Multivariable analysis a practical guide for clinicians and public health researchers /
"Now in its third edition, this highly successful text has been fully revised and updated with expanded sections on cutting-edge techniques including Poisson regression, negative binomial regression, multinomial logistic regression and proportional odds regression. As before, it focuses on easy...
I tiakina i:
Kaituhi matua: | |
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Kaituhi rangatōpū: | |
Hōputu: | Tāhiko īPukapuka |
Reo: | Ingarihi |
I whakaputaina: |
Cambridge :
Cambridge University Press,
2011.
|
Putanga: | 3rd ed. |
Ngā marau: | |
Urunga tuihono: | An electronic book accessible through the World Wide Web; click to view |
Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|
Rārangi ihirangi:
- 1. Introduction
- 2. Common uses of multivariable
- 3. Outcome variables in multivariable analysis
- 4. Independent variables in multivariable analysis
- 5. Relationship of independent variables to one another
- 6. Setting up a multivariable analysis
- 7. Performing the analysis
- 8. Interpreting the result
- 9. Delving deeper : checking the underlying assumptions of the analysis
- 10. Propensity scores
- 11. Correlated observations
- 12. Validation of models
- 13. Special topics
- 14. Publishing your study
- 15. Summary : steps for constructing a multivariable model.