Hey,

can anyone recommend a test for the following problems.

1) Say I have repeated measurements \(x_1,...,x_n\) and \(y_1,...,y_n\) such that each measurement may depend on the past. How can I test whether the means in both tests are equal, i.e. mean of \(x_1,...,x_n\) equal to mean of \(y_1,...,y_n\) ? I have learned that the t-test is not applicable in this situation since it allows only for dependence between \(x_i\) and \(y_i\) but not for serial dependence as indicated here. Note that I assume \(x_i\) and \(y_i\) to be independent.

2) Same situation as above but in addition let also \(x_i\) and \(y_i\) be dependent. So searial dependence and inter-goup dependence. Again the means of the groups should be compared.

Cheers

Btw: Normality can be assumed but I am also happy for non-parametric alternatives.

can anyone recommend a test for the following problems.

1) Say I have repeated measurements \(x_1,...,x_n\) and \(y_1,...,y_n\) such that each measurement may depend on the past. How can I test whether the means in both tests are equal, i.e. mean of \(x_1,...,x_n\) equal to mean of \(y_1,...,y_n\) ? I have learned that the t-test is not applicable in this situation since it allows only for dependence between \(x_i\) and \(y_i\) but not for serial dependence as indicated here. Note that I assume \(x_i\) and \(y_i\) to be independent.

2) Same situation as above but in addition let also \(x_i\) and \(y_i\) be dependent. So searial dependence and inter-goup dependence. Again the means of the groups should be compared.

Cheers

Btw: Normality can be assumed but I am also happy for non-parametric alternatives.

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