Multiple Linear Regression, Logistic Regression and Survival Analysis

COURSE CO-ORDINATOR

Dr.L.Jeyaseelan

Professor

This course is intended to improve participant’s ability to conduct regression analyses and study the relationship between response variable and multiple predictor variables. This course is also intended to sharpen the skills of analyzing binary outcome data and interpreting regression coefficients.

This course is targeted towards epidemiologist, biostatisticians, Demographers and other medical researchers.

WHY SHOULD SOMEONE ATTEND?

The primary bio-statistical tools in modern medical research are single-outcome, multiple-predictor methods: multiple linear regressions for continuous outcomes, logistic regression for binary outcomes, and the Cox proportional hazards model for time-to-event outcomes. Applying these methods and interpreting the results requires some introduction. However, introductory statistics courses have no time to spend on such topics. And therefore often neglected or misused by the researchers. The Logistics regression and Survival analyses modules are time tested and the concepts of Cox Proportional hazard model is made simple and understandable. The diagnostics to study whether the model fits the data will also be imparted through good and bad examples.

COURSE CONTENT

Regression analysis

  • Introduction to Regression
  • Simple linear regression
  • Assumptions
  • Tests of slope and intercept
  • Multiple linear regression
  • Model building strategy
  • Assessing Best Fit
  • Multicollinearity Problem and Diagnostics

Logistic Regression

  • Introduction to Logistic Regression, Rationale
  • Single and Multiple Logistic Regressions
  • Creating dummy variables
  • Model building
  • Assessing best fit
  • Diagnostics
  • Matched data analysis
  • Ordinal response logistic regression

Survival Analysis

  • Introduction to Survival Analysis
  • Kaplan Meier Survival Analysis
  • Comparison of two survival curves
  • Cox Proportional Hazards Model
  • Proportional Hazards assumption (Graphical approach and Goodness of fit)

Statistical Software:

  • SPSS and STATA (Analyses)

Course Fee : Rs 10,000/- (Inclusive of 18% GST)

Accomodation:

Participants will have to bear their own expenses for travel, boarding and lodging. The Organizers will provode Course Kit, Lunch and Snacks. However, the organizers may arrange basic accommodation with A/C facility in the college campus on request. Only limited accommodation is available in the campus and priority will be given to female participants.

Course fee shuld be paid in full by August 23, 2019.

Payment can be made by Demand Draft in favour of “Christian Medical College Vellore Association Account” payable at Vellore.

HOW TO APPLY?

Please use the “Application Format” for registration to be sent along with the required demand draft.

For brochure and registration form, click here

Address for communication

Mr.M.Mafhan Kumar / Mr. Sasikumar

Clinical Epidemiology Unit

Christian Medical College, Vellore

Pincode 632004

Email: ceu@cmcvellore.ac.in

Pnone : (0416) 2282329, 2282759