Showing posts with label coefficient alpha. Show all posts
Showing posts with label coefficient alpha. Show all posts

Friday, May 7, 2021

Alpha in Research & Statistics

 

In research, alpha is the probability of rejecting a true null hypothesis. 

In testing, alpha also refers to a measure of internal consistency—see Cronbach’s coefficient alpha.

Alpha waves are brain waves that can be measured on an electroencephalogram (EEG). Alpha waves are associated with daydreaming, meditating, and mindfulness.

Applied Statistics Concepts for Counselors on   AMAZON or   GOOGLE

Please check out my website   www.suttong.com

   and see my books on   AMAZON       or  GOOGLE STORE

Also, consider connecting with me on    FACEBOOK   Geoff W. Sutton    

   TWITTER  @Geoff.W.Sutton    

You can read many published articles at no charge:

  Academia   Geoff W Sutton     ResearchGate   Geoffrey W Sutton 




Please check out my website   www.suttong.com

   and see my books on   AMAZON       or  GOOGLE STORE

Also, consider connecting with me on    FACEBOOK   Geoff W. Sutton    

   TWITTER  @Geoff.W.Sutton    

You can read many published articles at no charge:

  Academia   Geoff W Sutton     ResearchGate   Geoffrey W Sutton 

Monday, April 26, 2021

Coefficient Alpha or Cronbach's Alpha

 Coefficient Alpha (also called "alpha") is a statistical value indicating the degree of internal consistency of items in a multiple-item scale like survey items or Likert-type scales.

Internal consistency is one measure of reliability for scores from scales, measures, and survey items.

The alpha statistic was developed by Lee Cronbach in 1951 thus it is also called Cronbach's alpha. In research reports, you may just see the Greek lower case letter alpha, α.


The procedure to calculate alpha can be found in SPSS under Analyze > Scale > Reliabilty.

For research purposes, scales with alpha levels equal to or above alpha = .70 are acceptable. The best scales have values of alpha = .9 or higher.

The alpha method works best to evaluate unidimensional measures. If there are two or more dimensions in a set of items, the alpha value will be lower so, when alpha values are low, consider which item or items do not support the primary dimension.

Cite this Post

Sutton, G.W. (2021, April 26). Coefficient Alpha or Cronbach’s Alpha. Retrieved from https://statistics.suttong.com/2021/04/coefficient-alpha-or-cronbachs-alpha.html


Learn more about statistics in Applied Statistics Concepts for Counselors on AMAZON   or   GOOGLE








Learn more about surveys and statistics in Creating Surveys on    AMAZON or    GOOGLE












Please check out my website   www.suttong.com

   and see my books on   AMAZON       or  GOOGLE STORE

Also, consider connecting with me on    FACEBOOK   Geoff W. Sutton    

   TWITTER  @Geoff.W.Sutton    

You can read many published articles at no charge:

  Academia   Geoff W Sutton     ResearchGate   Geoffrey W Sutton 

Saturday, October 28, 2017

HOPE - How to measure hope








The Adult Hope Scale developed by C. R. Snyder of the University of Kansas is an easy to use measure of hope. The original scale has 12-items, which measure two dimensions of hope based on hope theory. Four measure agency and four measure pathways--the other four are distractors.


The agency concept measures the capacity to focus energy on a goal. The pathways concept assesses plans to achieve goals. In recent studies, the four distraction items are often dropped leaving 8-items. Researchers often use the total score for the 8-items as a measure of trait (aka dispositional) hope.




I have also included a Spanish language measure of hope in this post.

Here's the text we (Sutton et al., 2018) used to refer to the scale along with our findings.


The items used a response format of 1 = definitely false to 8 = definitely true. A sample item is, “I meet the goals I set for myself.” Snyder et al. (1991) reported alphas between .79 and .95 in four samples. 
In our two studies, the alpha reliability values were .82 and  .95.

As you might expect, hope is positively correlated with well-being, which provides some evidence supporting validity. Hope was significantly correlated with the Schwartz Outcome Scale in both studies (.64, .76) and with the Theistic Spiritual Outcome Scale in study 2 (.72).

Using the Hope Scale

Counselors and psychotherapists may consider the scale in assessment of clients because it strongly predicts satisfaction with therapy and patient well-being, which are used as outcome measures as noted above (See Sutton et al., 2018)

Researchers may want to use hope in a variety of surveys looking at characteristics of populations. The reliability values of the items vary with the study yet indicate an overall consistency in many contexts.

The 8-item Scale

LINK TO COPY OF THE ADULT HOPE SCALE (also called The Trait Hope Scale)


Learn more about Hope Theory

Learn more about adding scales like Hope when Creating Surveys
Available from AMAZON





Applied Statistics: Concepts for Counselors

Available from AMAZON















Resource Link:  A – Z Test Index


La Esperanza

A Spanish hope scale (Escala de Esperanza de Herth) is also available. An article suggests adequate psychometric properties for a 28-item version (Uribe, Bardales, & Herth, 2012).

Read more about hope in Chapter 5 of 
Living Well










References

Snyder, C. R., Harris, C., Anderson, J. R., Holleran, S. A., Irving, L. M., Sigmon, S. T., Yoshinoba, L., Gibb, J., Langelle, C., & Harney, P. (1991). The will and the ways: Development and validation of an individual-differences measure of hope. Journal of Personality and Social Psychology, 60, 570-585. doi:10.1037/0022-3514.60.4.570

Snyder, C. R., Parenteau, S. C., Shorey, H. S., Kahle, K. E., & Berg, C. (2002). Hope as the underlying process in the psychotherapeutic change process. International Gestalt Journal, 25,11-29.

Sutton, G. W., Kelly, H., Worthington, E. L. Jr., Griffin, B. J., & Dinwiddie, C. (2018) Satisfaction with Christian psychotherapy and well-being: Contributions of hope, personality, and spirituality. Spirituality in Clinical Practice, 5 (1), 8-24. doi: 10.1037/scp0000145 Academia Link    ResearchGate Link

Uribe, P. M., Bardales, M.C., & Herth, K. (2012). Propiedades psicométricas de la Escala de Esperanza de Herth en español. RIDEP, 33, 127-145. (aidep.org)

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My Books  AMAZON          and             GOOGLE STORE


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Articles: Academia  Geoff W Sutton   ResearchGate  Geoffrey W Sutton 

 


Wednesday, July 19, 2017

Understanding the Reliability of Educational and Psychological Tests


Why aren't tests reliable?

The reason tests are not reliable is that reliability is a property of the interpretation of scores not the tests themselves.
 

This isn't a matter of semantics.

Think about it this way.

Give all the students in one school an achievement test. The test items don't change so they appear stable, consistent, and reliable. However, when publishers report reliability values, they calculate the reliability statistics based on scores. Scores vary from one administration to another. If you ever took a test twice and got a different score, you know what I mean. Individuals change from day to day. And we change from year to year. Also, even a representative sample of students for a nation can be different each year.


Every time we calculate a reliability statistic, the statistic is slightly different.

Reliability values vary with the sample.

Reliability values vary with the method of calculation.

Reliability values also vary with the method used for calculation. You can get high reliability values using coefficient alpha with scores from a one-time administration. This method is common in research articles. But you will see different values from the same research team in different samples in the same article.


If we use a split-half method, which usually calculates reliability based on a correlation between two halves of one test, then we can get a reliability value based on one administration. But that's only half a test! Researchers use the Spearman-Brown formula to correct for the shortened half-test problem- but that's just an estimate of what the full test could be.


There's also a test-retest reliability method. Give a test one time, wait awhile- maybe a week or several weeks, then retest. That gives you an estimate of stability. But if you have a good memory, you can score higher on the second test on some tests like intelligence and achievement.


By now you get the point. Any one test can be associated with a lot of reliability values. The reliability problem is not just about tests. The problem can be understanding that tests do not have one reliability value. As with many things in science, there are many variables to consider when answering a question.

Reputable test publishers include reliability values in their test manuals. Teachers, Counselors, Psychologists, and other users ought to know about test score reliability.

Learn more assessment and statistical concepts in


Applied Statistics: Concepts for Counselors 

AMAZON BOOKS




Learn more about assessment and statistics at the Applied Statistics website


Learn more about Creating Surveys




Quick Notes on Test Reliability

Reliability is a property of scores not tests.

Reliability may mean stability of scores over time.

Reliability may mean how consistently test questions measure whatever the test measures.

Reliable test scores in one culture do not mean they will be reliable in another culture.

Reliable test scores do not guarantee the score are valid - but reliability places a limit on validity.

Reliability statistical concepts apply to tests, quizzes, polls, surveys...sets of questions yielding numerical scores.



Note: This is a re-posting of a post to this new blog. 

Links to Connections

My Page    www.suttong.com

  

My Books  AMAZON          and             GOOGLE STORE

 

FOLLOW   FACEBOOK   Geoff W. Sutton   TWITTER  @Geoff.W.Sutton

 

PINTEREST  www.pinterest.com/GeoffWSutton

 

Articles: Academia   Geoff W Sutton   ResearchGate   Geoffrey W Sutton 

 

 



Identity Salience Questionnaire (ISQ)

  Assessment name: Identity Salience Questionnaire (ISQ) Scale overview: The Identity Salience Questionnaire (ISQ) is a 6-item self-repor...