Measurement and bias Flashcards

1
Q

how is a hypothesis written

A

exposure to X is associated with an increased/decreased risk of Y

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2
Q

2 features of hypotheses

A

testable

specific

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3
Q

two types of errors?

A

random error

systematic error

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4
Q

3 types of random error

A

sampling error
individual biological variation
measurement error

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5
Q

measurement error formula

A

measured score = true score +/- error

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6
Q

example of systematic error

A

bias

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7
Q

selection bias

-what point in study does it arise

A

allocation stage

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8
Q

selection bias: what is it

A

non random allocation

researcher manipulates allocation

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9
Q

selection bias: how to control

A

random allocation

allocation concealment

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10
Q

performance bias

  • when
  • what
A

when interventions are being delivered

either

  • experimenter treats either group differently
  • participant realises which they’ve been allocated to and acts differently
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11
Q

performance bias

-controlling

A

double blind

placebo

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12
Q

detection bias

  • when
  • what
A

at the data collection stage

either

  • some differences in how outcomes are determined between groups
  • researcher question’s individuals outcome variable, causing them to change it
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13
Q

detection bias

-controlling

A

blind outcome assessors

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14
Q

measurement bias

  • when
  • what
A

when measuring either variable

either

  • measurement tool is wrong
  • one researcher consistently measures something wrong
  • different tools per group
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15
Q

measurement bias

-fixing

A
  • correct the tool
  • train the researcher
  • use consistent tools/protocols
  • collect data from multiple sources
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16
Q

recall bias

-what

A

participant forgets or omits information

17
Q

recall bias

-controlling

A

have a good research question
have a good questionnaire
have a good researcher

18
Q

attrition bias

-what

A

differential attrition between groups

19
Q

attrition bias

-controlling

A

may use intention to treat analysis

20
Q

publication bias

-what

A

research that has new/expected findings is more likely to be published than research with null/unexpected findings

21
Q

describe intention to treat analysis

A

use results of all people regardless of attrition/not following guidelines

22
Q

opposite of intention to treat analysis?

A

per protocol analysis

23
Q

what % of attrition is acceptable to lead to little bias?

A

<5%