Analysis of observational health care data using SAS

This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is suf...

Full description

Bibliographic Details
Main Author: Faries, Douglas E.
Other Authors: Leon, Andrew C., Haro, Josep Maria, Obenchain, Robert L.
Format: eBook
Language:English
Published: Cary, NC SAS Institute 2010
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
LEADER 03799nmm a2200505 u 4500
001 EB001908443
003 EBX01000000000000001071345
005 00000000000000.0
007 cr|||||||||||||||||||||
008 210123 ||| eng
020 |a 160764424X 
020 |a 9781607644248 
050 4 |a R864 
100 1 |a Faries, Douglas E. 
245 0 0 |a Analysis of observational health care data using SAS  |c [edited by] Douglas E. Faries, Andrew C. Leon, Josep Maria Haro, Robert L. Obenchain 
260 |a Cary, NC  |b SAS Institute  |c 2010 
300 |a xiv, 436 pages  |b illustrations 
505 0 |a Introduction to observational studies -- Propensity score stratification and regression -- Propensity score matching for estimating treatment effects -- Doubly robust estimation of treatment effects -- Propensity scoring with missing values -- Instrumental variable method for addressing selection bias -- Local control approach using JMP -- A two-stage longitudinal propensity adjustment for analysis of observational data -- Analysis of longitudinal observational data using marginal structural models -- Structural nested models -- Regression models on longitudinal propensity scores -- Good research practices for the conduct of observational database studies -- Dose-response safety analyses using large health care databases -- Costs and cost-effectiveness analysis using propensity score bin bootstrapping -- Incremental net benefit -- Cost and cost-effectiveness analysis with censored data -- Addressing measurement and sponsor biases in observational research -- Sample size calculation for observational studies 
505 0 |a Includes bibliographical references and index 
653 |a Medical records / Management / fast 
653 |a Medical & Biomedical Informatics / hilcc 
653 |a Medical records / Management / Data processing 
653 |a SAS (Computer file) / http://id.loc.gov/authorities/names/n88028236 
653 |a Medicine / hilcc 
653 |a Dossiers médicaux / Gestion / Informatique 
653 |a Medical records / Management / Data processing / fast 
653 |a Medical records / Management / http://id.loc.gov/authorities/subjects/sh85083015 
653 |a Health & Biological Sciences / hilcc 
653 |a SAS (Computer file) / fast 
653 |a MEDICAL / Medical History & Records / bisacsh 
653 |a Dossiers médicaux / Gestion 
700 1 |a Leon, Andrew C. 
700 1 |a Haro, Josep Maria 
700 1 |a Obenchain, Robert L. 
041 0 7 |a eng  |2 ISO 639-2 
989 |b OREILLY  |a O'Reilly 
776 |z 9781607644248 
776 |z 160764424X 
776 |z 9781607642275 
776 |z 1607642271 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781607642275/?ar  |x Verlag  |3 Volltext 
082 0 |a 651.5/04261 
082 0 |a 658 
082 0 |a 500 
520 |a This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data.This book is part of the SAS Press program