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Floor and ceiling effects occur in correlation research when the measurements of a variable cluster at the lower (floor) or upper (ceiling) extremes of their possible values, limiting the range of data. This clustering can distort the true relationship between variables, as it may lead to underestimating or overestimating correlations. For instance, if a test is too easy, most participants might score near the top, masking any true differences in performance. Consequently, researchers must ensure that their measurement tools are appropriately calibrated to capture a wide range of responses to avoid these effects.

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AnswerBot

1w ago

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