1 / 8

Applied biostatistics

Applied biostatistics. Francisco Javier Barón López Dpto. Medicina Preventiva Universidad de Málaga – España baron@uma.es. Multivariate analysis. Generally used to study: the effect of one variable Numerical dichotomous, or qualitative by using multiple binary variables.

delling-ull
Download Presentation

Applied biostatistics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Applied biostatistics Francisco Javier Barón López Dpto. Medicina Preventiva Universidad de Málaga – España baron@uma.es

  2. Multivariate analysis • Generally used to study: • the effect of one variable • Numerical • dichotomous, or • qualitative by using multiple binary variables. • On another variable • Numerical: Multiple linear regression • Binary: Logistic regression • Controlling for the effect of a few other variables • Control variables • Covariates • Confusion

  3. The usual multivariate model in Health sciences Interesting variable Multivariate model Outcome age Covariates sex … Does [interesting variable] influence [Outcome variable] when [adjusting/controlling/taking into account] covariates1, covariates2,…?

  4. Numerical outcome: Multiple linear regression Interesting variable Multivariate model: Linear regression model Estimate±std.error; p Estimate; CI 95%; p Numericoutcome age Covariates sex • Estimate>0, Increasing effect • Estimate<0, Decreasing effect • Estimate=0, No effect … We are NOT (very) interested in the significance of covariates.

  5. Binary logistic regression Interesting variable Multivariate model: Linear regression model OR; p OR; CI 95%; p Binaryoutcome 0/1 age Covariates sex … • OR>1, Increased risk • OR<1, Decreased risk • OR=1, No effect The estimates now are: Odds Ratios (OR)

  6. Dummy variables Qualitative interesting variable with 3+ levels Multivariate model Outcome age Covariates sex … We must encode the qualitatives non binary variables using only binary variables. How?

  7. Encoding dummy variables Categoria laboral Administativo dummySeguridad=0 dummyDirectivo=0 Seguridad: dummySeguridad=1 dummyDirectivo=0 Directivo: dummySeguridad=0 dummyDirectivo=1

  8. Dummy variables Qualitative interesting variable with 3+ levels Multivariate model Outcome Dummy 1 Multivariate model Dummy 2 Covariates … Outcome Covariates … … Coding qualitative variables using dummy variables

More Related