Title
Hierarchical models: What the data are really telling us,Used
Sold by Ergodebooks, an authorized reseller.
Returns accepted within 30 days | support@ergodebooks.com
Shipping Information
- Free Standard Shipping — United States only
- Processing Time: 1–3 business days
- Estimated Delivery: 3–5 business days after dispatch
- Double-boxed, fully insured & discreetly packaged
- Tracking number sent via email once dispatched
- Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund
Returns accepted within 30 days of delivery.
Damaged or Defective Item
Free return shipping + replacement or full refund
Wrong Item Received
Free return shipping + replacement or full refund
Change of Mind
Return shipping at customer's expense · 25% restocking fee applies
Payment Option
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.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.