menu
{ "item_title" : "Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates", "item_author" : [" Jeffrey R. Wilson", "Elsa Vazquez-Arreola", "Chen "], "item_description" : "This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. ​", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/03/048/906/303048906X_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates|Jeffrey R. Wilson

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. ​


This item is Non-Returnable

Details

  • ISBN-13: 9783030489069
  • ISBN-10: 303048906X
  • Publisher: Springer
  • Publish Date: September 2021
  • Dimensions: 9.21 x 6.14 x 0.41 inches
  • Shipping Weight: 0.61 pounds
  • Page Count: 166

Related Categories

You May Also Like...

    1

BAM Customer Reviews