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How to group data for MANOVA1 analysis

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Makunda Aryal
Makunda Aryal 2021 年 9 月 20 日
回答済み: Jeff Miller 2021 年 9 月 21 日
I have the data whose dimension is 84*84. Here 84 is the observation from 3 different groups (each group has 28 that is first 28 rows 1st group , 2nd 28 rows is 2nd group and so on). I would like to perform the MANOVA1 in attached data ( the attached data has 85*84 and first row was added just for grouping so in the last part of code X = table2array(t2(:,2:85)); I used from 2 to 85). I used the following code but when I run I got the error "The within-group sum of squares and cross products matrix
is singular." can anybody help me on this why I got that error and how to solve? or is there another way I can do the MANOVA1 on this data set?
t10 = load("Manova1Data.txt");
t = t10';
t2 = array2table(t);
t2.Group = repmat({'Group?'},height(t2),1);
GroupA = t2.t1>=1 & t2.t1<=28;
t2.Group(GroupA) = repmat({'GroupA'},sum(GroupA),1);
GroupB = t2.t1>=29 & t2.t1<=56;
t2.Group(GroupB) = repmat({'GroupB'},sum(GroupB),1);
GroupC = t2.t1>=57 & t2.t1<=84;
t2.Group(GroupC) = repmat({'GroupC'},sum(GroupC),1);
X = table2array(t2(:,2:85));
[d,p,statsTrain] = manova1(X,t2.Group);

回答 (1 件)

Jeff Miller
Jeff Miller 2021 年 9 月 21 日
84*84 is not going to work, sorry. For MANOVA, you need to have more cases in each group than the number of variables. Some possible alternatives:
  • Select out different subsets of the variables for different MANOVAs.
  • Use principal components analysis to reduce the number of variables by summarizing the 84 into a much smaller number of "components" that represent the variables almost as well. (This could be very helpful if there are reasonable correlations among variables within certain subsets of the 84.)

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