External Email - Use Caution Hello VIttal,
thanks for the info about the design. You wrote before that the Matlab variable X (i.e., the design matrix) has a dimension of 47x6. X is a translation of the study design into a numerical matrix, which is part of the statistical model. In your case, I assume that he first column is a vector of ones (i.e. the intercept/constant of the statistical model), and that the other columns reflect the numerical data in the table that you sent, in the same order. Correct me if I am wrong. Now, the contrast "matrix“ specifies the questions that you want to ask to the data, i.e. the effect of a certain variable (or sometimes combinations of variables) onto the outcome variable Y. I put "matrix" in quotes, because in many cases a simple vector is sufficient; contrasts need not necessarily be specified as a matrix, and contrasts specified as a matrix are typically more complex than those specified by a vector. In any case, the contrast vector/matrix needs to have as many elements/columns as there are columns in X, because the elements/columns oft the contrast vector/matrix will be matched with (and therefore need to correspond to) the columns of X. I.e. the nth element/column in your contrast vector/matrix refers to the nth predictor variable in the statistical model, i.e. the nth column of X. There are 6 columns in X in your case. The entries in the contrast vector/matrix represent weights that you assign to each variable in order to test for its effect. One often (but not always or necessarily) uses +1 to test for a positive relation of the chosen variable on Y, -1 for a negative effect, and zero for not considering a variable for a given contrast. Therefore, the simplest contrast is a vector with a single non-zero entry, and this already allows for the testing of effects. In other cases, contrasts can have more than one non-zero entry, or can be formulated as a matrix, but we don’t need this at the moment. The major issue with your design in its current form is that you will not be able to distinguish effects of time from effects of treatment, due to the absence of a control group. This precludes, as far as I can see, a clear interpretation of any changes in Y that you might observe. If you still want to go ahead and test the time/treatment effect, just set the corresponding element of the contrast vector to +1 or -1. Best, Kersten Am 30.11.2020 um 12:44 schrieb vittal korann <vittalkor...@gmail.com<mailto:vittalkor...@gmail.com>>: Hello FS experts Thank you for your kind response. This is regarding my previous mail. I think we need to talk about the design matrix X first (sorry, I did not look at your xlsx file; I think it's probably better to send simple csv files if at all). I attached longitudinal data in csv format. Besides the covariates that you mention, the matrix needs to contain an intercept, a variable for ?time?, a variable for ?group? (assuming you have a control group also), and a group-by-time interaction term in order to asses differential change over time (again, if you have a control group). I do not have a control group. Right now I have only schizophrenia patients who underwent 2 scans: the first is the baseline and the second one is after 3 months of yoga therapy. Wish to know how can I proceed with my available data. Just to make sure: ?age? should be ?age at baseline? (i.e. constant across time per subject), otherwise, it will be confounded with time. Yes, I used the same across the study. Could you review (and possibly adapt) your design matrix X with respect to which columns it contains, and write it in the reply? I tried but couldn't get there. Looking forward to your response. Thanks, Vittal <longitudinal_data.csv> -- Kersten Diers Image Analysis Group (AG Reuter) German Center for Neurodegenerative Diseases (DZNE) B.1.114 | Building 99 | Venusberg-Campus 1 | 53127 Bonn | Germany https://secure-web.cisco.com/1-2DMCqsEAxXMrF8CjX08W54lPnfE5EsDPiGxF4zYoYh78iwWTCiH2R9fR1qkjryQdeo9WyU4jf6QC0vdHLHc6PUeRu90ms-mEJnCueSGHvgg8h1SYT4nyn8Ybo4z8oWPSjEvhdNYadIybyuDDMQ45UF8R7ihI1J_UphS-RSofNA-kmLj70XvA_wYZcFGTdVNeYKfGof40gjNcfE53MNCKKj8UE4kK1AHVuvBmara9eRtXLb5m76hw2SNqErQTohjFGmUfD28xkPzQxRhw5429g/https%3A%2F%2Fwww.dzne.de%2Fen%2Fsites%2Fbonn%2Fresearch-groups%2Freuter.html Phone: +49 / 228 / 43302 - 381
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