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Table 2 S. cerevisiae versus C. glabrata logistic regression analyses

From: The determinants of gene order conservation in yeasts

    Multiple regression
  Simple regression Stepwise regression Estimate z-value Residual deviation P(>|χ|)
Null 853.06 (0) 855.07 2.535 25.310 853.07 -
Met 852.93 (-) -0.052 -0.692 852.94 -
Cex 852.35 (-) 0.05 0.526 852.22 -
Igd 833.09 (1) 837.09 -0.312 -4.172 832.48 <0.0001
Let 853.02 (-) 0.044 0.453 832.33 -
Rec 850.4 (-) -0.084 -0.935 830.95 -
Cre 845.2 (2) 835.1 -0.168 -2.08 827.16 <0.05
Pro 852.7 (-) -0.092 -0.995 826.22 -
  1. The first column lists the seven predictors contributing to the generalized models and the corresponding null model. The second column shows residual deviance (equivalent to the residual sum of squares in ordinary regression analyses) of a model with a single determinant. The third column describes a stepwise forward regression according to the Akaike criterion with insertion order in parenthesis. The last four columns list the results of a multiple regression model (estimates and z-values) and the corresponding Anova with terms added sequentially from met to pro (residual and χ2 test).