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RME > Week 4 > Flashcards

Week 4 Flashcards

1
Q

Validity

A

the degree to which a test or instrument measures what it purports

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2
Q

Validity

Logical / Face Validity

A

do the methods and approach make sense?

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3
Q

Validity

Content Validity

A

Does the test fully represent the domain of the concept it is intended to measure?

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4
Q

Validity

Criterion Validity - Concurrent

A

correlating an instrument with a criterion administered at the same time

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5
Q

Validity

Criterion Validity - Predictive

A

correlating an instrument with a criterion administered in the future

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6
Q

Criterion Validity - Predictive

Cross- Validation

A
  • generate a predictive equation with 1/2 of the sample
  • confirm the prediction equation works with other 1/2 of sample
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7
Q

Validity

Construct Validity

A

degree to which the scores from a test measure the hypothesis construct

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8
Q

Measurement Reliability

A
  • refers to the consistency and stability of a measurement tool or method
  • indicates how dependably a method measures something over time, across different observers, or in various contexts
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9
Q

What are common sources of measurement errors?

A
  • testing
  • instrumentation
  • scoring
  • participant
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9
Q
A
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10
Q

Reliability Tests

Test-retest Reliability

A

measures the consistency of results when the same test is administered to the same sample at different points in time

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11
Q

Reliability Tests

Interrater Reliability

A

assesses the degree to which different observers or rates agree in their assessments

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12
Q

Reliability Tests

Parallel Forms

A

comparing two different versions of a test that are designed to be equivalent

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13
Q

Reliability Tests

Internal Consistency

A

examine the consistency of results across items within a test
* a common measure of internal consistency is Cronbach’s alpha, which assesses how well the items on a test measure the same construct

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14
Q

Common Statistical Approaches

Test-retest Reliability

A
  • Pearson correlation coefficient
  • Intraclass correlation coefficient (ICC)
  • Coefficient of Variation
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15
Q

Common Statistical Approaches

Interrater Reliability

A
  • Percent agreement
  • Cohen’s alpha
  • Intraclass correlation coefficient (ICC)
16
Q

Common Statistical Approaches

Parallel Forms Reliability

A
  • Pearson Correlation coefficient
  • Split-Half method
  • Counterbalancing method
17
Q

Common Statistical Approaches

Internal Consistency

A
  • Cronbach’s Alpha
  • Split-Half reliability
18
Q

Ranking research design from weakest evidence to strongest evidence.

A
  • Animal research (does not involve animals)
  • Clinical textbooks, experts opinions (not primary research)
  • Case reports / case studies (no or little design)
  • Case-control studies (observational)
  • Cohort studies (observational)
  • Randomized control trials (experimental)
  • Systematic review (evidence study)
  • Meta-analysis (evidence study)
19
Q

Threats to Internal Validity

History

A

External or historical event that occurred during the course of the study that may be responsible for the effects instead of the intervention itself

20
Q

Threats to Internal Validity

Maturation

A

An internal and natural process that leads participants to change on the dependent measure

21
Q

Internal Threats to Validity

Testing

A

Changes in test scores occur because of repeated testing

22
Q

Threats to Internal Validity

Differential Selection

A

Any difference between the study groups before the start of the study due to either self-selection or experimenter selection

23
Q

Threats to Internal Validity

Instrumentation

A

Changes in instrument calibration or human observers

24
Q

Threats to Internal Validity

Regression to the Mean

A

The phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement

25
Q

Threats to Internal Validity

Selection Interactions / Expectancy

A

Both researchers or study subjects may tend to expect one group may perform better (or worse) the other

26
Q

Threats to Internal Validity

Experimental Mortality (Attrition)

A

People can drop out of the study for any reason; if reason is related to treatment status it may cause bias

27
Q

What are threats to External Validity?

A
  • selection bias
  • pretesting
  • experimental setting
  • multiple treatment
28
Q

Threats to External Validity

Selection Bias

A
  • Who is included/excluded
  • Race/ethnicity, age, sex, lifestyles, SES
  • Disease characteristics
29
Q

Threats to External Validity

Pretesting

A

If you pretest, then when participants take the “true test” their responses may differ compared to if they never took the a pretest

30
Q

Threats to External Validity

Experimental Setting

A
  • Participants performance improves just b/c they know they are being watched
  • Hawthorne Effect
31
Q

Threats to External Validity

Multiple Treatments

A

Receiving on treatment may influence how you respond to other treatments

32
Q

Random Control Trial (RCT)

A
  • A study design where participants are randomly assigned to either the intervention group or the control group
  • randomization minimizes bias, allowing for causal inferences
33
Q

Quasi-Experimental

A
  • A study design that looks at the effect of an intervention without random assignment
  • while it can still compare groups, the lack of randomization makes it more prone to bias
34
Q

Natural Experiment

A
  • A study that takes advantage of “naturally occurring circumstances in which subsets of the population have different levels of exposure to a supposed causal factor, in a situation resembling an actual experiment”
  • Provides an alternative when it is impossible or unethical to assign treatment

RME (5 decks)

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