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Condition: Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.
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hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Hardcover. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)
Published by Springer (edition 2nd ed. 2012), 2011
ISBN 10: 1461413524 ISBN 13: 9781461413523
Language: English
Hardcover. Condition: Very Good. 2nd ed. 2012. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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Hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)
Published by Springer (edition 2nd ed. 2012), 2011
ISBN 10: 1461413524 ISBN 13: 9781461413523
Language: English
Hardcover. Condition: Good. 2nd ed. 2012. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)
Seller: Goodwill of Greater Milwaukee and Chicago, Racine, WI, U.S.A.
Seller rating 5 out of 5 stars
Condition: acceptable. Book is considered to be in acceptable condition. The actual cover image may not match the stock photo. Book may have one or more of the following defects: noticeable wear on the cover dust jacket or spine; curved, dog eared or creased page s ; writing or highlighting inside or on the edges; sticker s or other adhesive on cover; CD DVD may not be included; and book may be a former library copy.
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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models
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Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Condition: New. pp. 532 2nd Edition.
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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 140.57
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Add to basketCondition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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Regression Methods in Biostatistics
Published by Springer-Verlag New York Inc., US, 2014
ISBN 10: 1489998543 ISBN 13: 9781489998545
Language: English
Paperback. Condition: New. 2nd ed. 2012. This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
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Regression Methods in Biostatistics
Published by Springer-Verlag New York Inc., US, 2011
ISBN 10: 1461413524 ISBN 13: 9781461413523
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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US$ 195.69
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Add to basketHardback. Condition: New. 2nd ed. 2012. This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
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US$ 143.29
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Add to basketCondition: New. Short and to the point so that the important issues and similarities between the methods, rather than the differences, shine throughProvides a unified introduction to the regression methods listed in the titleUnified approach should appeal .
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Regression Methods in Biostatistics
Published by Springer-Verlag New York Inc., US, 2014
ISBN 10: 1489998543 ISBN 13: 9781489998545
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
US$ 210.08
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Add to basketPaperback. Condition: New. 2nd ed. 2012. This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
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Regression Methods in Biostatistics : Linear, Logistic, Survival, and Repeated Measures Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 204.92
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Regression Methods in Biostatistics
Published by Springer-Verlag New York Inc., US, 2014
ISBN 10: 1489998543 ISBN 13: 9781489998545
Language: English
US$ 175.05
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Add to basketPaperback. Condition: New. 2nd ed. 2012. This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
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US$ 193.93
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Regression Methods in Biostatistics
Published by Springer-Verlag New York Inc., US, 2011
ISBN 10: 1461413524 ISBN 13: 9781461413523
Language: English
US$ 188.80
Convert currencyUS$ 86.80 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardback. Condition: New. 2nd ed. 2012. This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
-
Regression Methods in Biostatistics
Published by Springer-Verlag New York Inc., US, 2014
ISBN 10: 1489998543 ISBN 13: 9781489998545
Language: English
US$ 202.80
Convert currencyUS$ 86.80 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback. Condition: New. 2nd ed. 2012. This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
