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000733818 020__ $$a9783319185361$$qelectronic book
000733818 020__ $$a3319185365$$qelectronic book
000733818 020__ $$z9783319185354
000733818 0247_ $$a10.1007/978-3-319-18536-1$$2doi
000733818 035__ $$aSP(OCoLC)ocn919611846
000733818 035__ $$aSP(OCoLC)919611846
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000733818 049__ $$aISEA
000733818 050_4 $$aRA652.2.P82
000733818 08204 $$a614.407/27$$223
000733818 24500 $$aInnovative statistical methods for public health data4h[electronic resource] /$$cDing-Geng (Din) Chen, Jeffrey Wilson, editors.$$h[electronic resource]
000733818 264_1 $$aCham ;$$aNew York :$$bSpringer,$$c[2015]
000733818 264_4 $$c©2015
000733818 300__ $$a1 online resource.
000733818 336__ $$atext$$btxt$$2rdacontent
000733818 337__ $$acomputer$$bc$$2rdamedia
000733818 338__ $$aonline resource$$bcr$$2rdacarrier
000733818 4901_ $$aICSA book series in statistics,$$x2199-0980
000733818 504__ $$aInclude bibliographical references and index.
000733818 5050_ $$aPart 1: Modelling Clustered Data -- Methods for Analyzing Secondary Outcomes in Public Health Case Control Studies -- Controlling for Population Density Using Clustering and Data Weighting Techniques When Examining Social Health and Welfare Problems -- On the Inference of Partially Correlated Data with Applications to Public Health Issues -- Modeling Time-Dependent Covariates in Longitudinal Data Analyses -- Solving Probabilistic Discrete Event Systems with Moore-Penrose Generalized Inverse Matrix Method to Extract Longitudinal Characteristics from Cross-Sectional Survey Data -- Part II: Modelling Incomplete or Missing Data -- On the Effects of Structural Zeros in Regression Models -- Modeling Based on Progressively Type-I Interval Censored Sample -- Techniques for Analyzing Incomplete Data in Public Health Research -- A Continuous Latent Factor Model for Non-ignorable Missing Data -- Part III: Healthcare Research Models -- Health Surveillance -- Standardization and Decomposition Analysis: A Useful Analytical Method for Outcome Difference, Inequality and Disparity Studies -- Cusp Catastrophe Modeling in Medical and Health Research -- On Ranked Set Sampling Variation and its Applications to Public Health Research -- Weighted Multiple Testing Correction for Correlated Endpoints in Survival Data -- Meta-analytic Methods for Public Health Research.
000733818 506__ $$aAccess limited to authorized users.
000733818 520__ $$aThe book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes.
000733818 588__ $$aOnline resource; title from PDF title page (viewed September 4, 2015)
000733818 650_0 $$aPublic health$$xStatistical methods.
000733818 7001_ $$aChen, Ding-Geng,$$eeditor.
000733818 7001_ $$aWilson, Jeffrey,$$eeditor.
000733818 77608 $$iPrint version:$$z9783319185354
000733818 830_0 $$aICSA book series in statistics.
000733818 852__ $$bebk
000733818 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-18536-1$$zOnline Access$$91397441.1
000733818 909CO $$ooai:library.usi.edu:733818$$pGLOBAL_SET
000733818 980__ $$aEBOOK
000733818 980__ $$aBIB
000733818 982__ $$aEbook
000733818 983__ $$aOnline
000733818 994__ $$a92$$bISE