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20 Cards in this Set

  • Front
  • Back
Reliability
- Does my measure consistently respond the same way to the same situation?
- Consistency and repeatability
Ways of checking reliability:
Test-Retest Reliability
- Same test, two time points
- Same measurement to finest detail
- Do not want to do this is if there is a chance for things to change between time one and two
Ex) Step on scale, step off scale
Ways of checking reliability:
Inter-Rater Reliability
- Same test, done by two different people
- Different versions of measurement technique (same time point or diff. time points)
- Want to make sure you get the same results
- Important with face-to-face interviews when the person collecting the data is engaged and involved
Ways of checking reliability:
Inter-Method Reliability
- Two different tests, developed by the same methods
- Say question again to people that isn't as familiar
- There should be a correlation b/t the two questions
- Changing wording or phrases
Ways of checking reliability:
Internal Consistency
- Compare different items on the same test
Comparing two tests using correlations starts with...
- Sample 1 on x axis
- Sample 2 on y axis
If increasing slope, then there is ___________________.
Consistency
R =
- How strong the correlation is
- How tight/how clustered the data is around the line of best fit
P =
How significant the correlation is
R is negative when there is...
An inverse correlation
What do correlations of 1 and 0 mean?
1 = perfect reliability
0 = no reliability
The more residuals you have, the weaker the correlation, and R is closer to...
- R is closer to 0
If all residuals are close to the line of best fit, then R is closer to...
- R is closer to 1
Random Error
- No idea where it came from
- Associated with reliability
Systematic Error
- Consistently and always biased in a certain direction (more of a solvable problem)
- Associated with validity
The amount of residuals and how weak the correlation is is directly related to...
- Directly related to random error and how much of it there is
Requirements for Validity Review:
- Agreed-upon DEFINITION
- Measurement methods SPECIFICALLY collect info. about events that fit that definition
- Measurement methods COMPLETELY assess the whole concept described by that definition
- IF there is another measurement method for the same concept that is known to be valid, the new method should have both a strong correlation with the GOLD STANDARD method and little bias (little/no difference in paired T-test)
Paired T-test
- Tests for an overall difference in the average between 2 repeated measurements
- For each individual, calculate measure 1 minus measure 2 (subtract the difference)
- If there is no difference (Null), then the distribution of the differences should be centered about zero
---> Difference from zero is bias
---> Greater variation/spread of these differences is random error
Predictive Validity
- Does the measure help us understand the real world?
- Measure something at time 1 and then measure something else at time 2 and see if they correlate in the expected direction
- 2 totally different measurement techniques with 2 different scales; so, do not need slope=1 and int.=0
Discriminant Validity
- Wanting the measure to be different from something else, to show a contrast between them
- Looking for a low or zero correlation
- Want to show that they are separated