作者: BLAZE 時(shí)間: 2025-3-21 23:37
Statistical Models for Prediction,on the most relevant aspects of these models in a prediction context. All models are illustrated with case studies. In Chap. 6, we will discuss aspects of choosing between alternative statistical models.作者: dictator 時(shí)間: 2025-3-22 03:54 作者: Cardioversion 時(shí)間: 2025-3-22 07:10
Assumptions in regression models:Additivity and linearity,egies to extend a prediction model with interactions and non-linear terms, since better fulfillment of assumptions in a particular sample does not necessarily imply better predictive performance for future subjects. We consider several case studies for illustration of various strategies to deal with additivity and linearity.作者: hallow 時(shí)間: 2025-3-22 11:21
Book 20091st editionin the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-ba作者: Pantry 時(shí)間: 2025-3-22 15:21 作者: Pantry 時(shí)間: 2025-3-22 20:19
Evaluation of performance,lly relevant for prediction of binary outcomes in individual patients. We will illustrate the use of performance measures in the testicular cancer case study, with model development in 544 patients, internal validation with bootstrapping, and external validation with 273 patients from another centre.作者: 有花 時(shí)間: 2025-3-22 23:55 作者: EWE 時(shí)間: 2025-3-23 04:50 作者: antidepressant 時(shí)間: 2025-3-23 08:30
Restrictions on candidate predictors,predictors, combining similar variables, and averaging the effects of similar variables. We provide a detailed description of a case study of modelling similar effects of aspects of family history for robust prediction of the presence of a genetic mutation.作者: forestry 時(shí)間: 2025-3-23 11:25
Presentation formats, Various presentation formats are possible for prediction models and for decision rules, some of which will be discussed in this chapter. We illustrate the creation of some formats at a technical level for the testicular cancer case study.作者: 鍵琴 時(shí)間: 2025-3-23 14:59
Composites Science and Technology power. Power considerations are given for studying effects of specific predictors, and for developing a prediction model that can provide reliable predictions. We use several case studies for illustration.作者: Latency 時(shí)間: 2025-3-23 19:24
Safety in Biology Laboratories,on the most relevant aspects of these models in a prediction context. All models are illustrated with case studies. In Chap. 6, we will discuss aspects of choosing between alternative statistical models.作者: Affiliation 時(shí)間: 2025-3-23 23:32
The Safety of PES in the Offshore Industry,equency tables are useful to this aim. We will consider various issues in coding of unordered and ordered categorical predictors. For continuous predictors, we specifically discuss how we can limit the influence of outliers and interpret regression coefficients.作者: 樹木心 時(shí)間: 2025-3-24 05:09 作者: Default 時(shí)間: 2025-3-24 09:38 作者: 要素 時(shí)間: 2025-3-24 13:40
Experience with Computer Assessmentpe of statistical model in a prediction context, with illustration in a case study on modelling age–outcome relationships in medicine. We also summarize results from some empirical comparisons of alternative statistical models.作者: Evacuate 時(shí)間: 2025-3-24 15:52 作者: 確認(rèn) 時(shí)間: 2025-3-24 19:16 作者: Incisor 時(shí)間: 2025-3-24 23:35 作者: PANG 時(shí)間: 2025-3-25 06:21
Case study on dealing with missing values,ral studies were available to quantify predictor effects and to develop and validate prognostic models. Missing values were a key issue, since few studies recorded all predictors of interest. The use of single and multiple imputation methods is illustrated with a detailed description of the analyses in R software.作者: 寬大 時(shí)間: 2025-3-25 09:33
https://doi.org/10.1007/978-0-387-77244-8An?sthesie-Informations-Management-System; Data-analysis; Evidence-Based Medicine; Prediction; Radiologi作者: 罵人有污點(diǎn) 時(shí)間: 2025-3-25 14:08 作者: 和平 時(shí)間: 2025-3-25 18:28
Ewout W. SteyerbergA sensible strategy to all three aspects (development, validation, updating) is relevant to provide up-to-date prognostic models that can reliably support medical practice.Includes supplementary mater作者: airborne 時(shí)間: 2025-3-25 23:51
Statistics for Biology and Healthhttp://image.papertrans.cn/c/image/228183.jpg作者: 暴露他抗議 時(shí)間: 2025-3-26 02:40
Clinical Prediction Models978-0-387-77244-8Series ISSN 1431-8776 Series E-ISSN 2197-5671 作者: anachronistic 時(shí)間: 2025-3-26 07:54
Experience with Computer Assessmentral studies were available to quantify predictor effects and to develop and validate prognostic models. Missing values were a key issue, since few studies recorded all predictors of interest. The use of single and multiple imputation methods is illustrated with a detailed description of the analyses in R software.作者: CURL 時(shí)間: 2025-3-26 11:22
Composites Science and Technologya cohort study, strengths and limitations of case series from a single center, from registries, or prospective trials. We further discuss issues in choosing predictors and outcome variables for prediction models. An important question is often how large a study needs to be for sufficient statistical作者: inventory 時(shí)間: 2025-3-26 14:02
Safety in Biology Laboratories,urvival data. We discuss common statistical models in medical research such as the linear, logistic, and Cox regression model, and also simpler approaches and more flexible extensions, including regression trees and neural networks. Details of the methods are found in many excellent texts. We focus 作者: 線 時(shí)間: 2025-3-26 18:02
Safety in Chemistry Laboratories,ects, outside the sample under study. A key threat to validity is overfitting, i.e. that the data under study are well described, but that predictions are not valid for new subjects. Overfitting causes optimism about a model‘s performance in new subjects. After introducing overfitting and optimism, 作者: circumvent 時(shí)間: 2025-3-26 21:37
Experience with Computer Assessmentns from underlying data. Statistical models can well be used to make predictions for future subjects. We consider some general issues in choosing a type of statistical model in a prediction context, with illustration in a case study on modelling age–outcome relationships in medicine. We also summari作者: HUMID 時(shí)間: 2025-3-27 04:53 作者: 使殘廢 時(shí)間: 2025-3-27 09:04 作者: 跑過 時(shí)間: 2025-3-27 12:39 作者: Saline 時(shí)間: 2025-3-27 17:07 作者: 沙發(fā) 時(shí)間: 2025-3-27 21:51
Mohammad Golam Kibria,Md. Anwarul Abedinan be assessed with interaction terms. We also consider the linearity assumption of continuous predictors in a multivariable regression model, where multiple non-linear terms can be included to allow for non-linear relationships between predictors and outcome. Throughout we stress parsimony in strat作者: epidermis 時(shí)間: 2025-3-28 00:56
Takako Izumi,Indrajit Pal,Rajib Shawethods. These modern estimation methods include uniform shrinkage methods (heuristic or bootstrap based) and penalized maximum likelihood methods (with various forms of penalty, including the “Lasso”). We illustrate the application of these methods with a data set of 785 patients from the GUSTO-I ca作者: 單獨(dú) 時(shí)間: 2025-3-28 02:07 作者: Innovative 時(shí)間: 2025-3-28 07:16 作者: minaret 時(shí)間: 2025-3-28 13:59 作者: 滔滔不絕地講 時(shí)間: 2025-3-28 18:15
Book 20091st editionand applications of prediction models are often suboptimal in medical publications. With this book Ihope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is作者: Irritate 時(shí)間: 2025-3-28 21:37
Safety in Chemistry Laboratories,imates per centre are drawn towards the average to improve the quality of predictions. We then turn to overfitting in regression models, and discuss the concepts of selection and estimation bias. Again, shrinkage is a solution, which now draws estimated regression coefficients to less extreme values作者: 頭盔 時(shí)間: 2025-3-28 23:37 作者: LAPSE 時(shí)間: 2025-3-29 06:57 作者: anthesis 時(shí)間: 2025-3-29 08:06
1431-8776 his book Ihope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is978-0-387-77244-8Series ISSN 1431-8776 Series E-ISSN 2197-5671 作者: Anthem 時(shí)間: 2025-3-29 11:53
Overfitting and optimism in prediction models,imates per centre are drawn towards the average to improve the quality of predictions. We then turn to overfitting in regression models, and discuss the concepts of selection and estimation bias. Again, shrinkage is a solution, which now draws estimated regression coefficients to less extreme values作者: 北極人 時(shí)間: 2025-3-29 16:34 作者: 分散 時(shí)間: 2025-3-29 20:55 作者: omnibus 時(shí)間: 2025-3-30 01:38 作者: 社團(tuán) 時(shí)間: 2025-3-30 05:56
Statistical Models for Prediction,urvival data. We discuss common statistical models in medical research such as the linear, logistic, and Cox regression model, and also simpler approaches and more flexible extensions, including regression trees and neural networks. Details of the methods are found in many excellent texts. We focus 作者: BUST 時(shí)間: 2025-3-30 08:46 作者: 暫時(shí)別動(dòng) 時(shí)間: 2025-3-30 12:24 作者: EVEN 時(shí)間: 2025-3-30 17:30
Dealing with missing values,el for a single outcome (.). Traditional complete case analysis suffers from inefficiency, selection bias of subjects, and other limitations. We briefly review the theoretical background on mechanisms of missingness of predictor values and how these may affect prognostic modelling. We further concen作者: 角斗士 時(shí)間: 2025-3-30 22:33
Case study on dealing with missing values,ral studies were available to quantify predictor effects and to develop and validate prognostic models. Missing values were a key issue, since few studies recorded all predictors of interest. The use of single and multiple imputation methods is illustrated with a detailed description of the analyses作者: 內(nèi)疚 時(shí)間: 2025-3-31 02:30
Coding of Categorical and Continuous Predictors,e for entering in regression models and must first be manipulated. This is known as “coding.” As in any data analysis, we will usually start with obtaining an impression of the data under study, such as occurrence of missing values and the distribution of predictors. Descriptive analyses, such as fr
