China
Africa
Explore chapters and articles related to this topic
Measurement Models for Patient-Reported Outcomes and Other Health-Related Outcomes
Published in Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle, Structural Equation Modeling for Health and Medicine, 2021
Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle
Cronbach’s alpha (or coefficient alpha) is a routinely used measure of internal consistency in health and medicine that can be used to evaluate composite reliability of a measurement model [42]. The coefficient omega is another widely used measure of composite reliability. Cronbach’s alpha is calculated using observed item covariances and depends on the assumption of tau-equivalence. With tau-equivalence, all unstandardized factors loadings are equal (i.e. each indicator contributes equally to the construct). Omega is calculated using factor loadings and variance and relaxes the assumption of equal factor loadings. Thus, omega, given the more practical assumptions for CFA, is widely considered to be a more useful measure in the context of assessing composite reliability of a measurement model.
Work stress induced psychological disorders in construction
Published in Imriyas Kamardeen, Work Stress Induced Chronic Diseases in Construction, 2021
Moreover, constructs such as work–life conflict and job stress were measured by multiple items in the questionnaire. In order to ensure that the measurement items adequately represent the constructs, internal consistency and reliability tests were conducted with Cronbach’s alpha tests. Moreover, statistical means for the constructs were computed for use in further analyses. Table 2.4 depicts the results. To accept that a construct is reliable and the measurement items within a construct are internally consistent, the Cronbach’s α value must be higher than .70 (Tavakol and Dennick 2011). The constructs yielded alpha values of greater than the threshold.
Practical Considerations for Interpreting Change Following Brain Injury
Published in Mark R. Lovell, Ruben J. Echemendia, Jeffrey T. Barth, Michael W. Collins, Traumatic Brain Injury in Sports, 2020
Grant L. Iverson, Michael Gaetz
The internal consistency reliability of the scale was estimated using Cronbach’s alpha (α = 0.89). The split-half reliability was .88. The test was administered to all the athletes at the beginning of each season. The one-year test-retest reliability coefficients for 113 subjects were .24 (p = .011; Pearson) and .23 (p = .017; Spearman). The very low test-retest correlation after 12 months is probably due to the “state” nature of the assessment. Athletes are instructed to rate these symptoms based on the past 24 hours. This would obviously make the ratings highly susceptible to situational factors. The test-retest reliability is affected further by restriction in range and skewness in these score distributions.
Developing social skills and self-satisfaction of adults with intellectual disabilities through sports: a parental perspective
Published in International Journal of Developmental Disabilities, 2023
The value of Cronbach’s alpha coefficient lies between 0 to 1, where a value closer to 1 indicates a high reliability of the score, and a value closer to 0 indicates low reliability (Perrin 2020). It can be seen from Table 3 that the Cronbach's alpha coefficient obtained for the Likert scale was 0.743, which is greater than the recommended limit of 0.7. The high value of Cronbach's alpha reliability coefficient shows that the scale used in the present study was highly reliable and valid. Along with this, the value of the reliability coefficient in the study further indicates the presence of consistency in the responses of the respondents. Furthermore, Table 4 depicts the mean and standard deviation of the different variables taken in the reliability test. The variables all have nearly the same mean value, which again provides evidence of high reliable scores in the study.
Evidence-based-practice profile among physiotherapists: a cross-sectional survey in France
Published in European Journal of Physiotherapy, 2023
Arnaud Bruchard, Xavier Laurent, Pauline Raul, Germain Saniel, Grégory Visery, Vincent Fontanier, Nadège Lemeunier
We used a French translation of the EBP2 questionnaire, a questionnaire which has been validated and employed among health-related professionals [16,19,25–27]. Studies using this questionnaire assessed its internal reliability by the means of Cronbach’s alpha, either computed for the whole questionnaire or for each domain. Despite being almost exclusively used to estimate reliability, Cronbach’s alpha suffers from several limitations, underestimating the reliability of a test and overestimating the first factor saturation [33]. The paradox between the intense use of Cronbach’s alpha to assess internal reliability and its limits to do so accurately has been at the heart of intense debates among statisticians and psychologists [34–38]. As a result, reliability theory now suggests the use of several other reliability coefficients. In this context, we computed internal reliability estimates of the EBP2 from our dataset using the psych package in R [39]. These include Cronbach’s alpha [40], Beta which is the worst split-half reliability [41], McDonald’s hierarchical and total omegas [42], Guttman’s λ4 and λ6 [43]. Cronbach’s alpha values in our dataset (Supplementary Appendix 3) were similar comparable to those of previous studies. Complementary reliability coefficients (Supplementary Appendix 3) confirmed the reliability of the tool and its design, putting aside items falling into the ‘Other characteristics’ domain.
The Association of Child Abuse Experiences and Intolerance of Uncertainty in Young Adults
Published in Psychiatry, 2023
Ayşe Hatun Dirican, Ekin Doğa Kozak, Önder Kavakcı, Berna Sönmez
We analyzed the data using AMOS 24 and SPSS 25. Confirmatory factor analysis was performed to evaluate the measurement model and validity of the scales used in this study. Cronbach’s alpha values were calculated to test the scales’ reliability. Structural equation modeling (SEM) was implemented in AMOS by using maximum likelihood estimation to analyze the relationship between independent variables and dependent variable. SEM is a powerful statistical method combining path model with latent and observed variables (indicators; Anderson & Gerbing, 1988; Gürbüz, 2019; Hox & Bechger, 1998). It allows testing of interrelationships between a range of variables simultaneously (Porritt et al., 2015). In addition, SEM models estimate measurement errors explicitly for both independent and dependent variables (Novikova et al., 2013). To determine if the mean scores of the IU differed significantly by demographic groups, independent samples t-test and one-way analysis of variance (ANOVA) were conducted in SPSS.