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To explore the bivariate and multivariate relations between fatty degeneration of the lumbar multifidus muscle (LMM) and LMM function among patients with low back pain (LBP).
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In a randomly selected derivation data set (60% of data), multivariate-adjusted relations between FAO estimates and GDD data were evaluated with final models and coefficients from the derivation data set presented in Supplemental Table 4.
We applied to multivariate phenotype based GWAS to relations between plasma lipid levels for an in-depth study.
Subsequently, using multivariate linear regression models, the relations between the relevant SeMaS characteristics and PAM scores (0 100) were investigated.
Multivariate logistic regression analyses were used to determine relations between probability of VOC occurrence relative to hydrogeologic and anthropogenic variables.
Multivariate linear regression models were calculated to identify independent relations between potential risk factors and variation of IMT.
Statistical relations between road characteristics and speed indicators were explored using multivariate classification methods and regression models.
We show relations between optimality of designs in univariate models and in their multivariate extensions.
This led us to explore relations between Pα and DTI fractional anisotropy by means of a multivariate penalized regression.
Cross-sectional relations between risk factors and LA size (both at year 5) were assessed by multivariate linear regression.
Relations between barriers and prescribing behaviour were assessed by means of Spearman rank correlation and multivariate regression modelling.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com