File size: 2,966 Bytes
2e77130
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
%% Step 3 3AOB
clear all; clc
addpath('Z:\EXPERIMENTS\mTBICoBRE\EEG\');

datadir='Z:\EXPERIMENTS\mTBICoBRE\EEG\3AOB Processed\';

homedir='Z:\EXPERIMENTS\mTBICoBRE\MANUSCRIPT 3AOB\';

cd(homedir);



load('Z:\EXPERIMENTS\mTBICoBRE\EEG\BV_Chanlocs_60.mat');

tx2disp=-500:2:1000;



% Load Data

s1_Load_Data;       



% Kill Data

s2_Kill_Data;



%% Demographics



s3_Demographics;

 

sx_Predict_Attrition;





%% Example ERPs



StdSite=find(strcmpi('FCz',{BV_Chanlocs_60.labels}));

StdT1=300; StdT2=450; 



TargSite=find(strcmpi('Pz',{BV_Chanlocs_60.labels}));

TargT1=400; TargT2=600; 



NovSite=find(strcmpi('FCz',{BV_Chanlocs_60.labels}));

NovT1=300; NovT2=450; 



ERPSITE=[StdSite,TargSite,NovSite];

ERPWINS=[StdT1,StdT2;TargT1,TargT2;NovT1,NovT2];

ERPWINS_tx2disp=[[find(tx2disp==StdT1),find(tx2disp==StdT2)];...

                 [find(tx2disp==TargT1),find(tx2disp==TargT2)];...

                 [find(tx2disp==NovT1),find(tx2disp==NovT2)] ];





s4_Example_ERPs



%% ERPs by Group



time=1;



s5_ERPs_by_Group





%% For SPSS



s6_FOR_SPSS



figure; boxplot(FORSPSS(:,[10,11,16,17,22,23])); % Raw, Scaled

skewness(FORSPSS(:,[10,11,16,17,22,23]))  % not skewed



% Calculate reliability for controls

CTL_REL=FORSPSS(FORSPSS(:,3)==1,:);



[REL.rho.F12,REL.p.F12]=corr(CTL_REL(:,11),CTL_REL(:,17),'type','Spearman','rows','pairwise'); % F_Tot 1 & 2

[REL.rho.F13,REL.p.F13]=corr(CTL_REL(:,11),CTL_REL(:,23),'type','Spearman','rows','pairwise'); % F_Tot 1 & 3

[REL.rho.F23,REL.p.F23]=corr(CTL_REL(:,17),CTL_REL(:,23),'type','Spearman','rows','pairwise'); % F_Tot 2 & 3



[REL.rho.P3b12,REL.p.P3b12]=corr(CTL_REL(:,11+1),CTL_REL(:,17+1),'type','Spearman','rows','pairwise'); % P3b 1 & 2

[REL.rho.P3b13,REL.p.P3b13]=corr(CTL_REL(:,11+1),CTL_REL(:,23+1),'type','Spearman','rows','pairwise'); % P3b 1 & 3

[REL.rho.P3b23,REL.p.P3b23]=corr(CTL_REL(:,17+1),CTL_REL(:,23+1),'type','Spearman','rows','pairwise'); % P3b 2 & 3



[REL.rho.P3a12,REL.p.P3a12]=corr(CTL_REL(:,11+2),CTL_REL(:,17+2),'type','Spearman','rows','pairwise'); % P3a 1 & 2

[REL.rho.P3a13,REL.p.P3a13]=corr(CTL_REL(:,11+2),CTL_REL(:,23+2),'type','Spearman','rows','pairwise'); % P3a 1 & 3

[REL.rho.P3a23,REL.p.P3a23]=corr(CTL_REL(:,17+2),CTL_REL(:,23+2),'type','Spearman','rows','pairwise'); % P3a 2 & 3



%% Correlations



DV=IDENTITY.QUEX(:,find(strcmp('F_Tot',IDENTITY_QUEX_HDR)));  



time=1; 

CONDI4Corr=3;  % Std, Targ, Nov



s6_Correlations



%% Predictions



quexidx=find(strcmp('F_Tot',IDENTITY_QUEX_HDR));

CONDI4Corr=2;  % Std, Targ, Nov



s6_Correlations_S1EEG_With_FrSBediffs



%% -------------- Between-Group rho-to-z



% Just type 'em in here from the plots (remember number on plots is df, not N):

r1=-.11
n1=38
r2=-.46
n2=23

clc;

t_r1 = 0.5*log((1+r1)/(1-r1));
t_r2 = 0.5*log((1+r2)/(1-r2));
z = (t_r1-t_r2)/sqrt(1/(n1-3)+1/(n2-3))
p = (1-normcdf(abs(z),0,1))*2


%% -------------- Within-Group rho-to-z

s7_Mengs_z