Significance tests and p values Flashcards

1
Q

Definition of a null hypothesis

A

Staring assumption about the population of interest

No real difference/association

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2
Q

Definition of a p value

A

The probability that you will get AT LEAST the observed value assuming that the null is true

A way of weighing the evidence against null

Probability from a significance test

The larger the difference observed in your sample, the less likely that it could have come from a population where no difference exists

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3
Q

Definition of clinical significance

A

Difference observed is large enough to be clinically meaningful
Not a statistical judgement

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4
Q

Why do we use significance tests

A

Results are based on a sample, can’t be sure if results benefit whole population
Different samples give different results, could be due to chance

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5
Q

What is the null hypothesis

A

Assumes that there is no difference/association

Must have enough evidence from sample data to reject null

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6
Q

What is the p value

Why is it useful

A

Probability found from statistical significance tests
Helps you weigh up evidence against null
the larger the difference observed in your sample, the less likely that is could have come from a population where no difference exists

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7
Q

How do you interpret p < 0.05

A

If p< 0.05 => reject null as association exists => statistically significant
If 0 not included in CI, can really reject null

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8
Q

How do you interpret p ≥ 0.05

A

If p ≥ 0.05 => can’t reject null => not statistically significant
Can’t accept it, other possibilities ar present
If 5% within 95% for difference => results are consistent with null

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9
Q

How do you present p values

A

State exact p values
Avoid only stating p< 0.05 or p≥ 0.05
-only acceptable if p is tiny

Allows for full interpretation of evidence

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10
Q

What is the difference between clinical and statistical significance

When would a result be clinically important but not statistically?
When would a result be statistically important but not clinically?

A

Difference observed is large enough to be clinically meaningful
Clinically important, not statistically => occurs when sample size is small
Statistically important, not clinically => occurs when sample size is large

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11
Q

What is a 2 sided significance test

When would you use it

A

Used when you have a

  • null hypothesis, no difference
  • alternative hypothesis, difference exists on either side
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12
Q

What is a 1 sided significance test

When would you use it

A

Used when you have a

  • null hypothesis, no difference/difference exists in 1 direction
  • alternative hypothesis, difference exists in other direction
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13
Q

How would you choose between a 2 sided and 1 sided test

A

1 sided does not differentiate between no effect and a harmful effect => unaccepatble
2 sided should always be use unless clearly justified before hand

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