Nesting loop reiterating wrong code

Hello,

I would like to write a loop that runs 5000 times (rows) an equation that calculates 1 row of 8 columns of data. My code so far is:

for f=1:4999;
    %Create an inner loop
    for g=1:8
        %Compute randomized slope
        h=glmfit(arr(e,1),arr(e,g+1),'normal');
        %Put randomized slope in slp
        slp(g)=h(2);
    end
    %Computer differences in randomized treatment slopes
      diff(f)=mean(slp(1:3))-mean(slp(4:8));
end

Instead of looping the calculation of the slope and the creation of the row of 8 slopes, it ends up looping just the calculation of the differences in randomized treatment slopes.

I'm rather new to MatLab (and self taught) so any advice would be greatly appreciated. Thank you !

Edit: Here is my code as a whole

%Read Original Data
arr=csvread('testdata.csv',1,0);
%Fit a linear model to each treatment, and put slopes in slpobs
a=zeros(1,8);
for b=1:8
  c=glmfit(arr(:,1),arr(:,b+1),'normal');
  d(b)=(c(2));
end
slpobs=transpose(d);
%Compute the observed differences between treatment means
diffobs=mean(d(1:3))-mean(d(4:8));
%Create randomized times
e=fix(random('uniform',1,176,176,1));
%Create array for randomized slopes
diff=zeros(1,4999);
%Create an outer loop
for f=1:4999
  %Create an inner loop
  for g=1:8
      %Compute randomized slope
      h=glmfit(arr(e,1),arr(e,g+1),'normal');
      %Put randomized slope in slp
      slp(g)=h(2);
  end
  %Computer differences in randomized treatment slopes
    diff(f)=mean(slp(1:3))-mean(slp(4:8));
end
%Take the absolute value of randomized differences
absdiff=abs(diff);
%Find instances where the random difference exceeds the observed difference
index=sum(absdiff>=diffobs);

Answer 1

[Brittany]

Delete the semicolon from the end of your first for statement. That is probably why it is not doing the inner loop.

Answer 2

[Matt Tearle]

Nothing inside your outer loop (except the indexed assignment at the end) references the loop variable f, so you're doing exactly the same calculation each time. Perhaps the line

h=glmfit(arr(e,1),arr(e,g+1),'normal');

should be

h=glmfit(arr(f+e,1),arr(f+e,g+1),'normal');

instead? Or something like that?

Also, if you're not already, preallocate your arrays!