Similar to the models for SI change, we repeated modeling for these three variables alone and in combinations of two to better understand how glycine, alanine, and proline concentrations were related to sustained SI change.
First, we repeated models adjusting for the ratio of pesticide metabolite to creatinine level, instead of adjusting for creatinine.
In addition, we repeated models without adjusting for maternal serum POPs concentrations.
However, to date, the potential of repeated measures models for estimating DGE and IGE on survival time has not been investigated.
When data analyses were repeated (same models) for the two groups of unexposed children separately, the trends were the same but the results were not significant.
Initially we modeled the total coverage of the branch, using a Poisson distribution with mean λ under the variant and error models and in the repeat model (for representing the repeat copy number).
As a secondary analysis we also repeated the model for GHQ with the addition of a further fixed effect for pattern of missing values.
The GEE model is a repeated measures model for binary outcomes which accounts for the correlation between siblings.
Estimates are given as least squares means from the repeated measurements model (for sodium, glucose and lactate arithmetic mean and P-values from Kruskall Wallis test are given).
The process is repeated for model widths w min + 1 to w max - 1 (the longest model is always kept in the set of candidate models).
