Delirium Of the NLG919

At each step, we checked whether the addition of the new variable made others insignificant, in which case, we dropped those variables from the model. The final model was obtained when no significant improvement could be achieved with the addition of new variables. Violation of model assumptions was checked in the final models. Colinearity was assessed through graphical exploration of explanatory variables, correlation tests, and variance inflation factors (VIF) in the final model. Independence was assessed by studying the spatial (correlograms) and temporal correlation (cross-correlations) of the model residuals. Multivariate results Similarly to the results obtained with multi-model selection, a combination of seasonal Verteporfin order factors, water conditions, and community composition remained in the final models for Akonolinga and Bankim (Appendix table 1). Firstly, the effect Tubulin of seasonality remained for Akonolinga after accounting for water parameters and biological factors. Secondly, regarding water conditions, pH had a significant positive effect on MU presence in Akonolinga, whereas in Bankim the negative effect of water flow was evident, with lotic ecosystems being the least positive, followed by lentic ones, which had significantly lower positivity than stagnant ecosystems. Finally, the effect of aquatic communities through total abundance was significant and inversely correlated learn more with MU in Akonolinga, while in Bankim Shannon's diversity showed a positive correlation with MU presence. Individual taxa that remained significant and inversely correlated with MU were Gastropoda, Decapoda, Hemiptera and Anura for Akonolinga; and Ephemeroptera, fish, Diptera and Anura for Bankim. The only taxon positively correlated with MU in the final model was Hirudinea in Akonolinga and Coleoptera for Bankim. In summary, the results obtained from multi-model selection and classical model selection procedures were qualitatively and quantitatively similar. Appendix table 1. Results of multivariate analyses for Akonolinga (12 months of sampling) and Bankim (4 months of sampling) DOI: http://dx.doi.org/10.7554/eLife.07616.011 Variable Akonolinga (n = 183) Bankim (n = 61) Effect Std. error p-value Effect Std. error p-value Model AIC 400.7 �C �C 182.7 �C �C Variance of random effect 0.20 �C �C 1.77 �C �C (Intercept) ?12.56 4.40