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Lecture 13 – More on Matched Models

Lecture 13 – More on Matched Models. Outline Interactions with the matching variables Additive models Diagnostics Efficiency. Leisure world data. Neither ignoring the matching nor fitting individual α j for each matched set is a good idea.

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Lecture 13 – More on Matched Models

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  1. Lecture 13 – More on Matched Models • Outline • Interactions with the matching variables • Additive models • Diagnostics • Efficiency BIOST 536 Lecture 13

  2. Leisure world data • Neither ignoring the matching nor fitting individual αj for each matched set is a good idea BIOST 536 Lecture 13

  3. Effect modification by the matching or stratifying variables BIOST 536 Lecture 13

  4. Interactions with the matching variables BIOST 536 Lecture 13

  5. Interactions with the matching variables BIOST 536 Lecture 13

  6. Additive models BIOST 536 Lecture 13

  7. Additive models • As is often the case, the interaction term allows OR ( A=1 & B=1) < OR(A=1) x OR(B=1) • Suggests an additive model without interaction might be as good • Stata cannot fit the additive model without writing a special routine; some specialized packages (Egret; Epicure) can do these model fits BIOST 536 Lecture 13

  8. Additive models • Additive models can be attractive scientifically, but in practice are difficult to fit and have poor statistical properties BIOST 536 Lecture 13

  9. Diagnostics BIOST 536 Lecture 13

  10. Diagnostics BIOST 536 Lecture 13

  11. Efficiency BIOST 536 Lecture 13

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