TY - JOUR
T1 - Coeficiente Alfa
T2 - The Resistance of a Classic
AU - Doval Diéguez, Eduardo
AU - Viladrich, C.
AU - Angulo-Brunet, A.
N1 - Publisher Copyright:
© 2023, Colegio Oficial de Psicologos Asturias. All rights reserved.
PY - 2023/2
Y1 - 2023/2
N2 - BACKGROUND: During the 20th century the alpha coefficient (α) was widely used in the estimation of the internal consistency reliability of test scores. After misuses were identified in the early 21st century alternatives became widespread, especially the omega coefficient (ω). Nowadays, α is re-emerging as an acceptable option for reliability estimation.METHOD: A review of the recent academic contributions, journal publication habits and recommendations from normative texts was carried out to identify good practices in estimation of internal consistency reliability.RESULTS: To guide the analysis, we propose a three-phase decision diagram, which includes item description, fit of the measurement model for the test, and choice of the reliability coefficient for test score(s). We also provide recommendations on the use of R, Jamovi, JASP, Mplus, SPSS and Stata software to perform the analysis.CONCLUSIONS: Both α and ω are suitable for items with approximately normal distributions and approximately unidimensional and congeneric measures without extreme factor loadings. When items show non-normal distributions, strong specific components, or correlated errors, variants of ω are more appropriate. Some require specific data gathering designs. On a practical level we recommend a critical approach when using the software.
AB - BACKGROUND: During the 20th century the alpha coefficient (α) was widely used in the estimation of the internal consistency reliability of test scores. After misuses were identified in the early 21st century alternatives became widespread, especially the omega coefficient (ω). Nowadays, α is re-emerging as an acceptable option for reliability estimation.METHOD: A review of the recent academic contributions, journal publication habits and recommendations from normative texts was carried out to identify good practices in estimation of internal consistency reliability.RESULTS: To guide the analysis, we propose a three-phase decision diagram, which includes item description, fit of the measurement model for the test, and choice of the reliability coefficient for test score(s). We also provide recommendations on the use of R, Jamovi, JASP, Mplus, SPSS and Stata software to perform the analysis.CONCLUSIONS: Both α and ω are suitable for items with approximately normal distributions and approximately unidimensional and congeneric measures without extreme factor loadings. When items show non-normal distributions, strong specific components, or correlated errors, variants of ω are more appropriate. Some require specific data gathering designs. On a practical level we recommend a critical approach when using the software.
KW - Cronbach’s alpha
KW - Internal consistency
KW - Omega
KW - Reliability
KW - Software
KW - Humans
KW - Psychometrics/methods
KW - Reproducibility of Results
KW - Surveys and Questionnaires
KW - Cronbach’s alpha
KW - Internal consistency
KW - Omega
KW - Reliability
KW - Software
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85146904754&partnerID=MN8TOARS
UR - http://www.scopus.com/inward/record.url?scp=85146904754&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/2cdb41e9-6e00-31a4-9ecd-4d59f5bc9f89/
U2 - https://doi.org/10.7334/psicothema2022.321
DO - https://doi.org/10.7334/psicothema2022.321
M3 - Article
C2 - 36695846
SN - 0214-9915
VL - 35
SP - 5
EP - 20
JO - Psicothema
JF - Psicothema
IS - 1
ER -