Changes: Internal consistency

Latest revision as of 07:30, 17 June 2009

Statistics: Scientific method · Research methods · Experimental design · Undergraduate statistics courses · Statistical tests · Game theory · Decision theory

Main article: Test consistency

In statistics and research, internal consistency is a measure based on the correlations between different items on the same test (or the same subscale on a larger test). It measures whether several items that propose to measure the same general construct produce similar scores. For example, if a respondent expressed agreement with the statements "I like to ride bicycles" and "I've enjoyed riding bicycles in the past", and disagreement with the statement "I hate bicycles", this would be indicative of good internal consistency of the test.

Internal consistency is usually measured with Cronbach's alpha, a statistic calculated from the pairwise correlations between items. Internal consistency ranges between zero and one. A commonly-accepted rule of thumb is that an α of 0.6-0.7 indicates acceptable reliability, and 0.8 or higher indicates good reliability. High reliabilities (0.95 or higher) are not necessarily desirable, as this indicates that the items may be entirely redundant. The goal in designing a reliable instrument is for scores on similar items to be related (internally consistent), but for each to contribute some unique information as well.

External links

http://www.wilderdom.com/personality/L3-2EssentialsGoodPsychologicalTest.html

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-In [[statistics]] and [[research]], '''internal consistency''' is the coefficient of test scores.  Put more simply, internal consistency measures the consistency of results across items within a single test. One example of internal consistency in research might be a test of two questions.  The first statement says "You feel negatively about bicycles."  The second statement would say "You like to ride bicycles."  If a person agrees with the first and disagrees with the second, the test has internal consistency.
+In [[statistics]] and [[research]], '''internal consistency''' is a measure based on the [[correlation]]s between different items on the same test (or the same subscale on a larger test). It measures whether several items that propose to measure the same general construct produce similar scores. For example, if a respondent expressed agreement with the statements "I like to ride bicycles" and "I've enjoyed riding bicycles in the past", and disagreement with the statement "I hate bicycles", this would be indicative of good internal consistency of the test.
+Internal consistency is usually measured with [[Cronbach's alpha]], a statistic calculated from the pairwise correlations between items. Internal consistency ranges between zero and one. A commonly-accepted rule of thumb is that an α of 0.6-0.7 indicates acceptable reliability, and 0.8 or higher indicates good reliability. High reliabilities (0.95 or higher) are not necessarily desirable, as this indicates that the items may be entirely redundant. The goal in designing a reliable instrument is for scores on similar items to be related (internally consistent), but for each to contribute some unique information as well.
-== External links ==
+== See also ==
+* [[Cronbach's alpha]]
+* [[Reliability (statistics)]]
+* [[Test reliability]]
+== External links ==
 * http://www.wilderdom.com/personality/L3-2EssentialsGoodPsychologicalTest.html
+[[Category:Test construction]]
+<!--
+[[nl:Interne consistentie (statistiek)]]
+-->
+{{enWP|Internal consistency}}