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critical numbers PT Flashcards

1
Q

what is a case control study

A

find people with a disease, look back in time and see if they were exposed to risk factor in question
Retrospective

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2
Q

what are the positives of a case control study

A

works well for investigating rare outcomes
fast + cheap
few ethical considerations

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3
Q

what are the negatives of a case control study

A

cannot prove causation/eliminate cofounders
can be difficult to establish order of events
bias (recall)
can only investigate a single disease

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4
Q

what is a cross sectional study

A

take a sample, see who has the disease right then and there

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5
Q

what are the positives of a cross sectional study

A

fast/cheap
few ethical considerations
generates hypothesis

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6
Q

what are the negatives of a cross sectional study

A

cannot prove causation/eliminate bias
less suitable for rare diseases
difficult to get an understanding of order of events
sample bias

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7
Q

what is a cohort study

A

collect information from a sample, some with exposure, some do not (none with outcome)
follow up over time and see if there is a link between exposure and outcome
prospective

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8
Q

what are the positives of a cohort study

A

few ethical considerations

clarity on event sequence

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9
Q

what are the negatives of a cohort study

A

cannot prove causation/eliminate cofounders
not suitable for rare diseases or when disease takes a long time to develop
time consuming/expensive
difficulty following up
patients can change behaviours in the cohort

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10
Q

what is a randomised control trial

A 
multiple groups (arms) , give each different exposures and compare outcomes 
can balance arms by matching, randomising, cross-over, placebos, binding
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11
Q

what are the positives of a RCT

A

gold standard - can prove causation by eliminating cofounders
random - less bias

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12
Q

what are the negatives of a RCT

A

not suitable for rare outcome or when outcome takes a long time to develop
time consuming + expensive
often unethical
issues with follow up/ compliance

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13
Q

what is an ecological study

A

massive sample, by looking at data previously collected to look at prevalence, trends and correlation (populations, not individuals)

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14
Q

what are the positives of an ecological study

A

fast/cheap
very large sample - small SE
easy
good to generate hypothesis

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15
Q

what are the negatives of ecological studies

A

variation/ bias/ inconsistency in data

cannot prove causation

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16
Q

what is ecological fallacy

A

where there is a correlation between predictor and outcome, but this does not mean causation

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17
Q

what is the target population

A

the population the sample represents

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18
Q

what is the sample population

A

the people whom data is collected

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19
Q

what is random sampling

A

random number generator, “draw a name out of a hat”. Usually preferred way of sampling.

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20
Q

what is systematic sampling

A

e.g. count of the list and every “k”th element is taken

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21
Q

what is convenience sampling

A

The first people who approach you are used. Easiest technique but likely the worst.

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22
Q

what is cluster sampling

A

Divide the population into groups, usually geographically
Each group is called a cluster, or block
Clusters are randomly selected, each element in the selected cluster used.

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23
Q

what is stratified sampling

A

Divide the population into groups/strata, based not on geography, but some characteristic, e.g. Males or Females.
A sample is taken from each of these strata using either random, systematic or convenience sampling

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24
Q

what is sampling bias

A

sample is not representative of the target population

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25
Q

what is recall bias

A

people fail to remember specifics innocently

26
Q

what is social-desirability bias

A

incorrect information is given due to societal pressure

27
Q

what is information bias

A

where data is consistently measured wrong

28
Q

what is volunteer bias

A

volunteers aren’t representative

29
Q

what is produced bias

A

subjects in different arms are treated differently

30
Q

what is reliability

A

how consistent the results of the study are

31
Q

what increases reliability

A

larger sample size

peer reviewed

32
Q

what is validity

A

does the test measure what it is supposed to? - have confounders been addressed

33
Q

what are the 2 types of numeric variable

A

continuous (any value within a range)

discrete (whole numbers)

34
Q

what are the 2 types of categorical variables

A

ordinal (distinct ordering or hierarchy)

nominal (no distinct ordering)

35
Q

what is risk

A

number of examined outcomes / total number of possible outcomes

36
Q

what is the absolute risk difference?

A

difference between 2 risks

37
Q

how do you calculate absolute risk difference (ARD)

A

work out the 2 individual risks for the subsets you’re measuring and then subtract them

38
Q

how do you calculate number needed to treat (NNT) or harm (NNH)

A

NNT/H = 1/ARD

39
Q

how do you calculate risk ratio/relative risk

A

divide one risk by another

40
Q

what is odds

A

the ratio of the probability of the occurrence of the event to the probability of non-occurrence

41
Q

odds equation

A

odds = probability / (1- probability)

42
Q

how do you calculate odds ratio

A

divide one odd by the other

43
Q

what is sensitivity

A

The sensitivity of a test is the proportion of people who test positive among all those who actually have the disease

= true positive/ true negative + false negative

44
Q

what is specificity

A

The specificity of a test is the proportion of people who test negative among all those who actually do not have that disease.

= true neg/ true neg+ false pos

45
Q

what is positive predictive value (PPV)

A

the probability that following a positive test result, that individual will truly have that specific disease.
= true pos / true pos + false pos

46
Q

what is negative predictive value (NPV)

A

the probability that following a negative test result, that individual will truly not have that specific disease.
= true neg/true neg+ false neg

47
Q

what is test accuracy

A

the proportion of true result that were revealed

= TP +TN/ TP +TN + FP +FN

48
Q

what is prevalence

A

the proportion of people within the community with the disease

49
Q

how do you calculate standard deviation

A

minus the mean from every data point, square it and sum all values together. Following this, divide by n-1 and then square root the entire result

50
Q

what is standard error

A

the SD of all the sample means S/ square root of n

51
Q

what does standard error assume

A

the data is normally distributed and there is a sufficient sample size

52
Q

what is interquartile range , how do you calculate it and what is it useful for

A

Used in conjunction with the median to describe data. Calculated by subtracting the upper quartile (75%) from the lower quartile (25%)
Especially useful to use when the data is not normally distributed (i.e. skewed)

53
Q

what are confidence intervals

A

give limits in which we are confident (in terms of probability) that the true population parameter lies

54
Q

how do you calculate 95% confidence intervals

A

mean +/- 1.96 x standard error

55
Q

what is the p-value

A

the probability of obtaining your results or results more extreme, if the null hypothesis is true

56
Q

when do you reject the null hypothesis

A

if the p-value is less than 0.05

57
Q

using Pearson’s correlation coefficient what does +1, -1, and 0 mean

A

+1 = perfect positive linear association

-1 = perfect negative linear association

0 = no linear relation at all

58
Q

simple linear regression formula

A 
y = mx + c
y - dependent variable 
m- gradient 
x- independent variable 
c- intercept
59
Q

what is multiple linear regression

A

expansion of simple linear regression to include multiple independent variables

60
Q

what is logistic regression

A

used when your outcome variable (y) is a binary variable

61
Q

what does PICO stand for

A

P - patient of population
I - intervention or indicator
C - comparison or control
O - outcome

Critical numbers (7 decks)

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