Topic 1: Design of Experiments Flashcards

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1
Q

Why is data important?

A

Use data for problem-solving

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2
Q

How many types of data scientist?

A

2: Professional and popular

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3
Q

What is different between professional and popular data scientist?

A

Professional data scientist is able to explore and work on different aspects of data life cycle

Popular data scientist works on dataset from a particular field, data detective

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4
Q

What are challenges with collecting dataset?
How to minimize?

A

Ethics, privacy, errors, missing values
Transparent plan and non-identifible subjects

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5
Q

What is the gold standard to gather data?

A

Randomised controlled trial (RCT)
random double-blinded allocation

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6
Q

What is domain knowledge?

A

Domain knowledge is the context background information needed to analyse and understand the dataset

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7
Q

During the process of gathering information or data, the evidence must be….

A
  • Each piece of evidence needs to be weighed up equally
  • Clear and well-cited
  • Every stage of the study in research journal must be well-documented
  • Journals needs to be reproducible research
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8
Q

What is reproducible research?

A

The author of the study needs to present data set and software used in the study for further verifying and altenative analyses

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9
Q

How many types of controlled experiments are there?

A

2: Contemporaneous (happens at the same time with the treatment grouop)
Historical (happens before the treatment group)

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10
Q

What is placebo?

A

A pretend treatment, designed to be neutral and indistinguishable from the treatment

The participants in double-blinded trial don’t know whether they are receiving the real or placebo treatment

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11
Q

What is placebo effect?

A

A phenomenon in which the subjects/receivers think they are having the treatment and responses to the idea

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12
Q

What is confounding?

A

when the results/effects get mixed up/become misleading because of a 3rd extraneous variable
=> confusing intepretation

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13
Q

What is bias?

A

A factor affecting the ablity of the data to precisely measure the effect of the treatment

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14
Q

What are some confounders with RCT?
Explain each one

A

Selector bias: the 2 groups are not comparable

Observer bias: subjects/ investigators are aware of the identity of the 2 groups/the study ==> affects responses and evaluations + placebo effect

Consent bias: the subjects choose whether to join or not

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15
Q

What is observational study?

A

The investigator does NOT decide or allocate the subjects into groups

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16
Q

What results can be conveyed from observational study?

A

Observational study can only SUGGEST causation using suggestive verbs (link, increase the risks, risk factors,…), NOT PROVE causation

17
Q

What are lurking variables in observational studies?

A

Various misleading hidden confounders
- Selection bias

  • Survivor bias: worst subjects dropout of the study => improvement of the effects
  • Adherers/non-adherers: the pattern can be due to whether the subjects adhere to the treatment/program or not rather than the treatment itself
18
Q

What is a solution to minimize the confounders?

A

Slicing up the groups into subgroups based on the confounders in order to be able to compare the results

19
Q

What is Simpson’s paradox?

A

A phenomenon in which patterns/trends can be observed in individual data sets but will disappear or reverse when combining all groups together.
The percentages in subgroups are different when combining the subgroups.

20
Q

If a study involves a data set from the past, what is it called?

A

Historical control in which time will become a confounding variable

21
Q

What is a control group?

A

A group in a study that receives the placebo treatment

22
Q

What is a controlled experiment?

A

Investigators allocate subjects into 2 groups: control and treatment group
The effects of the variable/treatment is controlled

23
Q

What is controlling for confounders?

A

By dividing up the groups into subgroups based on confounders, the influence of those variables can be reduced

24
Q

What is the actual difference between RCT and observational studies?

A

In RCT, the investigator is the one allocating each participants into control/treatment group. This means that there is already intervention or manipulation to the variable being studied.

Meanwhile, in observational study, the investigator observes/studies the participants who are already exposed to the independent variable (eg: pp who already smoke since we cannot force pp into treatment group in which they have to start smoking) ==> No intervention