Expanding behavior pattern sensitivity analysis with model selection and survival analysis

BMC Veterinary Research

Table 3 Linear regression models for proportion-resistant inflection and maximum levels of decreasing and peaked behaviors, respectively

Behavior Mode	Behavior Pattern Measure	Most Parsimonious Model													Full Model
		Standardized Input Parameters Coefficient (Standard Error)										Fit Statistics			Fit Statistics
		p _r	start _r	λ _in	λ _out	log₁₀(β_sr)	MIC _s		δ	V _LI	η _LI	AIC	BIC	Adj. R²	AIC	BIC	Adj. R²
Decreasing	Inflection Level	0.091 (0.002)		−0.031 (0.003)			MIC _s	−0.007 (0.005)	−0.02 (0.004)	− 0.011 (0.002)	− 0.011 (0.002)	−800	−767	0.885	− 758	−664	0.869
							MIC _s ²	0.008 (0.003)
							MIC _s ³	−0.006 (0.002)
Peaked	Max Level	0.086 (0.003)	0.022 (0.003)	−0.036 (0.003)	0.02 (0.002)	0.009 (0.002)	MIC _s	−0.081 (0.003)	−0.021 (0.002)	− 0.022 (0.002)	−0.018 (0.002)	− 1706	− 1653	0.807	− 1597	−1468	0.775
Peaked	Max Level	0.086 (0.003)	0.022 (0.003)	−0.036 (0.003)	0.02 (0.002)	0.009 (0.002)	MIC _s ²	0.032 (0.003)	−0.021 (0.002)	− 0.022 (0.002)	−0.018 (0.002)	− 1706	− 1653	0.807	− 1597	−1468	0.775
Peaked	Relative Max Level	0.06 (0.003)	−0.07 (0.003)	−0.043 (0.003)	0.02 (0.003)		−0.02 (0.003)		−0.068 (0.003)	− 0.022 (0.003)	−0.021 (0.003)	− 1685	− 1641	0.734	− 1709	− 1585	0.752

The example mathematical model was for the proportion of tetracycline-resistant enteric Escherichia coli in a beef steer during and after administration of oral chlortetracycline. A separate linear regression model was built for each behavior pattern measure of each behavior mode. The behavior pattern measure was the dependent variable in the linear regression models. Inflection points occurred during chlortetracycline administration in 65% of decreasing behavior simulations. Simulations that did not have an inflection point were excluded from the inflection level model. A maximum proportion resistant during chlortetracycline administration could be calculated for all peaked behavior simulations. Coefficients and standard errors are listed for the standardized parameters that were included in each most parsimonious linear regression model. Full model refers to a linear regression model including all the parameters listed in Table 6 as independent variables. Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and adjusted R² are given for the most parsimonious and the full model

ISSN: 1746-6148