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Pop health > Lecture 24 chance 2 > Flashcards

Lecture 24 chance 2 Flashcards

1
Q

Internal validity

A

Extent to which we can rely on we think that the study findings valid based on how the study was done

3 components - chance, bias, confounding

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2
Q

Chance

A

Sampling error

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3
Q

P values

A

Based on hypothesis testing

Probability of getting study estimate (or one further from the null), when there is really no association in population, because of sampling error (chance)

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4
Q

P values telling us about associations about

A

Differences between groups

Whether or not that difference is sufficiently large, inconsistent with there being no difference of underlying population

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5
Q

Truth

A

Dont know it

Could be association between exposure and outcome Or no association between exposure and outcome

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6
Q

2 ways to be correct

A

Find an association when there truly is one Or not find an association when there isnt one

Consistent with the underlying population

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7
Q

Could be wrong in 2 ways

A

find an association in study (measure of association that does not equal null value) when there truly is no association (population parameter is of null value) Or no association when there is one

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8
Q

P values

A

Probability from study

Study has got it wrong this way it has found an association when there truly is not one in the population

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9
Q

P values require

A

Null hypothesis

Alternative hypothesis

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10
Q

Really is no association in the population

A

Population parameter equals null value (ratio measure null value = 1, Difference measure null value = 0)

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11
Q

Really is an association in the population hypothesis is

A

Parameter does not equal null value

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12
Q

P values Probability when

A

null hypothesis is true that our study has found an association when there truly isnt

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13
Q

Type 1 error

A

Finding an association when there truly isnt one

Set at 5%

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14
Q

Probability less than 5%

A

sufficiently unlikely that chance is the reason for finding this association

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15
Q

Threshold: 0.05 (5%, or 1 in 20)

A

Find association by chance

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16
Q

If p < 0.05

A

reject null hypothesis (no association)
Accept alternative hypothesis (is association in population)
Association is statistically significant

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17
Q

Never accept

A

null hypothesis

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18
Q

p > 0.05

A

Fail to reject H0
Reject HA
Association is: ‘Not Statistically Significant’

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19
Q

3 elements

A

Interpret RR measures of associations

20
Q

Type 2 error

A

Study Don’t find association that truly exists
Truth there is an association in population between the exposure and outcome
Due to not having enough people in study

21
Q

To avoid type 2 error

A

Sufficient statistical power
Enough people in study
Can calculate how many people needed in study to have a certain level of statistical power

22
Q

To assess statistical significance

A

See if 95% CI includes null value

23
Q

95% CI includes null value

A

95% CI the study findings are consistent with there being no association in study population
Not statistically significant
p > 0.05

applies to RR RD

24
Q

95% CI doesnt include null value

A

Not consistent with no association in population
Statistically significant
p < 0.05

applies to RR and RD

25
Q

3 steps

A

Interpret measure of association (RR)
Interpret CI
Statistical association

26
Q

Arbitrary threshold 0.05

A

Assess significance
No logic behind it
Still allows for error (type 1 error)

27
Q

P values Refers to chance

A

Don’t say anything about whether the results are valid, useful or correct

Study Could be bias, study could be done poorly could still get a statistical significant finding

Don’t tell how good the study is Just tell what the likely impact of chance is

28
Q

Absence of a statistically significant association is not evidence of absence of a real association

A

Absence of evidence not the same as evidence of absence

Not finding a pvalue that is statistically significant association is not evidence that there is no association. Its just evidence that you haven’t found it

29
Q

chance consists of

A

validity
CI
sampling error
p values

30
Q

What are p-values?

A

Probability of getting study estimate (or a study estimate further from the null), when there is really no association, because of sampling error (chance)

31
Q

If p value probability really low,

A

estimate is due to sampling error (chance)

Uses logic of hypothesis testing

32
Q

null hypothesis (H0)

A

Really is no association in the population

Parameter equals null value

RR, OR = 1
RD = 0

33
Q

the alternative hypothesis (HA)

A

Really is an association in the population

Parameter does not equal null value

RR OR = 1
RD = 0

34
Q

P value less than 0.05

A

Chance is an unlikely explanation of the study finding

Reject H0
Accept HA

Association is:
‘Statistically Significant’

35
Q

p-value is greater than 0.05

A

study finding is consistent with chance as an explanation

Fail to reject H0
Reject HA

Association is:
‘Not Statistically Significant’

36
Q

Probability of getting study estimate (or an estimate further from the null) when there is really no association because of

A

sampling error (chance)

37
Q

Type-II errors

A

Incorrectly fail to reject H0 when should have
(p should have been < 0.05 but got > 0.05)

due to having too few people in the study

38
Q

Bigger sample size

A

more likely to get small p

39
Q

Smaller sample size

A

less likely to get small p

40
Q

You can see whether a p-value is greater or less than 0.05 with a

A

95% confidence interval

41
Q

p > 0.05

A

95% CI includes null value

study finding is consistent with chance as an explanation

Not statistically significant

Fail to reject H0 and reject HA

42
Q

p < 0.05

A

not 95% CI includes null value

Chance is an unlikely explanation of the study finding

Statistically significant

Reject H0 and accept HA

43
Q

Why p-values are problematic

A

Arbitrary threshold

Only about H0

Nothing about importance

44
Q

Arbitrary / artificial threshold

p value

A

At 5% threshold will still find a statistically significant association when there really isn’t one at least one time in twenty (Type-I error)

45
Q

Only about H0

p value

A

Just give evidence about consistency with the null hypothesis

Don’t say anything about precision

46
Q

Nothing about importance

p value

A

Statistical significance is not clinical significance

Don’t say anything about whether the results are valid, useful or correct

Absence of a statistically significant association is not evidence of absence of a real association

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