Week 3 Flashcards

1
Q

performance bias

A

systematic differences in the care provided to the comparison groups other than the intervention being tested

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2
Q

reducing performance bias

A

blinding

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3
Q

detection bias

A

outcome assessment differs systematically between comparison groups

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4
Q

reducing detection bias

A

blinding of outcome assessors

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5
Q

measurement bias

A

systematic error in the measurement of information on the exposure or outcome

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6
Q

measurement bias aka

A

information bias and observation bias

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7
Q

misclassification

A

incomplete medical records, recording errors, misinterpretation of records, errors in the questionnaire including recall bias by the participant

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8
Q

non differential misclassification

A

information is incorrect, but same across the two groups

underestimates the strength of association between exposure and disease

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9
Q

differential misclassifaction

A

information errors differ between the two groups

either a decrease or increase in the perceived association between exposure and outcome

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10
Q

reduce measurement bias

A

standardised research protocols, obtaining information from multiple sources, blinding of researchers and staff to the exposure/disease status of the participant, training of interviewers

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11
Q

reduce recall/response bias

A

defining research question carefully
devise high quality questionnaires
highly trained research staff

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12
Q

attrition bias

A

loses to follow up or dropouts

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13
Q

intention to treat analysis (ITT)

A

analysing all participants recruited from the randomisation process even if they have not completed the study
done to avoid the effects of crossover and dropout

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14
Q

methods for dealing with missing data

A

baseline values or last outcome measured by participant carries over
sensitivity analysis
mixed models
worst and best cases scenarios

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15
Q

reducing attrition bias

A

create project identity
good communication between staff and participants
keep follow up interviews brief
accessibility to clinics

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16
Q

per-protocol analysis

A

only data for participants who complete the study are analysed

17
Q

as treated analysis

A

middle grounds where non adhering participants moved to control group

18
Q

negative confounding

A

confounding variable biases towards the null hypothesis

19
Q

positive confounding

A

confounding variable biases away from null hypothesis

20
Q

Reduce confounding

A

limit participation of certain subgroup who share the confounding factor
analysis of the data through stratification
filter for certain groups
matching in case control studies
randomise individuals to different groups

21
Q

how much attrition is too much (attrition bias)

A

less than 5% leads to little bias

more than 20% threatens study validity

22
Q

probability can be defined by

A

relative frequency

23
Q

parameter

A

unknown characteristic of interest in the true population

24
Q

sample result

A

estimated value of the parameter based on a random sample taken from the study population

25
Q

descriptive epidemiology

A

hypothesis generation; person, place, time

26
Q

analytical epidemiology

A

hypothesis testing; study design, methods

27
Q

aetiology

A

cause of a disease

28
Q

measured score

A

true’ score +/- Error

29
Q

bias vs confounding

A

Bias creates an association that is not true whereas confounding describes an association that is true, but potentially misleading; potential to correct for confounding once study completed

30
Q

test-retest reliability

A

test results are consistent over time by administering the same test twice over a period of time to same group of individuals

31
Q

inter-rater reliability

A

assess the degree to which different judges or raters agree in their assessment decision

32
Q

construct validity

A

does test measure what is claims to be measuring

33
Q

negatively skewed

A

mean < median < Mode

34
Q

positively skewed

A

mean>median>mode

35
Q

controlling confounders in design stage

A

randomisation
restriction
matching

36
Q

controlling confounders in analysis stage

A

stratification

statistical modelling