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Using diverse variables and protocols can be problematic in experimental studies because the variations in protocols between studies can affect the outcome of the experiments and thus their comparability [ 1, 9].
Contrary to our expectations, exercise/stretch did not show any correlation with the diverse variables, and relaxation was associated with a greater number of symptoms and worse physical functioning.
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For the modern biota, comprehensive environmental datasets exist, comprising diverse variables at fine spatial and temporal resolutions.
In addition, the majority of models consist of diverse variables, including laboratory profiles and BMI, which require additional blood assays or mathematical calculations (6– 10).
However, the analysis of the HT patients classified according to lipid levels revealed more significant associations between the polymorphisms and diverse variables.
With respect to socioeconomic status, it is notable that diverse variables indicative of sanitation conditions and widely recognized as important in diarrhea control [ 36, 40- 43] were associated in the descriptive analyses with the occurrence of the disease among Indigenous children but were not retained in the final multivariable model.
The TNM classification system has long been the accepted predictive tool for breast cancer and provides useful information for the clinical decision-making process in these patients; [ 20] however, this system is based solely on disease-related parameters and does not include diverse variables, including diagnostic methods, which may influence the outcome of patients.
In order to further confirm the above findings about the effects of HRT and to investigate associations between the diverse variables, correlation analyses of changes from baseline to 24 months in serum levels of TNF-α, IL-1Ra, IL-6, sIL-6R, OPG, IGF-1, ESR, and E2 and changes of BMD in the total hip and lumbar spine were sought.
Designs, data collection and data management procedures are relatively standard for the same type of survey (DHS and MICS); however, there are differences in dataset structures between DHS and MICS and within each of these types of surveys (e.g. diverse variables names for the same variable and/or different coding of the same variables).
Randomized studies make sense when it is feasible to limit the impact of diverse variables.
At the level of comprehension generally, the response latency is under the influence of diverse variables which are still in the road of investigation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com