First, we determined the number of exponentials to use by comparing the AIC between potential models and whether models converged when fitted through a Levenberg-Marquardt nonlinear least-squares method. Then, we determined the appropriate random-effects structure and heteroscedasticity correction for NLME modeling by assessing convergence, AIC, within-experiment and between-experiment heteroscedasticity for various combinations. Last, we added a linear dependence of (some of) the fixed effects to a dummy variable WT/Hacd1-KO and assessed the statistical significance of this addition with an ANOVA.

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