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The model error is estimated as the difference between the models given by the straight and curved paths.
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The resulting dipole locations are free to move outside of the prior distribution, although the model evidence of the result is a balance between the likelihood of the model given the data, and the (Kullback-Leibler) divergence between the posteriors and the priors (cf. the model complexity).
Statin use, age and gender were forced to remain in the model given demonstrated associations between these factors and dementia or Lp-PLA2 activity [ 18- 20].
To verify this, we conducted quantitative RT-PCR (qRT-PCR) analysis of the expression of a selection of genes in the rat kidney (see Additional file 4) and calculated correlations between fold changes of gene expression between the rat models given by qRT-PCR and the three microarray platforms.
However, the model gave good agreements between predictions by NEF and experiment results in all cases.
The model gives a relation between μa and μs' of the phantom and the measured effective photon path length.
The model gives a linear relationship between the time required to reach the desired breakthrough concentration and the bed height.
Model selection between the two models gives wrong results when P E T > P E S, meaning that the simplified model gives lower prediction error than the true model structure.
The likelihood ratio chi-square statistic tests the hypothesis of no difference between the null model given a specified distribution and the fitted prognostic model with p parameters [ 15].
It is difficult discriminating between models given that they all showed good specification and fit and satisfied relevant statistical assumptions.
Thus, the consistency between the two predictive models gives credence to the results of the current predictions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com