ETHER Senior Resident Stats Talk 29 Jan 2016
•Télécharger en tant que PPTX, PDF•
0 j'aime•279 vues
Talk on Statistics for Anaesthesia Senior Residents as part of National Training programme.
Recommandé
Contenu connexe
Similaire à ETHER Senior Resident Stats Talk 29 Jan 2016
Similaire à ETHER Senior Resident Stats Talk 29 Jan 2016 (20)
Plus de Hon Liang
Plus de Hon Liang (15)
Dernier
Dernier (20)
ETHER Senior Resident Stats Talk 29 Jan 2016
- 1. ETHER 29 Jan 2016
- 4. I hate stats
- 6. Medutainment
- 14. But is the Truth true?
- 15. An Example
- 21. Why not ask bus drivers instead?
- 24. Type of Paper Intervention Drug Trial RCT Observational Case report Case series Case control Cohort Meta-analysis Systematic Review
- 25. Type of Paper Intervention Drug Trial RCT Observational Case report Case series Case control Cohort Meta-analysis Systematic Review
- 26. What is the question? Why this question? How to answer this question? Inclusion / Exclusion Methodology Actual stats calculation Conclusions and relevance RCT - Intervention
- 28. Interim analysis No control group. Significant conflict of interest COD: Fudgy terminology Small numbers
- 33. Define a “good” journal
- 35. Industry sponsored trial BMJ 7% NEJM 32% Citations Industry sponsored > other source of funding Reduction in Impact Factor 1% 15% Reprints Oct 2010
- 36. Nov 2009
- 37. May 2015
- 38. …half baked … …tendentious … …ill advised …
- 42. What to make of negative studies?
- 43. riskofdeath untreated risk of death reductionofriskofdeath untreated risk of death reductionofriskofdeath untreated risk of death A B C reductionofriskofdeath untreated risk of death adverse effects riskofdeath untreated risk of death treatmentriskofdeath untreated risk of death no treatment A B C
- 45. Why ask this question? How to answer this question? Is meta-analysis the right method to answer this question? Meta-analysis
- 46. What’s the result? How do we know the results valid? Meta-analysis G.I.G.O Garbage data Garbage result Garbage analysis
- 47. Where How Quality Data Reproducible Robust Meta-analysis How do we know the results valid? Search databases / terms Independent extraction Predefined data form Agreeing how to disagree
- 48. Meta-analysis How do we know the results valid? Publication bias Funnel Plot Data Reproducible Robust Problem of negative studies
- 49. “Perfect” data Garbage result Garbage analysis Observation vs intervention Heterogeneity Random vs fixed effect Sensitivity Analysis Meta-analysis
- 50. Meta-analysis Heterogeneity - I2 Lower = less heterogeneity Higher = more heterogeneity describes the percentage of variation across studies that is due to heterogeneity rather than chance
- 51. Meta-analysis Random vs Fixed Effect One true effect size shared by all the studies True effect vary so each study estimates a different effect size (when significant heterogeneity exist)
- 52. Sensitivity Analysis Meta-analysis Performing analysis with different assumptions to see if result remains the same
- 53. How to apply the results? “Perfect” data Result “Perfect” analysis Meta-analysis
- 54. Take home messages Medutainment is real and here to stay. Paper critique is about logic. If you are worried about Exit Paper critique, you are probably suffer from imposter syndrome.