Overcoming the simplification strategy
Analyzing binary or continuous data usually doesn’t cause any headaches for statisticians. But when we step into ordinal data, most of us ignore their specific nature and either dichotomize them or analyze them as if they are continuous.
Recently, these problems have become much more prevalent due to the nature of composite endpoints (watch out for an interesting episode on this in a few weeks).
Now Benjamin and I have worked on better tools to analyze such data already at the university. We’ll dig back into what we learned then and what is still relevant today.
Specifically, we’ll cover the following questions:
- What are ordinal data?
- How do we commonly analyze ordinal data and what’s wrong with these approaches?
- What are better ways to analyze ordinal data?
- How can we present ordinal data best using graphics?
References:
A New Nonparametric Approach for Baseline Covariate Adjustment for Two‐Group Comparative Studies
Van Elteren test for nonparametric two-way analysis
Find many more references for non-parametric approaches here!
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