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We review these findings and integrate them into a model for multilevel regulation of AID expression and targeting in immunoglobulin and non-immunoglobulin loci.
The analysis has been performed using the MULTIPOLES (MULTIstate POpulation model for multiLEvel Systems) population dynamics model developed by Kupiszewski and Kupiszewska (1998).
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All of the analyses were performed with Stata software, version 13.0 for Windows, using the generalized linear latent and mixed model (gllamm) framework for multilevel analysis [ 14].
The model accounted for multilevel correlation of data from multiple animals within herds.
Hierarchical models account for multilevel dependencies, resulting in estimates that are more accurate than their nonhierarchical counterparts, provided that the hierarchical assumptions are valid.
We used the Mixed Model module of SPSS for multilevel models [ 45] to examine these models.
This said, our results are comparable with simulation results for multilevel regression models as reported by other researchers [ 11].
Regression models were estimated using STATA ver.11.1MP (for the pooled and country specific models) [30], and MLwiN 2.20 (for multilevel models) [31].
Since time was not a significant predictor in the individual growth model for PCS, no multilevel model for change was calculated for this health outcome.
For this multi-level analysis, the MLwiN software package for fitting multi-level models was used (version 2.02; Centre for Multilevel Modelling, Institute of Education, University of London, UK).
Multilevel modeling was conducted in MLwiN version 2.19 (Centre for Multilevel Modeling, University of Bristol, U.K).
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