Title
Hierarchical models: What the data are really telling us,Used
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Generalized linear mixed models are commonly employed to tackle a wide variety of data analysis problems in a multitude of settings. In these data settings understanding the statistical results can be a bigger issue than generating the numbers from the analysis in the first place. Communicating the results of an analysis can be a challenge as at times there is not a clear picture of what is going on and one may see different results between a simple aggregate analysis and the results of a regression analysis. The goal of this monograph is to bridge this gap and develop tools for understanding this sort of data analysis. This document addresses 3 aims: to review statistical methods for the analysis of count data in hierarchical settings; to examine graphical methods for presenting findings and evaluating confounding; and to illustrate these methods with actual data.
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We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.
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