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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).