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Advanced Research Methods Summary 2017/2018

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This summary contains all the elaborations of the lectures, literature, and workgroups per week for the course Advanced Research Methods (ARM). So it is all the material you need to be able to pass your exams. The summary is written by 5 diligent students from academic year 2017/2018. By means of t...

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  • October 2, 2018
  • 61
  • 2017/2018
  • Summary

6  reviews

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By: wietskedewaard • 4 year ago

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By: gamleever • 4 year ago

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By: zmgezondheidswetenschappen • 5 year ago

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By: sophiebierens • 5 year ago

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By: MartinLex • 5 year ago

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The lectures and computer groups are not included

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By: cobylindeboom • 5 year ago

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Hi Martin. We used notes from the workgroups as well as from the PC labs if this was useful. I can send you some answers modules from the workgroups. Just let us know if you benefit from that and where it should go. Hopefully you can read the summary. and pass your exam:) Greetings Coby

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By: MartinLex • 5 year ago

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Hi, Coby, The rest of the summary is certainly useful, just because it was so explicitly in the caption that all the effects were included, I would only have given it 2 stars. That would help very much, could you send it to maartengroot11@gmail.com? Thank you in advance, Maarten

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By: rachidbouafi • 5 year ago

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Advanced Research Methods
Quanttatve and Qualitatve
MSc Health Care Management 2017-2018
Lectures & Workgroups




 Part 1: Epidemiology and quanttatve methods
o Lecture 1, 2 & 3
o Workgroups 1, 2, 3 & PC labs

 Part 2: Qualitatve methods
o Lecture 4 & 5
o Workgroups 4, 5, 6

 Part 3: Organizatonal design studies
o Practice exams




1

,Part 1: Epidemiology and quanttatve methods
Lecture 1 “Causal Inference; drawing lines between causes and efectss

Learning goals for this week:
o To explain the role of causal theories in the design of quantitatite studies
o To apply concepts confounder, confounding, intermediate tariables
o To use directed acyclic graphs (DAG’s) in the design of an analysis
o To be familiar with a number of types of bias

Epidemiology...
- Is not “the science of epidemics”
- “Is the study of the distributon of health-related states and etents in the populationn”
- “Does not represent a body of knowledge (…) It is a philosophy and methodology that can be applied
to a tery broad range of health problemsn The ‘art’ of epidemiology is knowing when and how to
apply the carious strategies creatitely to answer specifc health questionsn”

L’Oréal True Match Minerals leads to a beter skin? “70% less imperfectons in 4 weekss “Our powder covers
like a foundaton and improves the quality of your skin in 1 month!s
- “Improtes” implies a causal efectt
o A leads to B
o Using True Match Minerals leads to a beter skin
Is this contincing?
- Problemst
o Small sample; is this always a problem?
o Study performed or fnanced by commercial company; is this always fatal?
o No control group;
 Essential omission
 What without treatment?
 Potential regression towards the mean
- What do we want to know?
o Not interested in the outcome per se
o Interested in the role of treatment in achieting this outcome
- Conclusiont No meaningful causal conclusion can be drawn from this study

Formal defniton of causaton:
‘In an individual, a treatment has a causal efect if the outcome under treatment 1 would be diferent from the
outcome under treatment 2.’ (Hernan/Robins)
(What would happen to women that use minerals compared to women that don’t)




2

,Potental outcomes




3

, In individual cases, not all potental outcomes are not observed (so you don’t know what would happen to
the skin of women that don’t use the product)




- Counterfactual outcomet potential outcome that is not obserted because the subject did not
experience the treatment (‘counter of the fact’)
- Potential outcome a=1 is factual for some subjects, and counterfactual for othersn

Fundamental problem
- Inditidual causal efect cannot be obserted
o Except under extremely strong (and generally unreasonable) assumptions
- Causal inference as a missing data problem
- We need a diferent defnition of causal efects
- Aterage causal efects can be determined under
o No assumptions (randomised studies)
o Strong assumptions (obsertational studies)

Essental assumptons
Based on population aterages, conclusions on causal efects can be drawn if three assumptions holdt
- Posititity
o Units are assigned to all reletant ‘treatments’
- Consistency
o Treatment is clearly defned
o ‘No causation without manipulation’
What is obesity? By what is obesity caused? And what does that say about the impact on a
patient’s health?
- Exchangeability
o Treatment groups are exchangeable
 It does not mater who gets treatment A and who gets treatment B
o Notationt
 Potential outcomes are independent of the treatment that was actually receited

Meetng the assumptons
- Posititityt control group
- Consistencyt describe treatment with and without L’Oréal
- Exchangeabilityt randomise
Randomised controlled trial (RCT)
- Select patients
- Randomly assign them to treatment groups
- Gold standard

RCT’s vs observatonal studies
- RCT
o Expected exchangeability
o Posititity and consistency inherently assured
o Limited generalisability (external talidity) due to treatment protocol and patient selection
o Practical, ethical considerations
- Obsertational study
o Internal talidity threatened by lack of exchangeability
o Posititity and consistency need explicit atention
o Real world outcomes



4

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