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Advanced statistics for health research

By:

Butler, Richrad J

Contributor(s):

Material type: Text

TextPublication details: World Scientific Publishing Co. Pte. Ltd. Singapore 2023Description: xv, 379 pISBN:

9789811262302

Subject(s):

DDC classification:

610.21 BUT

Summary: Advanced Statistics for Health Research provides a rigorous geometric understanding of models used in the analysis of health data, including linear and non-linear regression models, and supervised machine learning models. Models drawn from the health literature include: ordinary least squares, two-stage least squares, probits, logits, Cox regressions, duration modeling, quantile regression and random forest regression. Causal inference techniques from the health literature are presented including randomization, matching and propensity score matching, differences-in-differences, instrumental variables, regression discontinuity, and fixed effects analysis. Codes for the respective statistical techniques presented are given for STATA, SAS and R. (https://www.worldscientific.com/worldscibooks/10.1142/13023#t=aboutBook)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	610.21 BUT (Browse shelf(Opens below))	1	Available		007743

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Advanced Statistics for Health Research provides a rigorous geometric understanding of models used in the analysis of health data, including linear and non-linear regression models, and supervised machine learning models. Models drawn from the health literature include: ordinary least squares, two-stage least squares, probits, logits, Cox regressions, duration modeling, quantile regression and random forest regression. Causal inference techniques from the health literature are presented including randomization, matching and propensity score matching, differences-in-differences, instrumental variables, regression discontinuity, and fixed effects analysis. Codes for the respective statistical techniques presented are given for STATA, SAS and R.

(https://www.worldscientific.com/worldscibooks/10.1142/13023#t=aboutBook)

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