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Scale Reliability and Validity (A measure can be valid but not reliable…
Scale Reliability and Validity
A measure can be valid but not reliable and a measure can by reliable but not valid.
You must test the scales to ensure that: these scales indeed measure the unobservable construct that we wanted to measure (i.e., the scales are “valid”), and (2) they measure the intended construct consistently and precisely (i.e., the scales are “reliable”).
Reliability is the degree to which the measure of a construct is consistent or dependable.
Reliability implies consistency but not accuracy.
Inter-rater reliability, also called inter-observer reliability, is a measure of consistency between two or more independent raters (observers) of the same construct.
Test-retest reliability is a measure of consistency between two measurements of the same construct administered to the same sample at two different points in time.
Split-half reliability is a measure of consistency between two halves of a construct measure.
Internal consistency reliability is a measure of consistency between different items of the same construct.
Validity
Validity is sometimes called construct validity
Validity refers to the extent to which a measure adequately represents the underlying construct that it is supposed to measure.
Translational validity also called representational validity is Theoretical assessment of validity focuses on how well the idea of a theoretical construct is translated into or represented in an operational measure.
Criterion-related validity included four sub-types: Convergent, discriminate, concurrent and predictive validity.
Face validity refers to whether an indicator seems to be a reasonable measure of its underlying construct “on its face”.
Content validity is an assessment of how well a set of scale items matches with the relevant content domain of the construct that it is trying to measure.
Discriminant validity refers to the degree to which a measure does not measure other constructs that it is not supposed to measure.
Concurrent validity examines how well one measure relates to other concrete criterion that is presumed to occur simultaneously.
Theory of Measurement
Theory of Measurement is a psychometric theory that examines how masurement works, what it measures. and what it does not measure.
Two type of mesurment errors are: random eand systematic error.
Random error is the error that can be attributed to a set of unknown and uncontrollable external factors that randomly influence some observations but not others.
Systematic error is an error that is introduced by factors that systematically affect all observations of a construct across an entire sample in a systematic manner.
An Integrated Approach to Measurement Validation
In order to have a complete and adequate assessment of validity must include both theoretical and empirical approaches.
Theoretical Assessment include conceptualize constructs, create/select indicators, q-sort for item refinement/dropping and examine face and content validity.
Empirical Assessment includes; Collect pilot test data, factor analysis for convergent/ discriminate validity, eamine reliability and scale dimensional. Examine predictive validity, validate mesures.
This elaborate multi-stage process is needed to ensure that measurement scales used in our research meets the expected norms of scientific research