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2 weeks ago
(252 views)

JMP Pro 13 allows assigning up to two Subject terms for the Exchangeable Structure of the Repeated Structure tab in the Mixed Model dialog. Can anyone give me an __example__ where two subject terms would be appropriate or preferred for repeated measures longitudinal regression? In particular, I'm wondering whether I could use ID and Eye as Subject terms for the partial dataset listed below (where Eye is nested within ID) and Year_Cat as the repeated term. Or should I use only ID as the Subject term and concatenate "Eye" and "Year_Cat" as the Repeated term? Thanks in advance.

ID | EYE (right=1, left=2) | YEAR_CAT |

589 | 1 | 0 |

589 | 1 | 1 |

589 | 1 | 2 |

589 | 1 | 3 |

589 | 1 | 4 |

589 | 2 | 0 |

589 | 2 | 1 |

589 | 2 | 2 |

589 | 2 | 3 |

589 | 2 | 4 |

670 | 1 | 0 |

670 | 1 | 1 |

670 | 1 | 2 |

670 | 1 | 3 |

670 | 1 | 4 |

670 | 1 | 5 |

670 | 1 | 6 |

670 | 2 | 0 |

670 | 2 | 1 |

670 | 2 | 2 |

670 | 2 | 3 |

670 | 2 | 4 |

670 | 2 | 5 |

670 | 2 | 6 |

5 REPLIES

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2 weeks ago
(212 views)

As an example, in measuring the effects on achievement scores of students where students are nested within schools, two subject terms--school and students within a school--would be appropriate.

In your case you can specify the random subject effects as shown below and leave the default Residual for Repeated Structure:

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2 weeks ago
(207 views)

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2 weeks ago
(202 views)

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2 weeks ago
(148 views)

Each ID has data from two eyes (or only one eye if data from the other eye are missing). And each eye of a given ID has multiple time points. For example, ID 1 might have right eye — year 0, year 1, year 3, and year 5 — and left eye — year 0, year 1, year 3, and year 5.

So which of your two options would be preferable for me?

Thanks,

Michael

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2 weeks ago
(127 views)