How perform anova tests after using regress in MATLAB?
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Hi! I'm trying to perform ANOVA analysis for a multiple regression model built using 
regress 
This is my model:
clc; clear; close all;
load('pred_zeros')
D = [Zero L_mean R_mean];
D(any(isnan(D), 2), :) = []; %remove NaN from matrix D
%linear regression 
X  =[ones(size(D(:,1),1),1),D(:,1),D(:,2)];
b  = regress(D(:,3), X);
Rmean_regr = b(1) + D(:,1)*b(2) + D(:,2)*b(3);
[~,~,~,~,stats] = regress(D(:,3), X); %model statistic
I only generate model statistics using stats. How should i do?
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Accepted Answer
  Jeff Miller
      
 on 8 Sep 2019
        Elisa, I think this might do what you want:
%linear regression 
d1 = D(:,1);
d2 = D(:,2);
d3 = D(:,3);
t = table(d1,d2,d3);
mdl12 = fitlm(t,'d3~d1+d2');
a = anova(mdl12)
More Answers (1)
  Jeff Miller
      
 on 7 Sep 2019
        It's a little difficult to say because "perform ANOVA" can mean several different things with regression models.
Usually the best approach is to make comparisons among models, where you fit several different regression models and compare their SSerror's.  MATLAB's 'stepwisefit' does that, so you might have a look and see whether that will answer the specific question(s) that you have.
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