how to get the fstat out of fitlm MATLAB

Question

I'm using lm = fitlm(X,y,'linear') it works nicely and outputs

lm = 


Linear regression model:
    y ~ 1 + x1 + x2 + x3

Estimated Coefficients:
               Estimate    SE           tStat      pValue    
    (Intercept)      2.1338      0.27403     7.7869    1.6357e-13
    x1              0.07202      0.01757     4.0991    5.5484e-05
    x2             -0.35927      0.12078    -2.9746     0.0032094
    x3             0.020363    0.0041479     4.9092    1.6168e-06


Number of observations: 264, Error degrees of freedom: 260
Root Mean Squared Error: 0.835
R-squared: 0.154,  Adjusted R-Squared 0.144
F-statistic vs. constant model: 15.8, p-value = 1.93e-09

somethings like this. However i want to get the F-statistic value of each model (in a loop) and export to a file. My problem is.. I can't find the variable of lm that contains F-statistic and it's pvalue; Also lm.Steps is empty..

================================================================================ And another question, under what condition should I use this regression results? if x1 is the component i want after regressing out other component and residuals, should I say x1 is responsible for y when p-value of x1 is less than 0.05 or p-value of the model is less than 0.05?

Answer 1

As suggested in the documentation for fitlm you can use the anova function on your model. Then extract the values (these will be for all x values) and save by whatever method you prefer:

tbl = anova(lm);

% something like this for just your desired values
A = [double(tbl.F),double(tbl.pValue)];
csvwrite('output.csv',A);

% or this dumps the entire result of anova to file
tbl2 = dataset2table(tbl);
writetable(tbl2, 'output.csv');

---

Okay for the other variant - if you want to use multiple inputs of X then you can use the summary option on anova and extract the F and p values from that:

X = cell array of inputs of length n;

F = zeros(n,1);
p = zeros(n,1);

for m = 1:n;
    lm = fitlm(X{n},y,'linear')
    tbl = anova(lm,'summary');

    % you may want to check these indices but should be the right points:

    F(n) = double(tbl(2,4));
    p(n) = double(tbl(2,5)); 
end