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Advanced Statistical Methods for Health Research (IBM SPSS)

Instructors
Mr Alphonse McDonald
Duration
2 Days
Course Level
LearnQuest / IBM Certified
Requirements
A good working knowledge of IBM SPSS Statistics Base and inferential statistics is required prior to attending this course. Attendance on the Statistical Methods for Healthcare Research course is strongly recommended.

The first part of the course focuses on the Analysis of Variance (ANOVA) techniques which allow you to test whether the means of several populations are the same. You will develop an understanding of when to apply the techniques, how to apply them and how to interpret the results. The second part of the course will build upon your knowledge of linear regression and will introduce you to logistic regression. We will include categorical predictors in regression models via dummy variables, discuss variable selection methods, model building philosophies and learn how to run and interpret logistic regression in IBM SPSS Statistics.

Course suitable for:

Healthcare professionals who want to identify significant differences between two or more groups and who want to analyze binary outcome data using logistic regression methods.

 

Candidates should have:

A good working knowledge of IBM SPSS Statistics Base and inferential statistics is required prior to attending this course. Attendance on the Statistical Methods for Healthcare Research course is strongly recommended.

Topics covered include:

  1. Logic of testing for mean differences
  2. Comparing two groups: review of t-test
  3. Comparing more than two groups: ANOVA
  4. Examining the data
  5. Hypothesis testing and assumptions
  6. One-way Analysis of Variance (ANOVA)
  7. Multi-way univariate ANOVA
  8. Multi-way multivariate ANOVA (MANOVA)
  9. Nonparametric (distribution free) alternatives
  10. Post hoc testing and planned comparisons
  11. Graphing the results
  12. Review of multiple linear regression
  13. Influential points and multicollinearity
  14. Including categorical predictors in regression models via dummy variables
  15. Running logistic regression in IBM SPSS Statistics
  16. ROC curves
  17. Interpreting logistic regression output
  18. Repeated measures ANOVA

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