Behavior Mode

Behavior Pattern Measure

Most Parsimonious Model

Full Model


Standardized Input Parameters
Coefficient (Standard Error)

Fit Statistics

Fit Statistics


p
_{
r}

p
_{
i}

start
_{
r}

start
_{
i}

λ
_{
out}

MIC
_{
s}

η
_{
LI}

AIC

BIC

Adj. R^{2}

AIC

BIC

Adj. R^{2}


Decreasing

Inflection Time^{4}

−3.2e14 (4.5e13)
 
3.4e14 (4.6e13)
  
2.2e14 (4e13)
 
14,373

14,389

0.301

14,367

14,460

0.387

Peaked

Max Time

310.43 (31.71)

−226.84 (30.33)

− 282.98 (31.6)

115.5 (30.3)

− 102.45 (30.31)

270.5 (31.02)

61.23 (30.63)

10,014

10,054

0.348

9853

9982

0.512

 The example mathematical model was for the proportion of tetracyclineresistant 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. For the inflection time model, the dependent variable was inflection time raised to the fourth power. 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 R^{2} are given for the most parsimonious and the full model