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Sectors with widely dispersed backward effects but with limited or no forward effects are mostly those that draw widely on domestic inputs but sell mainly to export markets or to tourists visiting Namibia.
Key manufacturing sectors with less widely dispersed backward effects are those that sell their products to a broad range of other sectors—hence the widely dispersed forward effects but whose main input from the domestic economy is the use of transportation and retail services to distribute their products.
Since we were most interested in the polygenic nature of these traits, we used a multiple logistic regression model with backward elimination to assess the joint effects of SNP genotypes on HLP phenotypes.
Multivariate analysis was done using logistic regression model with backward stepwise selection procedure to evaluate the effect of interactions between the different variables.
Frequencies and bivariate correlations were examined while a random-effects logistic regression model with backward elimination was used to determine correlates of childhood hunger.
Multivariate Cox regression models, with backward selection, were used to test the prognostic effect of p53 status after adjusting for other important prognostic variables.
In order to identify factors associated with mortality, Cox proportional hazard model with backward method was used to control for the effects of confounding variables.
Cox proportional hazards models with backward stepwise elimination were used to separately estimate the effects of different risk factors on the relative risk of time to HHS.
The independent effect of covariates on HRQoL was analysed with backward multiple linear regressions with entry at p < 0.05 and removal at p < 0.10.
The effect of covariates on hyponatremia was analyzed using logistic regression with backward elimination.
Binary logistic regression analysis was also performed, applying stepwise selection with backward elimination in order to identify independent risk factors and control confounding effects (variables mutually adjusted).
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