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Table 3 The output (parameter estimates, standard errors and p-values) of the mixed effect logistic regression (see Table  1 for definitions)

From: Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin

Variable Estimate Std. error Exp(est) P-value Δ AIC
Intercept 2.30 0.84   0.006  
Area shrubi 1 vs. 0* 1.05 0.27 2.86 <0.001 14
Area shrubi 2 vs. 0* 0.85 0.23 2.35 <0.001
Area shrubi 3 vs. 0* 0.79 0.23 2.21 <0.001
Meanarea_ p 0.45 0.12 1.40 <0.001 9
Meanarea _p2 −0.11 0.03 <0.001
RHmean Oct-Mar 1.21 0.13 3.34 <0.001 88
BlackFrdays 0.92 0.16 2.50 <0.001 55
SnoStartDays 1.17 0.20 3.23 <0.001 34
NuFarms 2.67 0.31 2.27 <0.001 94
NuFarms2 −1.85 0.21 <0.001
Red deer 1.28 0.22 3.59 <0.001 29
Pasture −1.36 0.30 0.25 <0.001 18
RRSum May −0.18 0.15 0.59 0.224 46
RRSu m May 2 −0.35 0.06 <0.001
RRSum Mar −0.40 0.14 0.67 0.004 6
TIncr + 5 < Days Jun −1.11 0.21 0.40 <0.001 27
TIncr + 5 < Day s Jun 2 0.19 0.04 <0.001
TMeanSD Apr 0.43 0.22 1.93 0.047 5
TMeanS D Apr 2 0.22 0.08 0.004
TDecr ÷ 5 < DaysJan − Dec 0.22 0.10 1.25 0.035 2
  1. Δ AIC denotes the change in AIC level obtained if excluding the relevant variable from the selected model. The continuous variables are scaled (before taking polynomials) to mean zero and variance one. The factor by which the odds of positive outcome are increased for each one-unit change in the variables are represented by the computed exp (estimates). For the polynomials the odds ratio is calculated only for an increase of one standard deviation from mean. ICC (Intraclass correlation; ratio of the variance between subjects over the total variance) for municipality was 0.33 and ICC for timespan was 0.36. The “Area shrubi” variable was categorized (in 4 equal parts defined by quartiles) to capture the nonlinear relationship (at logit-scale) with the outcome. The variables Area shrubi, BlackFrDays and RRSumMar represent the rough grazing level.