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    Validity and Reliability in Research

    Validity

    Validity is the research measures what it intends to investigate. There are three types of validity:

    1. Construct validity – the extent to which inferences from a test’s scores accurately reflect the construct that the test claims to measure.
    2. Content validity – the extent to which inferences from a test’s scores adequately represent the content or conceptual domain that the test claims to measure
    3. Internal validity – in experiments, it is the extent to which extraneous variables have been controlled by the researcher so that any observed effects can be attributed solely to the treatment variable.

    Reliability

    In qualitative research, it is the extent to which other researchers would arrive at similar results if they studied the same case using exactly the same procedures as the first researcher.  In classical test theory, it refers to the amount of measurement error in the scores yielded by a test.

    Types of reliability

    a. Inter-observer reliability – it is the extent to which the scores assigned by one observer of events correlate with the scores assigned by another observer of the same events.
    b. Intra-observer- reliability – it is the extent to which an observer makes consistent recordings of observational variables while viewing a videotape or listening to an audiotape of an event on several occasions

    Strategies to achieve internal reliability

    1. Low inference descriptors – describes behavior on which it is easy for independent observers to agree.
    2. Multiple researchers/ participant researchers – the best way to guard against threats to internal reliability. However, this is quite expensive. The alternative is to enlist the aid of local informants to validate the interpretations of the ethnographer.
    3. Peer examination – this involves the corroboration by other researchers working in similar settings
    4. Mechanically recorded data – this strategy allows for the preservation of the primary data.
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