Analytical strategies for the marble burying test: avoiding impossible predictions and invalid p-values

BMC Research Notes

Table 1 Numeric results for different models

Analysis	VPA	MPEP	VPA × MPEP	GOF	AIC	P _model
Normal	0.055	0.009	0.178	<0.001	259	<0.001
Poisson	<0.001	<0.001	0.223	<0.001	256	<0.001
Quasi-Poisson	0.045	0.006	0.490	<0.001	NA	NA
Negative binomial	0.075	0.009	0.470	0.233	223	1.000
Wilcoxon
	All: 0.602	All: 0.002	NA	NA	NA	NA
	MPEP: 0.494	VPA: 0.021	NA	NA	NA	NA
	Vehicle: 0.138	Control: 0.044	NA	NA	NA	NA

P-values for main and interaction effects are displayed. Goodness-of-fit p-values (a small p-value indicates a poor fit), AIC values (lower is better), and model probabilities (higher is better) indicate that the negative binomial model is preferred. The nonparametric Wilcoxon tests give much larger p-values overall.

ISSN: 1756-0500