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| The extent to which data obtained from measurement are directly relevant to target behavior of interest and to the reason(s) for measuring it |
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Part of construct validity; for code |
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| Refers to the consistency of measurement, specially, the extent to which repeated measurement of the same event yields the same values. |
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A relatively straightforward way of calculating inter-observer agreement is to use a total agreement approach (frequency-ratio approach). Using a total agreement strategy, a research sums the total number of responses recorded by each observer, divides the smaller total by the larger total, and multiples the amount by 100%.
:smaller/larger X 100% |
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A/(A + D) X 100%
Agreements = agree on occurrence or nonoccurrence |
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| High and low rate problem |
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}High rates: spuriously high because of agreements on occurrence?
}Low rates: may rarely agree on occurrence & still have high % interval agreement
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} Reactivity
} Drift
} Expectancy
} Complexity
} Location of observer
} Rates of behavior
} Episodic behavior |
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| Pros & cons of co-plotting |
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| From ecological science, more concerns, more monitoring |
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Intrusiveness; Efficiency; Outcome; Sustainability |
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It refers to whether a scale measures or correlates with the theorized psychological construct) The scale seeks to operationalize the concept, typically measuring several observable phenomena that supposedly reflect the underlying psychological concept. –Assessing how well this has been accomplished.
It is connecting dependent and independent variables in outcome research; examples of school risk, performance, aggression |
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Reliability puts limits on validity statements by error estimates.
It describes the extent to which a measurement procedure yields the same value when brought into repeated contact with the same state of nature. Reliable measurement is consistent measure |
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| A occ/(A occ + D occ) X 100% |
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| A nonocc/(A non + D nonocc) X 100% |
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| 2nd observer that comes into observation periodically and compare results with the 1st observer for agreement |
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Pros:
} Contact with data rather than summary statistic
} Evaluation in absolute differences
} Detection of threats to internal validity
} More closely related to decision ethics |
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} Cons: Disadvantages: visual analysis, no standard criteria, cluttering |
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| components are accurately identified & described |
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