Title: Menopause Rating Scale (MRS) in the Malay language- Translation and Validation in a
Multiethnic Population of Selangor, Malaysia
Version: 2 Date: 31 May 2022
Reviewer:  Abdullah Alamer
Reviewer's report:
I have read the paper titled "Menopause Rating Scale (MRS) in Bahasa Melayu language-
Translation and Validation in a Multiethnic Population of Malaysia" which focused on validating
The menopause Rating Scale (MRS).
I have little knowledge about the literature on the topic; however, I have a good understanding
of the statistical analyses and my comments will be in that area only.
Generally speaking,  the analysis scheme the authors used are questionable and a significant
improvement is needed. Following are the major points:
- Information about the original MRS is not clear. For example, how many dimensions the
original scale has postulated?  What is the number of items?  Were there any updates on the
scale since 2000?
- It is not clear why authors have used EFA since they have a hypothesized factor structure of the
scale.  It is only a translation so why would they conduct the EFA?  I suggest skipping this step.
- The translation in the appendix should be followed by the English version.
- The reporting of the values does not follow the best practices. For example, Table 2 should
have the skewness and kurtosis, instead of Scale variance if item deleted Corrected Item-
Total Correlation Squared multiple correlations Cronbach's alpha if item deleted as they are
unnecessary and should be removed.
- The same is true with Table 3. Please see how other papers report such findings.
- The EFA actually reads like a two-factor solution is appropriate following the eigenvalue above
1. This is one of the problems of using EFA when the researchers have a factor structure a priori.
- CFA has resulted in a questionable solution with RMSEA .12 and TLI below .90. Also
factor correlation was rather high (.88 between Somatic and Urogenital) which distract from
discriminant validity.
- The factor loadings are not the standardized ones (possibly you have reported the
unstandardized ones). This practice does not follow the field.
- The presentation of the CFA (the figure) is rather unprofessional.  Was the diagram drawn by
MS Word?? What software do the authors use to get the CFA? Why not just use the output of
that software?
- Given these issues, I highly recommend the authors revise their analytical scheme and confirm
their measure based on previously established measurement models. Recent research suggests
using the newly developed method, exploratory structural equation modeling (ESEM). ESEM
has been developed as an improved method that overcomes the limitations of EFA and CFA
and integrates the best of the two worlds  (Alamer & Marsh 2022; Marsh et al., 2009; Morin
et al., 2020). I highly recommend this method and below you can find useful resources for this
powerful confirmatory analysis.
Good luck!
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References
Alamer, A., & Marsh, H. (2022). Exploratory structural equation modeling in second language
research: An applied example using the dualistic model of passion. Studies in Second Language
Acquisition. 10.1017/S0272263121000863.
Marsh, H., Muthén, B., Asparouhov, T., Lüdtke, O., Robitzsch, A., Morin, A., & Trautwein,
U. (2009). Exploratory structural equation modeling, integrating CFA and EFA: Application to
students’ evaluations of university teaching. Structural Equation Modeling: A Multidisciplinary
Journal, 16(3), 439–476.
10.1080/10705510903008220.
Morin, A., Myers, N., & Lee, S. (2020). Modern factor analytic techniques: Bifactor models,
exploratory structural equation modeling (ESEM) and bifactor-ESEM. In
G. Tenenbaum, & R. C. Eklund (Eds.), Handbook of Sport Psychology (4th Edition). UK: Wiley.