Advanced Concepts for Applied Statistics in Healthcare

In this section, the following topics are included:

Calculating Sample Size and power under different Scenarios

Learner Outcomes

  • Describe the importance in establishing a sample to represent the population
  • Identify the difference between probabilistic and non-probabilistic sampling strategies.
  • Compute sample size under different scenarios using SAS code
  • Understand when a given sample size calculation is most appropriate
  • Apply the appropriate sampling strategy to a given research design

Mixed model analysis

Learner Outcomes

Understanding repeated measures designs, split-plot factorial models, nested designs and mixed model anovas that incorporate fixed and random effects

Survival analysis

Learner Outcomes

Type your learning objectives here.

  • First
  • Second


Computer Simulation and Random Number Generation

Learner Outcomes

In this chapter we will create new data sets using computer generated random numbers. In this way we can simulate research outcomes without actually  performing the research.
Some basic rules of the exercise are that we must begin by understanding our variables and the parameters that the variables represent. Min max estimates variance, N
Through computer simulation approaches we can combine logic with combinations and permutations in factorial models to explore wicked problems.




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Applied Statistics in Healthcare Research by William J. Montelpare, Ph.D., Emily Read, Ph.D., Teri McComber, Alyson Mahar, Ph.D., and Krista Ritchie, Ph.D. is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, except where otherwise noted.

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