www.gusucode.com > stats 源码程序 matlab案例代码 > stats/TestFixedEffectsCoefficientsforCategoricalDataExample.m
%% Test Fixed-Effects Coefficients for Categorical Data %% % Load the sample data. load(fullfile(matlabroot,'examples','stats','shift.mat')) %% % The data shows the absolute deviations from the target quality characteristic % measured from the products that five operators manufacture during three % different shifts: morning, evening, and night. This is a randomized block % design, where the operators are the blocks. The experiment is designed % to study the impact of the time of shift on the performance. The performance % measure is the absolute deviation of the quality characteristics from % the target value. This is simulated data. %% % |Shift| and |Operator| are nominal variables. shift.Shift = nominal(shift.Shift); shift.Operator = nominal(shift.Operator); %% % Fit a linear mixed-effects model with a random intercept grouped by operator % to assess if there is significant difference in the performance according % to the time of the shift. lme = fitlme(shift,'QCDev ~ Shift + (1|Operator)') %% % Test if all fixed-effects coefficients except for the intercept are 0. pVal = coefTest(lme) %% % The small $p$-value indicates that not all fixed-effects coefficients are 0. %% % Test the significance of the |Shift| term using a contrast matrix. H = [0 1 0; 0 0 1]; pVal = coefTest(lme,H) %% % Test the significance of the |Shift| term using the |anova| method. anova(lme) %% % The $p$-value for |Shift|, 0.00075956, is the same as the $p$-value of % the previous hypothesis test. %% % Test if there is any difference between the evening and morning shifts. pVal = coefTest(lme,[0 1 -1]) %% % This small $p$-value indicates that the performance of the operators are % not the same in the morning and the evening shifts.