code written: 2020-01-18
last ran: 2020-01-18
website: http://rpubs.com/navona/SPINS_normalityClinical
MVN tests. All MVN tests suggest that the \(Y\) set is not multivariate normal.
Mardia’s
## Test Statistic p value Result
## 1 Mardia Skewness 1394.10367987404 9.75220120854385e-73 NO
## 2 Mardia Kurtosis 14.1409556484297 0 NO
## 3 MVN <NA> <NA> NO
Henze-Zirkler’s
## Test HZ p value MVN
## 1 Henze-Zirkler 1.046297 0 NO
Royston’s
## Test H p value MVN
## 1 Royston 481.3512 7.778447e-94 NO
Doornik-Hansen’s
## Test E df p value MVN
## 1 Doornik-Hansen 18105.83 28 0 NO
Energy
## Test Statistic p value MVN
## 1 E-statistic 3.524195 0 NO
MVN plot. The Chi-square Q-Q plot shows large deviations from the reference line, which indicates departure from the multivariate normal distribution.

Multivariate outliers. Multivariate outlier detection methods suggest so many outliers that it would not make sense to remove them.
Mahalanobis distance

Adjusted Mahalanobis distance

Univariate tests. Here, we see that many of the distributions of many of the variables in the \(Y\) set are not normal.
Shapiro-Wilk’s
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Shapiro-Wilk
|
Processing speed
|
0.9897
|
0.0076
|
NO
|
|
Shapiro-Wilk
|
Attention & vigilance
|
0.9665
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
Working memory
|
0.9951
|
0.2501
|
YES
|
|
Shapiro-Wilk
|
Verbal learning
|
0.9847
|
4e-04
|
NO
|
|
Shapiro-Wilk
|
Visual learning
|
0.9829
|
1e-04
|
NO
|
|
Shapiro-Wilk
|
Problem solving
|
0.9849
|
4e-04
|
NO
|
|
Shapiro-Wilk
|
RMET
|
0.9433
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
RAD
|
0.9277
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
ER_40
|
0.8693
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
TASIT_1
|
0.8926
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
TASIT_2
|
0.8823
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
TASIT_3
|
0.9284
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
IRI
|
0.9914
|
0.0227
|
NO
|
|
Shapiro-Wilk
|
EA
|
0.9332
|
<0.001
|
NO
|
Cramer-von Mises
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Cramer-von Mises
|
Processing speed
|
0.1380
|
0.0342
|
NO
|
|
Cramer-von Mises
|
Attention & vigilance
|
0.2051
|
0.0046
|
NO
|
|
Cramer-von Mises
|
Working memory
|
0.0739
|
0.2478
|
YES
|
|
Cramer-von Mises
|
Verbal learning
|
0.1379
|
0.0343
|
NO
|
|
Cramer-von Mises
|
Visual learning
|
0.3089
|
3e-04
|
NO
|
|
Cramer-von Mises
|
Problem solving
|
0.2073
|
0.0043
|
NO
|
|
Cramer-von Mises
|
RMET
|
0.9903
|
<0.001
|
NO
|
|
Cramer-von Mises
|
RAD
|
1.5912
|
<0.001
|
NO
|
|
Cramer-von Mises
|
ER_40
|
2.3562
|
<0.001
|
NO
|
|
Cramer-von Mises
|
TASIT_1
|
1.7538
|
<0.001
|
NO
|
|
Cramer-von Mises
|
TASIT_2
|
2.2039
|
<0.001
|
NO
|
|
Cramer-von Mises
|
TASIT_3
|
0.8612
|
<0.001
|
NO
|
|
Cramer-von Mises
|
IRI
|
0.0736
|
0.2505
|
YES
|
|
Cramer-von Mises
|
EA
|
0.9933
|
<0.001
|
NO
|
Lilliefors
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Processing speed
|
0.0449
|
0.0564
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Attention & vigilance
|
0.0599
|
0.0019
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Working memory
|
0.0446
|
0.0605
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Verbal learning
|
0.0600
|
0.0018
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Visual learning
|
0.0684
|
2e-04
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Problem solving
|
0.0598
|
0.0019
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
RMET
|
0.1275
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
RAD
|
0.1392
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
ER_40
|
0.1405
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
TASIT_1
|
0.1590
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
TASIT_2
|
0.1461
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
TASIT_3
|
0.1051
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
IRI
|
0.0394
|
0.1487
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
EA
|
0.0957
|
<0.001
|
NO
|
Shapiro-Francia
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Shapiro-Francia
|
Processing speed
|
0.9906
|
0.0151
|
NO
|
|
Shapiro-Francia
|
Attention & vigilance
|
0.9665
|
<0.001
|
NO
|
|
Shapiro-Francia
|
Working memory
|
0.9960
|
0.3841
|
YES
|
|
Shapiro-Francia
|
Verbal learning
|
0.9854
|
9e-04
|
NO
|
|
Shapiro-Francia
|
Visual learning
|
0.9838
|
4e-04
|
NO
|
|
Shapiro-Francia
|
Problem solving
|
0.9866
|
0.0017
|
NO
|
|
Shapiro-Francia
|
RMET
|
0.9445
|
<0.001
|
NO
|
|
Shapiro-Francia
|
RAD
|
0.9291
|
<0.001
|
NO
|
|
Shapiro-Francia
|
ER_40
|
0.8664
|
<0.001
|
NO
|
|
Shapiro-Francia
|
TASIT_1
|
0.8918
|
<0.001
|
NO
|
|
Shapiro-Francia
|
TASIT_2
|
0.8831
|
<0.001
|
NO
|
|
Shapiro-Francia
|
TASIT_3
|
0.9269
|
<0.001
|
NO
|
|
Shapiro-Francia
|
IRI
|
0.9917
|
0.0296
|
NO
|
|
Shapiro-Francia
|
EA
|
0.9330
|
<0.001
|
NO
|
Anderson-Darling
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Anderson-Darling
|
Processing speed
|
0.8823
|
0.0238
|
NO
|
|
Anderson-Darling
|
Attention & vigilance
|
1.7529
|
2e-04
|
NO
|
|
Anderson-Darling
|
Working memory
|
0.4609
|
0.2586
|
YES
|
|
Anderson-Darling
|
Verbal learning
|
1.0538
|
0.009
|
NO
|
|
Anderson-Darling
|
Visual learning
|
1.9351
|
1e-04
|
NO
|
|
Anderson-Darling
|
Problem solving
|
1.4463
|
0.001
|
NO
|
|
Anderson-Darling
|
RMET
|
6.1082
|
<0.001
|
NO
|
|
Anderson-Darling
|
RAD
|
9.3415
|
<0.001
|
NO
|
|
Anderson-Darling
|
ER_40
|
13.4772
|
<0.001
|
NO
|
|
Anderson-Darling
|
TASIT_1
|
10.5432
|
<0.001
|
NO
|
|
Anderson-Darling
|
TASIT_2
|
13.2858
|
<0.001
|
NO
|
|
Anderson-Darling
|
TASIT_3
|
5.3011
|
<0.001
|
NO
|
|
Anderson-Darling
|
IRI
|
0.5848
|
0.1271
|
YES
|
|
Anderson-Darling
|
EA
|
6.0253
|
<0.001
|
NO
|
Univariate visualizations. The same data is visualized as qq-plots and histograms below. In the qq-plots, the coloured line is the reference line. In the histograms, the coloured line is the sample mean, and the shaded area is density.
qq-plots

histograms

Power transformation. We transformed the \(Y\) set data with a Yeo-Johnson power transformation (from the car package). Yeo-Johnson is employed as there are negative values in our \(Y\) set (namely, in the EA task). However, we observer that the transformation does not result in more tests achieving normality.
Shapiro-Wilk’s
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Shapiro-Wilk
|
Processing speed
|
0.9956
|
0.3562
|
YES
|
|
Shapiro-Wilk
|
Attention & vigilance
|
0.9870
|
0.0017
|
NO
|
|
Shapiro-Wilk
|
Working memory
|
0.9944
|
0.1832
|
YES
|
|
Shapiro-Wilk
|
Verbal learning
|
0.9943
|
0.1684
|
YES
|
|
Shapiro-Wilk
|
Visual learning
|
0.9890
|
0.0059
|
NO
|
|
Shapiro-Wilk
|
Problem solving
|
0.9864
|
0.0012
|
NO
|
|
Shapiro-Wilk
|
RMET
|
0.9855
|
7e-04
|
NO
|
|
Shapiro-Wilk
|
RAD
|
0.9765
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
ER_40
|
0.9014
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
TASIT_1
|
0.9729
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
TASIT_2
|
0.9672
|
<0.001
|
NO
|
|
Shapiro-Wilk
|
TASIT_3
|
0.9852
|
6e-04
|
NO
|
|
Shapiro-Wilk
|
IRI
|
0.9969
|
0.6795
|
YES
|
|
Shapiro-Wilk
|
EA
|
0.8988
|
<0.001
|
NO
|
Cramer-von Mises
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Cramer-von Mises
|
Processing speed
|
0.0486
|
0.5294
|
YES
|
|
Cramer-von Mises
|
Attention & vigilance
|
0.2233
|
0.0027
|
NO
|
|
Cramer-von Mises
|
Working memory
|
0.0780
|
0.2196
|
YES
|
|
Cramer-von Mises
|
Verbal learning
|
0.0873
|
0.1661
|
YES
|
|
Cramer-von Mises
|
Visual learning
|
0.1514
|
0.0227
|
NO
|
|
Cramer-von Mises
|
Problem solving
|
0.2072
|
0.0043
|
NO
|
|
Cramer-von Mises
|
RMET
|
0.2594
|
0.001
|
NO
|
|
Cramer-von Mises
|
RAD
|
0.4581
|
<0.001
|
NO
|
|
Cramer-von Mises
|
ER_40
|
1.3911
|
<0.001
|
NO
|
|
Cramer-von Mises
|
TASIT_1
|
0.5705
|
<0.001
|
NO
|
|
Cramer-von Mises
|
TASIT_2
|
0.4264
|
<0.001
|
NO
|
|
Cramer-von Mises
|
TASIT_3
|
0.1953
|
0.0061
|
NO
|
|
Cramer-von Mises
|
IRI
|
0.0466
|
0.5614
|
YES
|
|
Cramer-von Mises
|
EA
|
1.3836
|
<0.001
|
NO
|
Lilliefors
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Processing speed
|
0.0335
|
0.3775
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Attention & vigilance
|
0.0637
|
8e-04
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Working memory
|
0.0390
|
0.1735
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Verbal learning
|
0.0413
|
0.1185
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Visual learning
|
0.0554
|
0.007
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
Problem solving
|
0.0550
|
0.0077
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
RMET
|
0.0817
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
RAD
|
0.0929
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
ER_40
|
0.1103
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
TASIT_1
|
0.1035
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
TASIT_2
|
0.0875
|
<0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
TASIT_3
|
0.0630
|
0.001
|
NO
|
|
Lilliefors (Kolmogorov-Smirnov)
|
IRI
|
0.0370
|
0.2355
|
YES
|
|
Lilliefors (Kolmogorov-Smirnov)
|
EA
|
0.1216
|
<0.001
|
NO
|
Shapiro-Francia
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Shapiro-Francia
|
Processing speed
|
0.9968
|
0.5801
|
YES
|
|
Shapiro-Francia
|
Attention & vigilance
|
0.9887
|
0.0059
|
NO
|
|
Shapiro-Francia
|
Working memory
|
0.9955
|
0.3058
|
YES
|
|
Shapiro-Francia
|
Verbal learning
|
0.9951
|
0.2382
|
YES
|
|
Shapiro-Francia
|
Visual learning
|
0.9908
|
0.0194
|
NO
|
|
Shapiro-Francia
|
Problem solving
|
0.9881
|
0.0044
|
NO
|
|
Shapiro-Francia
|
RMET
|
0.9875
|
0.0032
|
NO
|
|
Shapiro-Francia
|
RAD
|
0.9783
|
<0.001
|
NO
|
|
Shapiro-Francia
|
ER_40
|
0.8961
|
<0.001
|
NO
|
|
Shapiro-Francia
|
TASIT_1
|
0.9751
|
<0.001
|
NO
|
|
Shapiro-Francia
|
TASIT_2
|
0.9700
|
<0.001
|
NO
|
|
Shapiro-Francia
|
TASIT_3
|
0.9869
|
0.0024
|
NO
|
|
Shapiro-Francia
|
IRI
|
0.9975
|
0.7588
|
YES
|
|
Shapiro-Francia
|
EA
|
0.8991
|
<0.001
|
NO
|
Anderson-Darling
|
Test
|
Variable
|
Statistic
|
p value
|
Normality
|
|
Anderson-Darling
|
Processing speed
|
0.3309
|
0.5121
|
YES
|
|
Anderson-Darling
|
Attention & vigilance
|
1.3347
|
0.0018
|
NO
|
|
Anderson-Darling
|
Working memory
|
0.5180
|
0.1873
|
YES
|
|
Anderson-Darling
|
Verbal learning
|
0.6074
|
0.1137
|
YES
|
|
Anderson-Darling
|
Visual learning
|
0.9685
|
0.0146
|
NO
|
|
Anderson-Darling
|
Problem solving
|
1.3568
|
0.0016
|
NO
|
|
Anderson-Darling
|
RMET
|
1.4943
|
7e-04
|
NO
|
|
Anderson-Darling
|
RAD
|
2.7768
|
<0.001
|
NO
|
|
Anderson-Darling
|
ER_40
|
8.4578
|
<0.001
|
NO
|
|
Anderson-Darling
|
TASIT_1
|
3.4135
|
<0.001
|
NO
|
|
Anderson-Darling
|
TASIT_2
|
2.9878
|
<0.001
|
NO
|
|
Anderson-Darling
|
TASIT_3
|
1.3557
|
0.0016
|
NO
|
|
Anderson-Darling
|
IRI
|
0.3059
|
0.5646
|
YES
|
|
Anderson-Darling
|
EA
|
8.8642
|
<0.001
|
NO
|