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**RE: 2x3 Mixed Design ANOVA**Oct 15, 2018 05:10 AM | Andrew Zalesky

RE: 2x3 Mixed Design ANOVA

Hi Ana,

this is not quite what I had in mind. I don't think that your proposed design matrix will work.

I was thinking of the following design matrix:

1 1

1 2

1 4

1 1

1 2

1 4

1 1

1 2

1 4

1 1

1 2

1 4

I have not included the within subjects effects. Need to include another 4 columns to model these effects, as you have done below.

Contrast is [0 1 0 0 0 0] to test for t1 < t2 < t3 and [0 -1 0 0 0 0] to test for t1> t2> t3.

Select "t-test"

The assumption here is that the increase in connectivity between t2 and t3 is exactly twice that of the increase between t1 and t2. Need to assess whether this assumption is realistic.

Note that there are more sophisticated tests to assess parametric increases with time, although they cannot be coded in terms of a GLM.

Andrew

this is not quite what I had in mind. I don't think that your proposed design matrix will work.

I was thinking of the following design matrix:

1 1

1 2

1 4

1 1

1 2

1 4

1 1

1 2

1 4

1 1

1 2

1 4

I have not included the within subjects effects. Need to include another 4 columns to model these effects, as you have done below.

Contrast is [0 1 0 0 0 0] to test for t1 < t2 < t3 and [0 -1 0 0 0 0] to test for t1> t2> t3.

Select "t-test"

The assumption here is that the increase in connectivity between t2 and t3 is exactly twice that of the increase between t1 and t2. Need to assess whether this assumption is realistic.

Note that there are more sophisticated tests to assess parametric increases with time, although they cannot be coded in terms of a GLM.

Andrew

*Originally posted by Ana Coelho:*Once again, thank you for your answer Dr.
Zalesky!

Just to clarify some things if I want to evaluate the linear increase: time1 < time2 < time3 and also taking into account that we have 2 groups (good performers vs. poor performers) then my design matrix for an example with 4 subjects will be something like this:

1 1 0 0 0 0 0 1 0 0 0

1 0 2 0 0 0 0 1 0 0 0

1 0 0 4 0 0 0 1 0 0 0

1 1 0 0 0 0 0 0 1 0 0

1 0 2 0 0 0 0 0 1 0 0

1 0 0 4 0 0 0 0 1 0 0

1 0 0 0 1 0 0 0 0 1 0

1 0 0 0 0 2 0 0 0 1 0

1 0 0 0 0 0 4 0 0 1 0

1 0 0 0 1 0 0 0 0 0 1

1 0 0 0 0 2 0 0 0 0 1

1 0 0 0 0 0 4 0 0 0 1

where columns 2 to 4 model time for group1 and columns 5 to 7 model time for group2. The last 4 columns model each subject.

The contrast for linear increase in the group 1 will be: [0 -1 0 1 0 ...] Is this contrast correct? Because you mentioned that contrasts will be [0 1 0 0...] for t1 > t2 > t3 and [0 -1 0 0...] for t1 < t2 < t3, but I don't get it how this reflects the linear increase.

Thanks in advance!

Best regards,

Ana

Just to clarify some things if I want to evaluate the linear increase: time1 < time2 < time3 and also taking into account that we have 2 groups (good performers vs. poor performers) then my design matrix for an example with 4 subjects will be something like this:

1 1 0 0 0 0 0 1 0 0 0

1 0 2 0 0 0 0 1 0 0 0

1 0 0 4 0 0 0 1 0 0 0

1 1 0 0 0 0 0 0 1 0 0

1 0 2 0 0 0 0 0 1 0 0

1 0 0 4 0 0 0 0 1 0 0

1 0 0 0 1 0 0 0 0 1 0

1 0 0 0 0 2 0 0 0 1 0

1 0 0 0 0 0 4 0 0 1 0

1 0 0 0 1 0 0 0 0 0 1

1 0 0 0 0 2 0 0 0 0 1

1 0 0 0 0 0 4 0 0 0 1

where columns 2 to 4 model time for group1 and columns 5 to 7 model time for group2. The last 4 columns model each subject.

The contrast for linear increase in the group 1 will be: [0 -1 0 1 0 ...] Is this contrast correct? Because you mentioned that contrasts will be [0 1 0 0...] for t1 > t2 > t3 and [0 -1 0 0...] for t1 < t2 < t3, but I don't get it how this reflects the linear increase.

Thanks in advance!

Best regards,

Ana

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Title | Author | Date |
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Ana Coelho |
Oct 10, 2018 | |

Andrew Zalesky |
Oct 10, 2018 | |

Ana Coelho |
Oct 11, 2018 | |

Andrew Zalesky |
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Ana Coelho |
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Andrew Zalesky |
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Ana Coelho |
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Andrew Zalesky |
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Ana Coelho |
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Andrew Zalesky |
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Ana Coelho |
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Ana Coelho |
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Ana Coelho |
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Ana Coelho |
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Andrew Zalesky |
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Andrew Zalesky |
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Andrew Zalesky |
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