Biostatistics Flashcards

1
Q

Health promotion prevention category

A

Primary prevention

Enables people to improve their health

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2
Q

Health risk assessment method

A

Questionnaires collecting demographic, medical, lifestyle, family history information to calculate a patient’s risk age.

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3
Q

Percent of data between +/- 1 SD

A

68%

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4
Q

Percent of data between +/-2 SD

A

95%

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5
Q

Percent of data between +/- 3 SD

A

99.7%

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6
Q

The parameter of diagnostic tests most important for screening

A

High sensitivity

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7
Q

Decreasing the cutoff point will result in:

A
Sensitivity: increased
True positive: increased
False positive: larger increase
PPV: decreased
False negative: decreased
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8
Q

Hawthorne effect (observer effect)

A

The tendency of study subjects to change their behavior as a result of their awareness that they are being studied

Affects validity

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9
Q

Berkson’s bias

A

Selection bias created by choosing hospitalized pts as the control group

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10
Q

Pygmalion effect

A

A researcher’s beliefs in the efficacy of treatment can potentially affect the outcome

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11
Q

Chi-square test for independence

A

To test the association between two categorical variables

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12
Q

Two-sample z test

Two/sample t test

A

Used to compare 2 group means(numerical values), not categorical variables.

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13
Q

ANOVA

A

Used to compare the means of 2 or more groups

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14
Q

Test parameter influenced by disease prevalence

A

PPV

NPV

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15
Q

Test parameter influenced by pretest probability

A

NPV

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16
Q

Validity of a test

A

The test measures what it is supposed to measure

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17
Q

Positive likelihood ratio

A

the probability of a person who has the disease testing positive divided by the probability of a person who does not have the disease testing positive.

=sens/ (1-spec)

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18
Q

Negative likelihood ratio

A

the probability of a person who has the disease testing negative divided by the probability of a person who does not have the disease testing negative

=(1-sens)/ spec

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19
Q

In a smoker, diabetic, alcoholic, sedentary, hypertensive individual, what is the intervention most likely to reduce overall mortality rate?

A

Smoking cessation

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20
Q

Negative skewed distribution curve

A

Peak (mode) to the right
Mean to the left
Median in between

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21
Q

Positively skewed curve

A

Mode to the left
Mean to the right
Median in between

22
Q

NNT calculation

A

1/ARR

23
Q

ARR

A

Control rate - treatment rate

24
Q

RRR

A

ARR/Control rate

25
Q

Relative risk

A

Treatment rate/control rate
Or
Risk of outcome in exposed / risk of outcome in non-exposed

26
Q

Type II error (beta) definition

A

The probability of concluding there is no difference when such a difference truly exists

27
Q

Power of study

A

1- beta

The ability of a study to detect a difference when such a difference truly exists

28
Q

Type one error (Alpha)

A

The probability of seeing a difference when there is no difference in reality

29
Q

Definition of a reliable test (precision)

A

It gives similar or very close results on repeat measurements

30
Q

Validity or accuracy

A

A test’s ability to measure what it is supposed to measure

31
Q

How to quantify the reliability of a test

A

In terms of the coefficient of variation ( standard deviation divided by mean of repeated measurements) generally expressed as a percentage

32
Q

The odds ratio measurement

A

Is a measure of association between an exposure and an outcome

All in favor of association/all against an association
=ad/bc

33
Q

The significance of confidence of interval in a meta-analysis study

A

If the range of confidence of interval does not include a null value, the result is statistically significant.

If the CI crosses the null value then there is no statistically significant difference between the groups.

34
Q

Matching Method

A

Used in design stage of case-control studies to control confounding

35
Q

Stratified analysis

A

Can be used to negate confounding effect

36
Q

Confounding effect vs effect modification in stratified analysis

A

Stratified analysis disappears the observed difference in the study due to “confounding effect” but potentiates the observed difference due to “effect modification”

37
Q

Case fatality rate measurement

A

Calculated by dividing the number of fatal cases by the total number of people with the disease

38
Q

Atributable risk percentage

A

100 x (Risk in exposed- Risk in unexposed) / risk in exposed

39
Q

Attrition bias

A

In prospective studies if loss to follow-up occurs disproportionately between the exposed and unexposed groups attrition bias can result if the lost subjects differ in the risk of developing the outcome compared to the remaining subjects.
It is a form of selection bias.

40
Q

Latency definition

A

The concepts of latency. It can be used for infectious diseases, risk factors and risk reducers.
The time between exposure and clinically apparent disease.

41
Q

The rare disease assumption

A

Refers to the fact that the odds ratio approximates RR When disease prevalence is low

42
Q

The relative risk null value

A

1

For a result to be considered statistically significant, its corresponding CI must not contain the null value

43
Q

The relationship between CI and P-value

A

A statistically significant 95% CI corresponds to a P-value <0.05. A statistically significant 99% CI corresponds to a P-value <0.01.

44
Q

Mean +/- 1.96 SD would cover

A

95% of the observations

45
Q

The mean +/- 2.58 SD would cover

A

99% of the observations

46
Q

SE= standard error

A

SD/√n
A way to account for variability due to sampling

95% CI= mean +/- 1.96 SE
99% CI= mean +/- 2.58 SE

47
Q

Relative risk, relative rate are for which type of study?

A

Cohort

Because these are incidence measures, they cannot be calculated from case-control studies

48
Q

Exposure odds ratio is for which type of study?

A

Case-control

49
Q

Prevalence odds ratio is for which type of study?

A

Cross-sectional

50
Q

Generalizability or external validity

A

The applicability of the obtained results beyond the cohort that Was studied