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Regression Modeling Strategies (Record no. 414412)
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| 000 -Маркер записи | |
|---|---|
| Контрольное поле постоянной длины | 05419nam a22004695i 4500 |
| 001 - Контрольный номер | |
| Контрольное поле | vtls000560082 |
| 005 - Дата корректировки | |
| Контрольное поле | 20210922090000.0 |
| 007 - Кодируемые данные (физ. описан.) | |
| Контрольное поле постоянной длины | cr nn 008mamaa |
| 008 - Кодируемые данные | |
| Контрольное поле постоянной длины | 170212s2015 gw | s |||| 0|eng d |
| 020 ## - Индекс ISBN | |
| ISBN | 9783319194257 |
| -- | 978-3-319-19425-7 |
| 024 7# - Прочие стандартные номера | |
| Стандартный номер | 10.1007/978-3-319-19425-7 |
| Источник номера | doi |
| 035 ## - Системный контрольный номер | |
| Системный контрольный номер | to000560082 |
| 040 ## - Источник каталогиз. | |
| Служба первич. каталог. | Springer |
| Служба, преобразующая запись | Springer |
| Организация, изменившая запись | RU-ToGU |
| 050 #4 - Расстановочный код библ. Конгресса | |
| Классификационный индекс | QA276-280 |
| 072 #7 - Код предметной/темат. категории | |
| Код предметной/темат. категории | PBT |
| Источник кода | bicssc |
| 072 #7 - Код предметной/темат. категории | |
| Код предметной/темат. категории | MAT029000 |
| Источник кода | bisacsh |
| 082 04 - Индекс Дьюи | |
| Индекс Дьюи | 519.5 |
| Номер издания | 23 |
| 100 1# - Автор | |
| Автор | Harrell , Jr., Frank E. |
| Роль лиц | author. |
| 9 (RLIN) | 466230 |
| 245 10 - Заглавие | |
| Заглавие | Regression Modeling Strategies |
| Физический носитель | electronic resource |
| Продолж. заглавия | With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis / |
| Ответственность | by Frank E. Harrell , Jr. |
| 250 ## - Сведения об издании | |
| Основные сведения об издании | 2nd ed. 2015. |
| 260 ## - Выходные данные | |
| Место издания | Cham : |
| Издательство | Springer International Publishing : |
| -- | Imprint: Springer, |
| Дата издания | 2015. |
| 300 ## - Физическое описание | |
| Объем | XXV, 582 p. 157 illus., 53 illus. in color. |
| Иллюстрации/тип воспроизводства | online resource. |
| 336 ## - Тип содержимого | |
| Тип содержимого | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - Средство доступа | |
| Средство доступа | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - Тип носителя | |
| Тип носителя | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 490 1# - Серия | |
| Заглавие серии | Springer Series in Statistics, |
| ISSN серии | 0172-7397 |
| 505 0# - Примечание о содержании | |
| Содержание | Introduction -- General Aspects of Fitting Regression Models -- Missing Data -- Multivariable Modeling Strategies -- Describing, Resampling, Validating and Simplifying the Model -- R Software -- Modeling Longitudinal Responses using Generalized Least Squares -- Case Study in Data Reduction -- Overview of Maximum Likelihood Estimation -- Binary Logistic Regression -- Binary Logistic Regression Case Study 1 -- Logistic Model Case Study 2: Survival of Titanic Passengers -- Ordinal Logistic Regression -- Case Study in Ordinal Regression, Data Reduction and Penalization.- Regression Models for Continuous Y and Case Study in Ordinal Regression -- Transform-Both-Sides Regression -- Introduction to Survival Analysis -- Parametric Survival Models -- Case Study in Parametric Survival Modeling and Model Approximation -- Cox Proportional Hazards Regression Model -- Case Study in Cox Regression -- Appendix. . |
| 520 ## - Аннотация | |
| Аннотация | This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for fitting nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. The reader will gain a keen understanding of predictive accuracy, and the harm of categorizing continuous predictors or outcomes. This text realistically deals with model uncertainty, and its effects on inference, to achieve "safe data mining." It also presents many graphical methods for communicating complex regression models to non-statisticians. Regression Modeling Strategies presents full-scale case studies of non-trivial datasets instead of over-simplified illustrations of each method. These case studies use freely available R functions that make the multiple imputation, model building, validation, and interpretation tasks described in the book relatively easy to do. Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalized least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models, and the Cox semiparametric survival model. A new emphasis is given to the robust analysis of continuous dependent variables using ordinal regression. As in the first edition, this text is intended for Masters' or Ph.D. level graduate students who have had a general introductory probability and statistics course and who are well versed in ordinary multiple regression and intermediate algebra. The book will also serve as a reference for data analysts and statistical methodologists, as it contains an up-to-date survey and bibliography of modern statistical modeling techniques. Examples used in the text mostly come from biomedical research, but the methods are applicable anywhere predictive models ("analytics") are useful, including economics, epidemiology, sociology, psychology, engineering, and marketing. |
| 650 #0 - Тематические рубрики | |
| Основная рубрика | Statistics. |
| 9 (RLIN) | 124796 |
| 650 14 - Тематические рубрики | |
| Основная рубрика | Statistics. |
| 9 (RLIN) | 124796 |
| 650 24 - Тематические рубрики | |
| Основная рубрика | Statistical Theory and Methods. |
| 9 (RLIN) | 303276 |
| 650 24 - Тематические рубрики | |
| Основная рубрика | Statistics for Life Sciences, Medicine, Health Sciences. |
| 9 (RLIN) | 265982 |
| 650 24 - Тематические рубрики | |
| Основная рубрика | Statistics and Computing/Statistics Programs. |
| 9 (RLIN) | 303277 |
| 710 2# - Другие организации | |
| Организация/юрисдикция | SpringerLink (Online service) |
| 9 (RLIN) | 143950 |
| 773 0# - Источник информации | |
| Название источника | Springer eBooks |
| 830 #0 - Заголовок добавочной библ.записи на серию — унифицированное заглавие | |
| Унифицированное заглавие | Springer Series in Statistics, |
| 9 (RLIN) | 297514 |
| 856 40 - Электронный адрес документа | |
| URL | <a href="http://dx.doi.org/10.1007/978-3-319-19425-7">http://dx.doi.org/10.1007/978-3-319-19425-7</a> |
| 912 ## - Coursera for Campus: онлайн курсы для ТГУ | |
| Coursera for Campus: онлайн курсы для ТГУ | ZDB-2-SMA |
| 999 ## - Системные контрольные номера (Koha) | |
| biblionumber (Koha) | 414412 |
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