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The dependent variable was therefore a dichotomous outcome trajectory variable: resilience (coded as "1") and non-resilience (coded as "2").
The two-way repeated measures ANOVA was used to analyse the effect of the intervention on the dependent variable resilience.
The model is appropriate for estimating the latent variable (resilience) and the item endorsability for responses scored in two or more categories.
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Associations between the independent variables (Resilience Scale, Mood Survey, Beck Hopelessness Scale and Perceived Stress Scale (emotional stress and stress control scores) and the dependent variables WC (cm) and BMI (kg/m) were examined by multiple linear regression analysis.
Among the independent variables, resilience was found to be positively associated with male gender and absence of parental mental disorder, and inversely associated with indigenous ethnic groups and childhood traumatic events.
Our model explained 59.5% of the variation in the dependent variable flood resilience index (R2 = .595 × 100 = 59.5%).
Lehner (2010) argues that, under variable environment, resilience to many environmental conditions is advantageous and selected for, and genetic robustness has evolved as a by-product of evolution of environmental robustness Yeast data also provide some important characteristics of quantitative genetic interactions relating to robustness.
We used GWR to explore the relationships between socioeconomic variables and resilience.
Our results were largely robust to different focal variables and resilience definitions.
The geographically weighted regression coefficient maps revealed the spatial pattern of the association of the variables with resilience.
The relationships between individual variables and resilience rank may not be as clear and straightforward as postulated in the hypotheses.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com