Cronbach's alpha is a measure of internal consistency, which is used to determine if multiple survey questions designed to measure a single underlying construct produce reliable and consistent results. The researcher administered a 9-question survey measuring employee safety to 101 workers and calculated a Cronbach's alpha of .721 based on responses from 95 workers, indicating high internal consistency among the survey questions. Cronbach's alpha values range from 0 to 1, with higher values indicating stronger internal consistency among survey questions that are intended to measure the same latent variable.
Cronbach's alpha meaning, thumb rules, procedure using SPSS and interpretation
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Cronbach's Alpha (α)
Cronbach’s alpha, α (or coefcient alpha), developed by Lee Cronbach in 1951, measures
reliability, or internal consistency.“Reliability” is how well a test measures what it should. For
example, a company might give a job satisfaction survey to their employees. High reliability
means it measures job satisfaction, while low reliability means it measures something else (or
possibly nothing at all).
Alpha is an important concept in the evaluation of assessments and questionnaires.( Mohsen
Tavakol, Reg Dennick
Cronbach's alpha is the most common measure of internal consistency ("reliability"). It is most
commonly used when you have multiple Likert questions in a survey/questionnaire that form a
scale and you wish to determine if the scale is reliable.
Cronbach’s alpha tests to see if multiple-question Likert scale surveys are reliable. These
questions measure latent variables—hidden or unobservable variables like: a person’s
conscientiousness, neurosis or openness. These are very difcult to measure in real life.
Cronbach’s alpha will tell you if the test you have designed is accurately measuring the variable
of interest.
Example
A researcher has devised a nine-question questionnaire to measure how safe people feel at work
at an industrial complex. Each question was a 5-point Likert item from "strongly disagree" to
"strongly agree". In order to understand whether the questions in this questionnaire all reliably
measure the same latent variable (feeling of safety) (so a Likert scale could be constructed), a
Cronbach's alpha was run on a sample size of 101 workers.
101 surveys were available for this analysis. Because many respondents answered that they did
not complete the entire survey, they were unable to provide answers to the provider-specific
questions.
Of the 101 surveys taken, 95 respondents completed the provider questions. The six provider-
specific questions were appropriately tested using Cronbach’s Alpha.
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Results of Reliability Testing Using the 95 completed surveys to assess the internal validity of
the provider questions.
. In SPSS, the steps are: Step
1: Click “Analyze, ” then click “Scale” and then click “Reliability Analysis.”
2: Transfer your variables (q1 to q5) into “Items, ”. The model default should be set as
“Alpha.”
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3: Click “Statistics” in the dialog box.
4: Select “Item, ”“Scale, ” and “Scale if item deleted” in the box description. Choose
“Correlation” in the inter-item box.
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5: Click “Continue” and then click “OK”
Out Put window
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A Cronbach’s Alpha measure of .721 was obtained. Cronbach's alpha, which indicates a high
level of internal consistency for our scale with this specific sample. We conclude, therefore, that
the internal reliability of the survey is sound.
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Note; A high level for alpha may indicat that the items in the test are highly correlated. However,
α is also sensitive to the number of items in a test. A larger number of items can result in a larger
α, and a smaller number of items in a smaller α.
If alpha is high, this may mean redundant questions (i.e. they’re asking the same thing). A low
value for alpha may mean that there aren’t enough questions on the test. Adding more relevant
items to the test can increase alpha. Poor interrelatedness between test questions can also cause
low values, so can measuring more than one latent variable.
References
Lund Research Ltd, 2018, Cronbach's Alpha (α) using SPSS Statistics
Mohsen Tavakol et al. 2011, Making sense of Cronbach’s alpha, International Journal of Medical
Education. Editorial ISSN: 2042-6372 DOI: 10.5116/ijme.4dfb.8dfd 53
http://creativecommons.org/licenses/by/3.0 Tavakol, Reg Dennick
Kyra Maples, 2015, SurveyVitals Anesthesia Survey Undergoes Cronbach’s Alpha Analysis