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The models use Maximum Penalized Likelihood Estimation [11, 12], which is a variational approach.
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Models 2 through 4 are full models using maximum likelihood estimations (MLE) with unstructured covariance structure.
Convulsion was induced in different animal models using maximum electric shock test [42, 43].
We fitted the models using maximum likelihood.
We used Mplus 6.1 (Muthén and Muthén 2007) to fit the models using maximum likelihood (ML) estimation.
All regression models used maximum likelihood estimates and we controlled for autocorrelation by correcting for autoregressive effects.
To achieve a more reliable P value, we fitted the models using maximum likelihood (rather than restricted maximum likelihood, Bolker et al. 2009).
To explore the relationships among multiple schizophrenia measures, Pearson correlation coefficients were calculated, and structural equation modeling was used to build path models using maximum likelihood estimation.
The R package lme4 (Bolker, 2013) was used to fit linear mixed models using maximum likelihood to model expression as a function of genetic interactions.
Fourthly, to investigate the effect of the intervention on the secondary outcomes, we performed linear mixed models using maximum likelihood estimation.
To allow for within participant correlation in the four day food diary, the diet outcome regression analyses were fitted with random intercept models using maximum likelihood estimation.
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