Bayesian methods in health economics Florence June 2019 FEEDBACK FORM
Please give scores and comments on the lecture and practical sessions to help us improve the course for the future.
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1. How do you assess the quality of the lectures from 1 (very poor) to 10 (excellent)
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Very poor
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Excellent
1b. Comments
Your answer
2. How do assess the quality of the practicals from 1 (very poor) to 10 (excellent)
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Very poor
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10
Excellent
2b. Comments
Your answer
3. What lecture(s) did you think were the most useful (NB: Stupid Google Forms doesn't let you unclick an answer, so please think carefully before you click...)
Please select all that are relevant
Lecture 1. Introduction to Bayesian inference
Lecture 2. Introduction to MCMC in BUGS
Lecture 3. Introduction to health economic evaluations
Lecture 4. Cost and cost-utility data
Lecture 5. Aggregated-level data and hierchical models
Lecture 6. Evidence synthesis and network meta-analysis
Lecture 7. Model error and structural uncertainty
Lecture 8. Markov models
Lecture 9. Survival analysis
Lecture 10. Missing data in cost-effectiveness modelling
Lecture 11. Introduction to the value of information
Lecture 12. Expected value of partial information (1)
Lecture 13. Expected value of partial information (2)
Lecture 14. Expected value of partial information (3)
Lecture 15. Expected value of sample information (1)
Lecture 16. Expected value of sample information (2)
Lecture 17. Expected value of sample information (3)
Please select all that are relevant
Lecture 1. Introduction to Bayesian inference
Lecture 2. Introduction to MCMC in BUGS
Lecture 3. Introduction to health economic evaluations
Lecture 4. Cost and cost-utility data
Lecture 5. Aggregated-level data and hierchical models
Lecture 6. Evidence synthesis and network meta-analysis
Lecture 7. Model error and structural uncertainty
Lecture 8. Markov models
Lecture 9. Survival analysis
Lecture 10. Missing data in cost-effectiveness modelling
Lecture 11. Introduction to the value of information
Lecture 12. Expected value of partial information (1)
Lecture 13. Expected value of partial information (2)
Lecture 14. Expected value of partial information (3)
Lecture 15. Expected value of sample information (1)
Lecture 16. Expected value of sample information (2)
Lecture 17. Expected value of sample information (3)
3b. Comments (you can elaborate on your answer to question 3 here)
Your answer
4. Was the material useful?
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Not useful at all
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5
Extremely useful
5. Did you feel you were prepared for the level of complexity of the lecture?
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Not very prepared at all
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5
Very prepared
6. What additional material would have like to receive?
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Your answer
7. Do you think you will use any of the concepts/methods/tools taught at the course in your applied work?
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Definitely - I will modify my workflow to include some or all of these
May be - I will try and use these and convince my boss/colleagues of their usefulness
Probably not - they are too complicated
Definitely not - I don't think they were useful at all
7b. Comments
Your answer
8. Do you think the period of the year in which the summer school was held was good?
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Not so much
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5
Excellent
8b. Comments (you can elaborate on your answer to question 8 here)
Your answer
9. Do you think the location of the course was good?
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Very poor
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Excellent
9b. Comments (you can elaborate on your answer to question 9)
Your answer
10. What did you think about the lecturers?
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Knowledgeable
Friendly
Helpful
Gianluca Baio
Chris Jackson
Anna Heath
Howard Thom
Knowledgeable
Friendly
Helpful
Gianluca Baio
Chris Jackson
Anna Heath
Howard Thom
10b. Comments (you can elaborate on your answers to question 10 here)
Your answer
11. Did you find the GitHub repository helpful
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Not very helpful at all
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5
Extremely helpful
11b. Comments (you can elaborate on your answer to question 11 here)
Your answer
Any other feedback
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