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. 2019 Mar 4;145(3):1168–1177. doi: 10.1121/1.5091776

TABLE III.

Hierarchical GLMM: To reach the appropriate complexity of model, we first modeled correct/incorrect answers as a function of each mouse as a fixed effect (row 1), then added the generalization type (as in Fig. 2) as a fixed effect (row 2), and finally modeled generalization type as a fixed effect nested within each mouse as a random effect (row 3). Since the final model had the best fit, it was used in all reported analyses related to the GLMM.

DF χ2 DFχ2 Pr(>χ2)
Mouse 2
Mouse + Type 6 2534.46 4 ≪ 0.001
Type | Mouse 20 407.22 14 ≪ 0.001