How perform anova tests after using regress in MATLAB?
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EM geo
el 7 de Sept. de 2019
Comentada: EM geo
el 9 de Sept. de 2019
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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Jeff Miller
el 8 de Sept. de 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)
Más respuestas (1)
Jeff Miller
el 7 de Sept. de 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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