.9763 -0.065 0.949
## ADNP_meth2 0.9373 3.2475 0.289 0.779
## Age_VEP 0.6756 0.4993 1.353 0.209
##
## Residual standard error: 4.963 on 9 degrees of freedom
## Multiple R-squared: 0.1722, Adjusted R-squared: -0.01181
## F-statistic: 0.9358 on 2 and 9 DF, p-value: 0.4273## Analysis of Variance Table
##
## Response: P60_N75_Amp_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 0.996 0.996 0.0405 0.8451
## Age_VEP 1 45.104 45.104 1.8312 0.2090
## Residuals 9 221.680 24.631##
## Call:
## lm(formula = P60_L_1m ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -23.833 -2.027 1.566 3.369 18.883
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 64.559 11.073 5.830 0.00025 ***
## ADNP_meth2 1.422 7.226 0.197 0.84840
## Age_VEP -1.387 1.111 -1.248 0.24343
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 11.04 on 9 degrees of freedom
## Multiple R-squared: 0.1834, Adjusted R-squared: 0.001892
## F-statistic: 1.01 on 2 and 9 DF, p-value: 0.4019## Analysis of Variance Table
##
## Response: P60_L_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 56.43 56.427 0.4627 0.5135
## Age_VEP 1 190.01 190.011 1.5581 0.2434
## Residuals 9 1097.53 121.948##
## Call:
## lm(formula = N75_L_1m ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.2587 -5.1014 -0.0431 3.5036 14.9323
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 68.6258 8.5036 8.070 2.06e-05 ***
## ADNP_meth2 8.0062 5.5494 1.443 0.183
## Age_VEP -0.1609 0.8532 -0.189 0.855
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.481 on 9 degrees of freedom
## Multiple R-squared: 0.2265, Adjusted R-squared: 0.05467
## F-statistic: 1.318 on 2 and 9 DF, p-value: 0.3147## Analysis of Variance Table
##
## Response: N75_L_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 187.04 187.042 2.6005 0.1413
## Age_VEP 1 2.56 2.559 0.0356 0.8546
## Residuals 9 647.32 71.924##
## Call:
## lm(formula = P100_L_1m ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.654 -4.650 -1.817 4.916 14.263
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 92.6210 8.8354 10.483 2.41e-06 ***
## ADNP_meth2 13.7774 5.7658 2.389 0.0406 *
## Age_VEP 0.1210 0.8865 0.137 0.8944
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.812 on 9 degrees of freedom
## Multiple R-squared: 0.4109, Adjusted R-squared: 0.28
## F-statistic: 3.139 on 2 and 9 DF, p-value: 0.09243## Analysis of Variance Table
##
## Response: P100_L_1m
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 486.00 486.00 6.2593 0.03376 *
## Age_VEP 1 1.45 1.45 0.0186 0.89439
## Residuals 9 698.80 77.64
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Call:
## lm(formula = ck32msc_b1 ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25362 -0.05457 0.01912 0.05846 0.18474
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.17966 0.12197 1.473 0.1748
## ADNP_meth2 -0.04207 0.07960 -0.529 0.6099
## Age_VEP 0.02461 0.01224 2.011 0.0752 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1216 on 9 degrees of freedom
## Multiple R-squared: 0.3916, Adjusted R-squared: 0.2563
## F-statistic: 2.896 on 2 and 9 DF, p-value: 0.1069## Analysis of Variance Table
##
## Response: ck32msc_b1
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 0.025859 0.025859 1.7475 0.2188
## Age_VEP 1 0.059844 0.059844 4.0442 0.0752 .
## Residuals 9 0.133176 0.014797
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Call:
## lm(formula = ck32msc_b2 ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.140977 -0.088287 -0.008967 0.042636 0.274802
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.16077 0.13843 1.161 0.275
## ADNP_meth2 -0.14727 0.09033 -1.630 0.137
## Age_VEP 0.02047 0.01389 1.474 0.175
##
## Residual standard error: 0.1381 on 9 degrees of freedom
## Multiple R-squared: 0.4528, Adjusted R-squared: 0.3313
## F-statistic: 3.724 on 2 and 9 DF, p-value: 0.0663## Analysis of Variance Table
##
## Response: ck32msc_b2
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 0.100559 0.100559 5.2762 0.04723 *
## Age_VEP 1 0.041404 0.041404 2.1724 0.17460
## Residuals 9 0.171529 0.019059
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Call:
## lm(formula = ck32msc_b3 ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.12561 -0.06251 -0.01077 0.02365 0.27958
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.05201 0.11907 0.437 0.673
## ADNP_meth2 -0.03980 0.07770 -0.512 0.621
## Age_VEP 0.01716 0.01195 1.436 0.185
##
## Residual standard error: 0.1188 on 9 degrees of freedom
## Multiple R-squared: 0.2651, Adjusted R-squared: 0.1018
## F-statistic: 1.624 on 2 and 9 DF, p-value: 0.25## Analysis of Variance Table
##
## Response: ck32msc_b3
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 0.016697 0.016697 1.1840 0.3048
## Age_VEP 1 0.029096 0.029096 2.0633 0.1847
## Residuals 9 0.126916 0.014102##
## Call:
## lm(formula = ck32msc_b4 ~ ADNP_meth + Age_VEP, data = adnponly)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.11416 -0.05048 -0.01117 0.02542 0.15255
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.066196 0.083056 0.797 0.446
## ADNP_meth2 -0.008201 0.054201 -0.151 0.883
## Age_VEP 0.008406 0.008333 1.009 0.339
##
## Residual standard error: 0.08283 on 9 degrees of freedom
## Multiple R-squared: 0.1271, Adjusted R-squared: -0.06685
## F-statistic: 0.6554 on 2 and 9 DF, p-value: 0.5424## Analysis of Variance Table
##
## Response: ck32msc_b4
## Df Sum Sq Mean Sq F value Pr(>F)
## ADNP_meth 1 0.002012 0.0020118 0.2932 0.6013
## Age_VEP 1 0.006982 0.0069815 1.0175 0.3395
## Residuals 9 0.061752 0.0068613##old below