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matlab and perl updates
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@kruggles7
kruggles7 committed Jul 9, 2015
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216 changes: 216 additions & 0 deletions ACEv2.m
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%Find total ACD score per subject

load filtered_final_2015_05_06

variables={'childhood_Note1/Childhood_1','childhood_Note1/Childhood_3','childhood_Note1/Childhood_5','childhood_Note1/Childhood_7','childhood_Note1/Childhood_9',...
'childhood_Note1/Childhood_11','childhood_Note1/Childhood_13','childhood_Note1/Childhood_15','childhood_Note1/Childhood_17','childhood_Note1/Childhood_19'};

variables_age={'childhood_Note1/Childhood_2','childhood_Note1/Childhood_4','childhood_Note1/Childhood_6','childhood_Note1/Childhood_8','childhood_Note1/Childhood_10',...
'childhood_Note1/Childhood_12','childhood_Note1/Childhood_14','childhood_Note1/Childhood_16','childhood_Note1/Childhood_18','childhood_Note1/Childhood_20'};

variables_lab={'parent/adult swore, humiliated or made afraid of being physically hurt', 'parent/adult pushed, slapped or threw something at',...
'parent/adult fondled or touched in a sexual way or had intercourse with', 'felt as if no one in the family loved or supported them',...
'often felt that they did not have enough to eat, was not protected', 'parents separated/divorced', 'mother/stepmother physically abused',...
'lived with someone who had drug/drinking problem', 'household member depressed/mentally ill', 'household member went to prison'};


questions={'Benchmark_Note1/Benchmark_1', 'Benchmark_Note1/Benchmark_2', 'Benchmark_Note1/Benchmark_3', 'Benchmark_Note1/Benchmark_4',...
'Benchmark_Note1/Benchmark_5','Benchmark_Note1/Benchmark_6', 'Benchmark_Note1/Benchmark_13', 'Benchmark_Note1/Benchmark_14',...
'Benchmark_Note1/Benchmark_17', 'Benchmark_Note1/Benchmark_18', 'Benchmark_Note1/Benchmark_19', 'Benchmark_Note1/Benchmark_20', 'Benchmark_Note1/Benchmark_22', ...
'Benchmark_Note1/Benchmark_24', 'Benchmark_Note1/Benchmark_25', 'Benchmark_Note1/Benchmark_28', 'Benchmark_Note1/Benchmark_31' };

quest_labels={'first got drunk', 'started drinking on regular basis', 'first tried marijuana', 'started using marijuana on a regular basis',...
'first had sexual intercourse', 'first had sexual intercourse on a regular basis', 'first started using POs', 'first started using POs regularly',...
'first snorted POs', 'first smoked POs', 'first injected any drug', 'first injected POs', 'first used heroin',...
'first injected heroin', 'first started using heroin regularly', 'first used benzos', 'first started using benzos regularly'};

birthday='Soc_Note1/Soc_3';

[r,c]=size(filtered_final);
filtered_data=filtered_final(2:r,:);
headers=filtered_final(1,:);
plot1=0;
plot2=0;


FILE_IN=fopen('ACE.txt', 'wt');

%ACE scale
ACE_mat=zeros(r-1,1);
for i=1:numel(variables)
D=variables{i};
indx=find(strcmp(headers,D)==1);
data_mat=filtered_data(:,indx);
indx_nan=find(strcmp('NaN', data_mat)==1);
for j=1:numel(indx_nan)
data_mat{indx_nan(j)}=NaN;
end
data_mat=cell2mat(data_mat);
data_mat(data_mat==77)=NaN;
data_mat(data_mat==88)=NaN;
data_mat(data_mat==99)=NaN;
for j=1:numel(data_mat)
if data_mat(j)==1
ACE_mat(j)=ACE_mat(j)+1;
end
end

end

m=nanmean(ACE_mat);
s=nanstd(ACE_mat);
new_mat=ACE_mat(isnan(ACE_mat)==0);
n=numel(new_mat);
fprintf(FILE_IN, '%s\n\n', ['ACE results: N = ' num2str(n) ', Mean = ' num2str(m) ', SD = ' num2str(s) ]);

for i=1:numel(questions)
D=questions{i};
indx=find(strcmp(headers,D)==1);
data_mat=filtered_data(:,indx);
indx_nan=find(strcmp('NaN', data_mat)==1);
for j=1:numel(indx_nan)
data_mat{indx_nan(j)}=NaN;
end
data_mat=cell2mat(data_mat);
data_mat(data_mat==77)=NaN;
data_mat(data_mat==88)=NaN;
data_mat(data_mat==99)=NaN;
data_mat(data_mat==0)=NaN;
indx2=find(isnan(data_mat)==0 & isnan(ACE_mat)==0);
x=data_mat(indx2); %interval
y=ACE_mat(indx2); %ordinal
[rho,p]=corr(x,y);
%spearman correlation
[rho_s, p_s]=corr(x,y,'Type','Spearman');
%nonparametric regression
m=nanmean(x);
s=nanstd(x);

fprintf(FILE_IN, '%s\n', ['Age when ' quest_labels{i} ]);
fprintf(FILE_IN, '%s\n', ['N = ' num2str(numel(y)) ', Mean = ' num2str(m) ', SD = ' num2str(s) ]);
fprintf(FILE_IN, '%s\n', ['pearson correlation ' num2str(rho) ]);
fprintf(FILE_IN, '%s\n', ['pvalue ' num2str(p) ]);
fprintf(FILE_IN, '%s\n', ['spearman correlation ' num2str(rho_s) ]);
fprintf(FILE_IN, '%s\n\n', ['pvalue ' num2str(p_s) ]);
if (plot1==1)
normplot(x);
print (gcf, '-dpng', ['normplot' num2str(i)]);
close
if i==1
normplot(y)
print (gcf, '-dpng', 'normplot_ACE')
close
end

scatter(x,y);
xlabel(['Age when ' quest_labels{i} ]);
ylabel('ACE score');
print (gcf, '-dpng', ['plot' num2str(i)]);
close
end

end

%BY AGE----------------------------------------------------------------

%ACE age
ACE_age=zeros(r-1,numel(variables_age));
ACE_age_=cell(r-1, numel(variables_age));
for i=1:numel(variables_age)
D=variables_age{i};
indx=find(strcmp(headers,D)==1);
data_mat=filtered_data(:,indx);
indx_nan=find(strcmp('NaN', data_mat)==1);
for j=1:numel(indx_nan)
data_mat{indx_nan(j)}=NaN;
end
data_mat2=data_mat;
ages=double.empty;
%fix_dates
for j=1:numel(data_mat2)
temp=data_mat2{j};
if isempty(strfind(temp, '/'))==0
indx3=strfind(temp, '/');
N='';
for k=1:indx3(1)-1
N=[N temp(k)];
end
data_mat2{j}=str2double(N);
elseif isempty(strfind(temp, '-'))==0
indx3=strfind(temp, '-');
N='';
for k=1:indx3(1)-1
N=[N temp(k)];
end
data_mat2{j}=str2double(N);

elseif isempty(strfind(temp, ','))==0
indx3=strfind(temp, ',');
N='';
for k=1:indx3(1)-1
N=[N temp(k)];
end
data_mat2{j}=str2double(N);
end
end
data_final=cell2mat(data_mat2);
ACE_age(:,i)=data_final;
ACE_age_(:,i)=data_mat;

end
fprintf(FILE_IN, '\n%s\n', 'Average age of traumatic events (AATE):' );
ACE_age_final=nanmean(ACE_age,2);

m=nanmean(ACE_age_final);
s=nanstd(ACE_age_final);
new_mat=ACE_age_final(isnan(ACE_age_final)==0);
n=numel(new_mat);
fprintf(FILE_IN, '%s\n\n', ['AATE results: N = ' num2str(n) ', Mean = ' num2str(m) ', SD = ' num2str(s) ]);

for i=1:numel(questions)
D=questions{i};
indx=find(strcmp(headers,D)==1);
data_mat=filtered_data(:,indx);
indx_nan=find(strcmp('NaN', data_mat)==1);
for j=1:numel(indx_nan)
data_mat{indx_nan(j)}=NaN;
end
data_mat=cell2mat(data_mat);
data_mat(data_mat==77)=NaN;
data_mat(data_mat==88)=NaN;
data_mat(data_mat==99)=NaN;
data_mat(data_mat==0)=NaN;
indx2=find(isnan(data_mat)==0 & isnan(ACE_age_final)==0);
x=data_mat(indx2); %interval
y=ACE_age_final(indx2); %ordinal
[rho,p]=corr(x,y);
%spearman correlation
[rho_s, p_s]=corr(x,y,'Type','Spearman');
%nonparametric regression


fprintf(FILE_IN, '%s\n', ['Age when ' quest_labels{i} ]);
fprintf(FILE_IN, '%s\n', ['N ' num2str(numel(y)) ]);
fprintf(FILE_IN, '%s\n', ['pearson correlation ' num2str(rho) ]);
fprintf(FILE_IN, '%s\n', ['pvalue ' num2str(p) ]);
fprintf(FILE_IN, '%s\n', ['spearman correlation ' num2str(rho_s) ]);
fprintf(FILE_IN, '%s\n\n', ['pvalue ' num2str(p_s) ]);
if (plot2==1)
normplot(x);
print (gcf, '-dpng', ['normplot' num2str(i)]);
close
if i==1
normplot(y)
print (gcf, '-dpng', 'normplot_AATE')
close
end

scatter(x,y);
xlabel(['Age when ' quest_labels{i} ]);
ylabel('Average age of traumatic events (AATE)');
print (gcf, '-dpng', ['plot' num2str(i) '_AATE']);
close
end

end

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