The Resource Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource)
Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource)
Resource Information
The item Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in European University Institute.This item is available to borrow from 1 library branch.
Resource Information
The item Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in European University Institute.
This item is available to borrow from 1 library branch.
- Summary
- The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies .--
- Language
- eng
- Edition
- 2nd ed. 2019.
- Extent
- 1 online resource (XXXIII, 558 pages)
- Contents
-
- Introduction
- Applications of prediction models.Study design for prediction modeling
- Statistical Models for Prediction
- Overfitting and optimism in prediction models
- Choosing between alternative statistical models
- Missing values
- Case study on dealing with missing values
- Coding of Categorical and Continuous Predictors
- Restrictions on candidate predictors
- Selection of main effects
- Assumptions in regression models: Additivity and linearity
- Modern estimation methods
- Estimation with external information
- Evaluation of performance
- Evaluation of Clinical Usefulness
- Validation of Prediction Models
- Presentation formats
- Patterns of external validity
- Updating for a new setting
- Updating for multiple settings
- Case study on a prediction of 30-day mortality
- Case study on Survival Analysis: prediction of cardiovascular events
- Overall lessons and data sets
- References
- Isbn
- 9783030163990
- Label
- Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating
- Title
- Clinical Prediction Models
- Title remainder
- A Practical Approach to Development, Validation, and Updating
- Statement of responsibility
- by Ewout W. Steyerberg
- Language
- eng
- Summary
- The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies .--
- Assigning source
- Provided by publisher
- http://library.link/vocab/creatorName
- Steyerberg, Ewout W
- Image bit depth
- 0
- Literary form
- non fiction
- Nature of contents
- dictionaries
- Series statement
-
- Statistics for Biology and Health,
- Springer eBooks.
- http://library.link/vocab/subjectName
-
- Statistics
- Internal medicine
- Label
- Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource)
- Antecedent source
- mixed
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- not applicable
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Applications of prediction models.Study design for prediction modeling -- Statistical Models for Prediction -- Overfitting and optimism in prediction models -- Choosing between alternative statistical models -- Missing values -- Case study on dealing with missing values -- Coding of Categorical and Continuous Predictors -- Restrictions on candidate predictors -- Selection of main effects -- Assumptions in regression models: Additivity and linearity -- Modern estimation methods -- Estimation with external information -- Evaluation of performance -- Evaluation of Clinical Usefulness -- Validation of Prediction Models -- Presentation formats -- Patterns of external validity -- Updating for a new setting -- Updating for multiple settings -- Case study on a prediction of 30-day mortality -- Case study on Survival Analysis: prediction of cardiovascular events -- Overall lessons and data sets -- References
- Control code
- 978-3-030-16399-0
- Dimensions
- unknown
- Edition
- 2nd ed. 2019.
- Extent
- 1 online resource (XXXIII, 558 pages)
- File format
- multiple file formats
- Form of item
-
- online
- electronic
- Governing access note
- Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
- Isbn
- 9783030163990
- Level of compression
- uncompressed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- 226 illustrations, 161 illustrations in color.
- Quality assurance targets
- absent
- Reformatting quality
- access
- Specific material designation
- remote
- System control number
- (OCoLC)1114822987
- Label
- Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource)
- Antecedent source
- mixed
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- not applicable
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Applications of prediction models.Study design for prediction modeling -- Statistical Models for Prediction -- Overfitting and optimism in prediction models -- Choosing between alternative statistical models -- Missing values -- Case study on dealing with missing values -- Coding of Categorical and Continuous Predictors -- Restrictions on candidate predictors -- Selection of main effects -- Assumptions in regression models: Additivity and linearity -- Modern estimation methods -- Estimation with external information -- Evaluation of performance -- Evaluation of Clinical Usefulness -- Validation of Prediction Models -- Presentation formats -- Patterns of external validity -- Updating for a new setting -- Updating for multiple settings -- Case study on a prediction of 30-day mortality -- Case study on Survival Analysis: prediction of cardiovascular events -- Overall lessons and data sets -- References
- Control code
- 978-3-030-16399-0
- Dimensions
- unknown
- Edition
- 2nd ed. 2019.
- Extent
- 1 online resource (XXXIII, 558 pages)
- File format
- multiple file formats
- Form of item
-
- online
- electronic
- Governing access note
- Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
- Isbn
- 9783030163990
- Level of compression
- uncompressed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- 226 illustrations, 161 illustrations in color.
- Quality assurance targets
- absent
- Reformatting quality
- access
- Specific material designation
- remote
- System control number
- (OCoLC)1114822987
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.eui.eu/portal/Clinical-Prediction-Models--A-Practical-Approach/7avQqHOd6pg/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.eui.eu/portal/Clinical-Prediction-Models--A-Practical-Approach/7avQqHOd6pg/">Clinical Prediction Models : A Practical Approach to Development, Validation, and Updating, by Ewout W. Steyerberg, (electronic resource)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.eui.eu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.eui.eu/">European University Institute</a></span></span></span></span></div>