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"Equally useful as a reference for individuals interested in the analysis of lifetime data and as a text for advanced students, Statistical Models and Methods for Lifetime Data, Second Edition provides broad coverage of the area without concentrating on any single field of application. Extensive illustrations and examples drawn from engineering and the biomedical sciences provide readers with a clear understanding of key concepts."--Jacket.

Mathematical statistics --- QA 276 .L328 Mathematical statistics --- Failure time data analysis --- Survival analysis (Biometry) --- AA / International- internationaal --- 303.0 --- 304.0 --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Failure time data analysis. --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Survival analysis (Biometry). --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Statistique

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* Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns. * Introduces the martingale and counting process formulation swil lbe in a new chapter. * Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations. * Presents new examples and applications of data analysis.

Mathematical statistics --- QA 276 .K215 Mathematical statistics --- Failure time data analysis --- Survival analysis (Biometry) --- Regression analysis --- AA / International- internationaal --- 303.0 --- 304.0 --- 519.5 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Failure time data analysis. --- Regression analysis. --- Survival analysis (Biometry). --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen

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While regression analysis traces the dependence of the distribution of a response variable to see if it bears a particular (linear) relationship to one or more of the predictors, nonparametric regression analysis makes minimal assumptions about the form of relationship between the average response and the predictors. This makes nonparametric regression a more useful technique for analyzing data in which there are several predictors that may combine additively to influence the response. (An example could be something like birth order/gender/and temperament on achievement motivation). Unfortunately, researchers have not had accessible information on nonparametric regression analysisuntil now. Beginning with presentation of nonparametric regression based on dividing the data into bins and averaging the response values in each bin, Fox introduces readers to the techniques of kernel estimation, additive nonparametric regression, and the ways nonparametric regression can be employed to select transformations of the data preceding a linear least-squares fit. The book concludes with ways nonparametric regression can be generalized to logit, probit, and Poisson regression.

Mathematical statistics --- QA 278.2 .H67 2000 Regression analysis. Correlation analysis --- Regression analysis --- Nonparametric statistics --- #SBIB:303H10 --- #PBIB:2003.3 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Distribution-free statistics --- Statistics, Distribution-free --- Statistics, Nonparametric --- Methoden en technieken: algemene handboeken en reeksen --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Nonparametric statistics. --- Regression analysis. --- Regression Analysis

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This book provides a timely and novel contribution to understanding and enhancing evidence use. It builds on and complements the popular and best-selling "What Works?: Evidence-based policy and practice in public services" (Davies, Nutley and Smith, Policy Press, 2000), by drawing together current knowledge about how research gets used and how this can be encouraged and improved. In particular, the authors explore various multidiscipliary frameworks for understanding the research use agenda; consider how research use and the impact of research can be assessed; summarise the empirical evidence from the education, health care, social care and criminal justice fields about how research is used and how this can be improved and draw out practical issues that need to be addressed if research is to have greater impact on public services. "Using evidence" is important reading for university and government researchers, research funding bodies, public service managers and professionals, and students of public policy and management. It will also prove an invaluable guide for anyone involved in the implementation of evidence-based policy and practice.

#SBIB:35H410 --- #SBIB:32H3 --- Beleidscyclus: algemene werken --- Politieke wetenschappen: inleidende werken, handboeken, methoden --- Political planning --- Public administration --- Social policy --- Methods in social research (general) --- Great Britain --- Beleid. --- Sociaal-wetenschappelijk onderzoek. --- Evidence-Based Practice --- JN 318 Political institutions and public administration (Europe) --- Organisation and Administration --- Public Policy

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Mathematical statistics --- QA 276.A55 Mathematical statistics / General Works --- Missing observations (Statistics) --- Mathematical statistics. --- Missing observations (Statistics). --- #PBIB:2003.3 --- #SBIB:303H10 --- #SBIB:303H510 --- Data, Missing (Statistics) --- Missing data (Statistics) --- Missing values (Statistics) --- Observations, Missing (Statistics) --- Values, Missing (Statistics) --- Estimation theory --- Multivariate analysis --- Multiple imputation (Statistics) --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Methoden en technieken: algemene handboeken en reeksen --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Statistical methods