• Order to parcel locker

    Order to parcel locker
  • easy pay

    easy pay
  • Reduced price
Multivariable Analysis: A Practical Guide for Clinicians and Public Health Researchers

Multivariable Analysis: A Practical Guide for Clinicians and Public Health Researchers

9780521760980
623.70 zł
561.33 zł Save 62.37 zł Tax included
Lowest price within 30 days before promotion: 561.33 zł
Quantity
Available in 4-6 weeks

  Delivery policy

Choose Paczkomat Inpost, Orlen Paczka, DPD or Poczta Polska. Click for more details

  Security policy

Pay with a quick bank transfer, payment card or cash on delivery. Click for more details

  Return policy

If you are a consumer, you can return the goods within 14 days. Click for more details

Description
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-to-follow explanations of complicated multivariable techniques. It is the perfect introduction for all clinical researchers. It describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It focuses on the nuts and bolts of performing research, and prepares the reader to set up, perform and interpret multivariable models. Numerous tables, graphs and tips help to demystify the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research.
Product Details
65452
9780521760980
9780521760980

Data sheet

Publication date
2011
Issue number
3
Cover
hard cover
Pages count
250
Dimensions (mm)
194.00 x 252.00
Weight (g)
720
  • Preface; 1. Introduction; 2. Common uses of multivariable models; 3. Outcome variables in multivariable analysis; 4. Type of independent variables in multivariable analysis; 5. Assumptions of multiple linear regression, multiple logistic regression, and proportional hazards analysis; 6. Relationship of independent variables to one another; 7. Setting up a multivariable analysis; 8. Performing the analysis; 9. Interpreting the analysis; 10. Checking the assumptions of the analysis; 11. Propensity scores; 12. Correlated observations; 13. Validation of models; 14. Special topics; 15. Publishing your study; 16. Summary:: steps for constructing a multivariable model; Index.
Comments (0)