Which term describes the ability to measure what was intended to be measured?
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Validity Validity is the extent to which an instrument, such as a survey or test, measures what it is intended to measure (also known as internal validity). This is important if the results of a study are to be meaningful and relevant to the wider population. There are four main types of validity:
Reliability Reliability is the overall consistency of a measure. A highly reliable measure produces similar results under similar conditions so, all things being equal, repeated testing should produce similar results. Reliability is also known as reproducibility or repeatability. There are different means for testing the reliability of an instrument:
Internal consistency can be measured using Cronbach’s alpha (α) – a statistic derived from pairwise correlations between items that should produce similar results. The usual range for the alpha will be zero to one, with values above 0.7 generally deemed acceptable, and a figure of one indicating perfect internal consistency. A negative value will occur if the choice of items is poor and there is inconsistency between them, or the sampling method is faulty. In these cases the items chosen need to be reviewed, along with possibly the sampling methods used for the items. Inter-rater reliability can be measured using the Cohen’s kappa (k) statistic. Kappa indicates how well two sets of (categorical) measurements compare. It is more robust than simple percentage agreement as it accounts for the possibility that a repeated measure agrees by chance. Kappa values range from -1 to 1, where values ≤0 indicate no agreement other than that which would be expected by chance, and 1 is perfect agreement. Values above 0.6 are generally deemed to represent moderate agreement. Limitations of Cohen’s kappa are that it can underestimate agreement for rare outcomes, and that it requires the two raters to be independent.
Generalisability Generalisability is the extent to which the findings of a study can be applicable to other settings. It is also known as external validity. Generalisability requires internal validity as well as a judgement on whether the findings of a study are applicable to a particular group. In making such a judgement, you can consider factors such as the characteristics of the participants (including the demographic and clinical characteristics, as affected by the source population, response rate, inclusion criteria, etc.), the setting of the study, and the interventions or exposures studied. Threats to external validity, that may result in an incorrect generalisation, include restrictions within the original study (eligibility criteria), and pre-test/post-test effects (where cause-effect relationships within a study are only found when pre-tests or post-tests are also carried out). What refers to whether you measure what you intended to measure?Validity refers to how well a test measures what it is purported to measure.
When a test has the ability to measure what it is intended to measure it is said to be group of answer choices?Content validity is an important research methodology term that refers to how well a test measures the behavior for which it is intended. If the test does indeed measure this, then it is said to have content validity -- it measures what it is supposed to measure.
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