國立虎尾科技大學 |

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates/ by Jeffrey R. Wilson, Elsa Vazquez-Arreola, (Din) Ding-Geng Chen.
作者:	Wilson, Jeffrey R.
其他作者:	Chen, (Din) Ding-Geng.
面頁冊數:	XXIII, 166 p. 20 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Public Health. -
電子資源:	https://doi.org/10.1007/978-3-030-48904-5
ISBN:	9783030489045

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates
Wilson, Jeffrey R.

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates[electronic resource] /by Jeffrey R. Wilson, Elsa Vazquez-Arreola, (Din) Ding-Geng Chen. - 1st ed. 2020. - XXIII, 166 p. 20 illus.online resource. - Emerging Topics in Statistics and Biostatistics ,2524-7735. - Emerging Topics in Statistics and Biostatistics ,.

1. Introduction to Binary Regression Models -- 2. Generalized Estimating Equations Binary Models -- 3. Lai and Small Models for Time-Dependent Covariates -- 4. Lalonde, wilson, and Yin Models for Time-Dependent Covariates -- 5. Irimata, Broatch, and Wilson Models for Time-Dependent Covariates -- 6. Bayesian GMM to IBW Method of Analysis -- 7. Models for Joint Responses for Time-Dependent Covariates -- 8. Other Models for Time-Dependent Covariates.

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health.

ISBN: 9783030489045

Standard No.: 10.1007/978-3-030-48904-5doiSubjects--Topical Terms:

592982
Public Health.

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates
LDR:02764nam a22004215i 4500 001 1029857
003 DE-He213
005 20200928212506.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030489045 $9 978-3-030-48904-5
024 7 $a 10.1007/978-3-030-48904-5 $2 doi
035 $a 978-3-030-48904-5
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a MED090000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a MBNS $2 thema
082 0 4 $a 519.5 $2 23
100 1 $a Wilson, Jeffrey R. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1069915
245 1 0 $a Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates $h [electronic resource] / $c by Jeffrey R. Wilson, Elsa Vazquez-Arreola, (Din) Ding-Geng Chen.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a XXIII, 166 p. 20 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Emerging Topics in Statistics and Biostatistics , $x 2524-7735
505 0 $a 1. Introduction to Binary Regression Models -- 2. Generalized Estimating Equations Binary Models -- 3. Lai and Small Models for Time-Dependent Covariates -- 4. Lalonde, wilson, and Yin Models for Time-Dependent Covariates -- 5. Irimata, Broatch, and Wilson Models for Time-Dependent Covariates -- 6. Bayesian GMM to IBW Method of Analysis -- 7. Models for Joint Responses for Time-Dependent Covariates -- 8. Other Models for Time-Dependent Covariates.
520 $a This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health.
650 2 4 $a Public Health. $3 592982
650 2 4 $a Health Care Management. $3 1019864
650 2 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
650 1 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 670172
650 0 $a Public health. $3 560998
650 0 $a Health services administration. $3 564005
650 0 $a Health care management. $3 1148454
650 0 $a Biostatistics. $3 783654
650 0 $a Statistics . $3 1253516
700 1 $a Chen, (Din) Ding-Geng. $e editor. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1321671
700 1 $a Vazquez-Arreola, Elsa. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1326675
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030489038
776 0 8 $i Printed edition: $z 9783030489052
776 0 8 $i Printed edition: $z 9783030489069
830 0 $a Emerging Topics in Statistics and Biostatistics , $x 2524-7735 $3 1318814
856 4 0 $u https://doi.org/10.1007/978-3-030-48904-5
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)