Data1001

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36 Terms

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Randomised Controlled Trial (RCT)

The most basic form of a randomised controlled trial (RCT) involves 2 steps:

Divide subjects into 2 Groups: Treatment and Control.

The Control is given a placebo.

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Placebo

Fake treatment

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Contemporaneous Control group

A contemporaneous Control group occurs at the same time as the Treatment Group.

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Historical Control group

A historical Control group occurs at an earlier time than the Treatment Group.

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The placebo effect

An effect which occurs from the subject thinking they have had the treatment.

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Bias

Something which effects the ability of the data to accurately measure the treatment effect.

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Consent Bias

When subjects choose whether or not they take part in the experiment.

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Double-blind Trial

When the subjects and investigators are not aware of the identity of the 2 Groups

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Observational Study

Research that gathers data in a real-world setting without intentionally manipulating any variable.

The investigator cannot use randomisation for allocation to groups.

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4 Precautions of Observational Studies

1. Observational studies can't establish causation.

2. Observational Studies can have misleading hidden confounders.

3. Observational studies with a confounding variable can lead to Simpson's Paradox

4. Observational studies result from using an historical control

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Confounding

When the Treatment Group and Control Group differ by some third variable (other than the treatment) which influences the response that is studied.

Hence the seeming effect of the treatment is also caused by other factors.

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Survivor bias

when certain types of subjects finish the study

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Adherer Bias

when certain types of subjects keep taking the treatment (or placebo), as opposed to the non-adherers.

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Selection bias

when some subjects are more likely to be chosen to be in the study than others.

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Simpson's Paradox

When relationships between percentages in subgroups are reversed when the subgroups are combined.

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How many observations and how many variables in the mtcars set, given this output:

> dim(mtcars)

[1] 32 11

32 observations, 11 variables

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Best chart for 1 qualitative variable?

Bar plot

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Best chart for 2 qualitative variables?

Double bar plot

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Best charts for 1 quantitative variable?

Histogram

Box plot

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Best charts for 2 quantitative variables?

Scatter plot

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Best chart for 1 quantitative and 1 qualitative variable?

Comparative box plot

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What does the area of a box in a histogram represent?

Percentage

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What does the height of a box in a histogram represent/

Crowding

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What would you call it when an interval contains the left endpoint but excludes the right endpoint? What is the command for this in R?

Eg. an 18 year old would be counted in [18,21) not [0,18).

Left closed, right open

In R: right = F

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How many columns/rows does the following output code for:

par(mfrow = c(1, 2))

Puts the graphic output in 1 row with 2 columns

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Mean

Average of the data

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Median

The middle data point

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Which is more robust? The Mean or the Median

Median

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What does it mean when a variable is classified as a 'factor' in R

It is Qualitative/categorical

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What does it mean when a variable is classified as an 'int' in R

Quantitative, discreet

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What does it mean when a variable is classified as a 'num' in R

Quantitative, continuous

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What is the mean and SD of the standard normal curve?

Mean: 0

SD: 1

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1 SD from the mean of a data set will capture what percentage of the data?

68%

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2 SDs from the mean of a data set will capture what percentage of the data?

95%

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3 SDs from the mean of a data set will capture what percentage of the data?

99.7%

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Interquartile Range

Describes the spread of middle 50% of a data set, IQR = Q3 - Q1.