How to create a slide presentation comparing different statistical approaches?

 As a statistical researcher, creating a clear, credible, and compelling slide presentation comparing different statistical approaches is a skill often required for seminars, cross-functional meetings, or regulatory communication. Below is a structured procedure—tailored for researchers—that balances scientific rigor with visual communication best practices.

---

✅ Step-by-Step Procedure: Comparing Statistical Approaches in a Slide Deck

1. Define the Objective & Audience

Before you build slides, clarify:

Element	Examples
Goal	Compare methods for robustness, efficiency, interpretability
Audience	Statisticians, clinicians, regulatory reviewers, PMs
Context	Internal method selection? Publication? Regulatory defense?
Scope	Exploratory vs. confirmatory? Frequentist vs. Bayesian?

Tip: If audience is non-statistical, focus more on implications, not math.

---

2. Select the Methods to Compare

Choose 2–4 methods based on relevance, e.g.:

• ANCOVA vs MMRM vs Mixed Models with Imputation

• Logistic regression vs Random Forest

• Parametric survival vs Cox vs RMST

• OLS-based Global Test vs Wei-Lachin vs O'Brien Rank Sum

You can compare:

Dimension	Examples
Assumptions	Normality, missingness, linearity
Statistical Properties	Bias, efficiency, type I error, power
Interpretability	Clinician-friendly estimates, causal links
Computational Cost	Time, software compatibility
Regulatory Acceptance	FDA/EMA precedent

---

3. Develop a Comparison Framework Table

Create a matrix that summarizes pros and cons:

Feature	Method A	Method B	Method C
Assumptions	Linear, MCAR	Flexible, MAR	Non-parametric
Handles Missing Data	No	Yes (via MMRM)	Yes (permutation)
Interpretability	High	Medium	Low
Type I Error Control	Good	Conservative	Conservative
Widely Accepted by FDA	✅	✅	⚠️ Rarely used

---

4. Visualize Performance (if simulated or real)

Show comparisons on real or simulated data:

• Line plots or bar charts of bias, MSE, power

• Boxplots of estimates across repetitions

• Time-to-event curves from different methods

• Permutation p-values vs parametric p-values

Use consistent colors and annotate key differences clearly.

---

5. Slide Structure Template

Slide #	Content
1	Title + Objective ("Comparison of Global Test Approaches")
2	Background & Why the Comparison Matters
3	Methods Overview (bulleted list or flowchart)
4	Key Assumptions of Each Method (table)
5	Pros/Cons Table
6	Simulation or Real-World Performance Results
7	Interpretation & Implications (which method is best when)
8	Conclusion & Recommendation
9	Backup: Math Formulas, Simulation Setup, References

---

6. Design Principles

• Use 1 concept per slide

• Use visuals > text (tables, plots, icons)

• Include plain-English captions under figures

• Keep font ≥ 18pt for all content

• Highlight preferred method using icons or color (e.g., ✅ 🔍 ⚠️)

---

7. Recommendations & Takeaways

End with a summary slide that includes:

✅ When to use Method A
⚠️ When to avoid Method B
🔍 Method C as sensitivity or exploratory option

---

8. Optional Enhancements

• Add animations to reveal comparisons step-by-step

• Use color coding: blue (assumptions), green (strengths), red (weaknesses)

• Include clinical or business context, if cross-functional

---

📦 Deliverables Template

If you’d like, I can generate:

• A PowerPoint shell for you to populate

• A table shell in Markdown or Excel

• SAS/R simulation code to compare the methods empirically

• A slide-ready figure comparing p-values or estimates

A simple example structure for internal team use:

• Slide 1: Overview of the key steps involved in each statistical approach

• Slide 2: Summary of p-values or key results based on real-world data using each method

• Slide 3–4 (optional): Detailed comparison of SAS outputs and the corresponding code used for each approach

• Slide 5: Pros and cons of each method presented in a clear comparison table