www.gusucode.com > stats 源码程序 matlab案例代码 > stats/HypothesisTestforFixedEffectsCoefficientsExample.m
%% Hypothesis Tests for Fixed-Effects Coefficients %% % Load the sample data. load(fullfile(matlabroot,'examples','stats','weight.mat')) %% % |weight| contains data from a longitudinal study, where 20 subjects are % randomly assigned to 4 exercise programs, and their weight loss is recorded % over six 2-week time periods. This is simulated data. %% % Store the data in a table. Define |Subject| and |Program| as categorical % variables. tbl = table(InitialWeight,Program,Subject,Week,y); tbl.Subject = nominal(tbl.Subject); tbl.Program = nominal(tbl.Program); %% % Fit a linear mixed-effects model where the initial weight, type of program, % week, and the interaction between the week and type of program are the % fixed effects. The intercept and week vary by subject. lme = fitlme(tbl,'y ~ InitialWeight + Program*Week + (Week|Subject)') %% % Test for the significance of the interaction between |Program| and |Week|. H = [0 0 0 0 0 0 1 0 0; 0 0 0 0 0 0 0 1 0; 0 0 0 0 0 0 0 0 1]; pVal = coefTest(lme,H) %% % The high $p$-value indicates that the interaction between |Program| and % |Week| is not statistically significant. %% % Now, test whether all coefficients involving |Program| are 0. H = [0 0 1 0 0 0 0 0 0; 0 0 0 1 0 0 0 0 0; 0 0 0 0 1 0 0 0 0; 0 0 0 0 0 0 1 0 0; 0 0 0 0 0 0 0 1 0; 0 0 0 0 0 0 0 0 1]; C = [0;0;0;0;0;0]; pVal = coefTest(lme,H,C) %% % The $p$-value of 0.0274 indicates that not all coefficients involving % |Program| are zero.