000			03057nam a2200313 i 4500
999			_c92 _d92
001			25039
003			OSt
005			20170213142114.0
008			100901t20102010ncua b 001 0 eng
010			_a2010459423
020			_a9781607642275 (pbk.)
020			_a1607642271 (pbk.)
035			_a(OCoLC)506277599
035			_a(OCoLC)506277599
040			_aDLC _beng _erda _cDLC _dSA$ _dYDXCP _dBDX _dS4S _dOCLCO _dOCLCF
042			_apcc
049			_aVXNB
050	0	0	_aR864 _b.A53 2010
245	0	0	_aAnalysis of observational health care data using SAS _c[edited by] Douglas E. Faries, Andrew C. Leon, Josep Maria Haro, Robert L. Obenchain.
260			_aCary, NC : _bSAS Institute, _c©2010.
300			_axiv, 436 pages _billustrations _c29 cm
500			_aLOCATED IN THE DESK RESERVE SPECIAL COLLECTIONS CABINET
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction 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.
520	8		_aAnnotation _bThis 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.
630	0	0	_aSAS (Computer file)
650		0	_aMedical records _xManagement _xData processing.
700	1		_aFaries, Douglas E. _eeditor of compilation.
710	2		_aSAS Institute.
942			_2lcc _cBook