Kooperativer Bibliotheksverbund

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Format: VIII, 289 S , Ill., graph. Darst , 25 cm

ISBN: 0195139739 , 0195145410

Series Statement: Series in affective science

Note: Includes bibliographical references and indexes

Language: English

Subjects: Psychology

Keywords: Zwischenmenschliche Beziehung ; Gefühlspsychologie ; Gefühl ; Interaktion ; Gesundheitspsychologie

URL: Inhaltsverzeichnis

URL: Verlagsangaben

URL: http://www.loc.gov/catdir/enhancements/fy0610/00035628-t.html

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Format: xiii, 210 p.

Edition: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.

Language: English

Keywords: Electronic books.

URL: Click to View

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ISBN: 0444861874

Content: This paper considers the formulation and estimation of continuous time social science duration models. The focus is on new issues that arise in applying statistical models developed in biostatistics to analyze economic data and formulate economic models. Both single spell and multiple spell models are discussed. In addition, we present a general time inhomogeneous multiple spell model which contains a variety of useful models as special cases. Four distinctive features of social science duration analysis are emphasized: (1) Because of the limited size of samples available in economics and because of an abundance of candidate observed explanatory variables and plausible omitted explanatory variables, standard nonparametric procedures used in biostatistics are of limited value in econometric duration analysis. It is necessary to control for observed and unobserved explanatory variables to avoid biasing inference about underlying duration distributions. Controlling for such variables raises many new problems not discussed in the available literature. (2) The environments in which economic agents operate are not the time homogeneous laboratory environments assumed in biostatistics and reliability theory. Ad hoc methods for controlling for time inhomogeneity produce badly biased estimates. (3) Because the data available to economists are not obtained from the controlled experimental settings available to biologists, doing econometric duration analysis requires accounting for the effect of sampling plans on the distributions of sampled spells. (4) Econometric duration models that incorporate the restrictions produced by economic theory only rarely can be represented by the models used by biostatisticians. The estimation of structural econometric duration models raises new statistical and computational issues. Because of (1) it is necessary to parameterize econometric duration models to control for both observed and unobserved explanatory variables. Economic theory only provides qualitative guidance on the matter of selecting a functional form for a conditional hazard, and it offers no guidance at all on the matter of choosing a distribution of unobservables. This is unfortunate because empirical estimates obtained from econometric duration models are very sensitive to assumptions made about the functional forms of these model ingredients. In response to this sensitivity we present criteria for inferring qualitative properties of conditional hazards and distributions of unobservables from raw duration data sampled in time homogeneous environments; i.e. from unconditional duration distributions. No parametric structure need be assumed to implement these procedures. We also note that current econometric practice overparameterizes duration models. Given a functional form for a conditional hazard determined up to a finite number of parameters, it is possible to consistently estimate the distribution of unobservables nonparametrically. We report on the performance of such an estimator and show that it helps to solve the sensitivity problem. We demonstrate that in principle it is possible to identify both the conditional hazard and the distribution of unobservables without assuming parametric functional forms for either. Tradeoffs in assumptions required to secure such model identification are discussed. Although under certain conditions a fully nonparametric model can be identified, the development of a consistent fully nonparametric estimator remains to be done. We also discuss conditions under which access to multiple spell data aids in solving the sensitivity problem. A superficially attractive conditional likelihood approach produces inconsistent estimators, but the practical significance of this inconsistency is not yet known. Conditional inference schemes for eliminating unobservables from multiple spell duration models that are based on sufficient or ancillary statistics require unacceptably strong assumptions about the functional forms of conditional hazards and so are not robust. Contrary to recent claims, they offer no general solution to the model sensitivity problem. The problem of controlling for time inhomogeneous environments (Point (2)) remains to be solved. Failure to control for time inhomogeneity produces serious biases in estimated duration models. Controlling for time inhomogeneity creates a potential identification problem. For a single spell data it is impossible to separate the effect of duration dependence from the effect of time inhomogeneity by a fully nonparametric procedure. Although it is intuitively obvious that access to multiple spell data aids in the solution of this identification problem, the development of precise conditions under which this is possible is a topic left for future research. We demonstrate how sampling schemes distort the functional forms of sample duration distributions away from the population duration distributions that are the usual object of econometric interest (Point (3)). Inference based on misspecified duration distributions is in general biased. New formulae for the densities of commonly used duration measures are produced for duration models with unobservables in time inhomogeneous environments. We show how access to spells that begin after the origin date of a sample aids in solving econometric problems created by the sampling schemes that are used to generate economic duration data. We also discuss new issues that arise in estimating duration models explicitly derived from economic theory (Point (4)). For a prototypical search unemployment model we discuss and resolve new identification problems that arise in attempting to recover structural economic parameters. We also consider nonstandard statistical problems that arise in estimating structural models that are not treated in the literature. Imposing or testing the restrictions implied by economic theory requires duration models that do not appear in the received literature and often requires numerical solution of implicit equations derived from optimizing theory.

In: Handbook of econometrics, Amsterdam : North-Holland Pub. Co, 1986, (1986), Seite 1689-1763, 0444861874

In: 9780444861870

In: year:1986

In: pages:1689-1763

Language: English

DOI: 10.1016/S1573-4412(86)03009-X

URL: Volltext  (Deutschlandweit zugänglich)

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Format: 1 Online-Ressource

Edition: 2. ed.

ISBN: 9781441968241

Series Statement: Springer series in statistics

Additional Edition: Erscheint auch als Druckausgabe ISBN 978-1-4419-6823-4

Language: English

DOI: 10.1007/978-1-4419-6824-1

URL: Volltext

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Format: XII, 226 p. 47 illus. , online resource.

ISBN: 9781475730272

Series Statement: Statistics for Biology and Health,

Content: Multiple complex pathways, characterized by interrelated events and con­ ditions, represent routes to many illnesses, diseases, and ultimately death. Although there are substantial data and plausibility arguments supporting many conditions as contributory components of pathways to illness and disease end points, we have, historically, lacked an effective methodology for identifying the structure of the full pathways. Regression methods, with strong linearity assumptions and data-based constraints on the extent and order of interaction terms, have traditionally been the strategies of choice for relating outcomes to potentially complex explanatory pathways. How­ ever, nonlinear relationships among candidate explanatory variables are a generic feature that must be dealt with in any characterization of how health outcomes come about. Thus, the purpose of this book is to demon­ strate the effectiveness of a relatively recently developed methodology­ recursive partitioning-as a response to this challenge. We also compare and contrast what is learned via recursive partitioning with results ob­ tained on the same data sets using more traditional methods. This serves to highlight exactly where--and for what kinds of questions-recursive partitioning-based strategies have a decisive advantage over classical re­ gression techniques. This book is suitable for three broad groups of readers: (1) biomedical re­ searchers, clinicians, public health practitioners including epidemiologists, health service researchers, environmental policy advisers; (2) consulting statisticians who can use the recursive partitioning technique as a guide in providing effective and insightful solutions to clients' problems; and (3) statisticians interested in methodological and theoretical issues.

Note: 1 Introduction -- 2 A Practical Guide to Tree Construction -- 3 Logistic Regression -- 4 Classification Trees for a Binary Response -- 5 Risk-Factor Analysis Using Tree-Based Stratification -- 6 Analysis of Censored Data: Examples -- 7 Analysis of Censored Data: Concepts and Classical Methods -- 8 Analysis of Censored Data: Survival Trees -- 9 Regression Trees and Adaptive Splines for a Continuous Response -- 10 Analysis of Longitudinal Data -- 11 Analysis of Multiple Discrete Responses -- 12 Appendix -- References.

In: Springer eBooks

Additional Edition: Printed edition: ISBN 9781475730296

Language: English

DOI: 10.1007/978-1-4757-3027-2

URL: http://dx.doi.org/10.1007/978-1-4757-3027-2

URL: Volltext

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Format: XII, 226 S. : , graph. Darst.

ISBN: 0-387-98671-5

Series Statement: Statistics for biology and health

Note: Literaturverz. S. 211 - 222

Language: German

Subjects: Economics

Keywords: Medizinische Statistik

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Format: 1 online resource (viii, 289 p.) : , ill.

ISBN: 9780199848201 (ebook) : , 0199848203 (ebook) :

Series Statement: Series in affective science

Content: Social integration and affiliative relationships can be linked to a variety of health and disease outcomes. This volume gathers lines of inquiry to advance the understanding of how emotion in social relationships influences health.

Additional Edition: Print version ISBN 9780195145410

Language: English

URL: Oxford scholarship online

URL: lizenzpflichtig

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Format: X, 371 p. , online resource.

ISBN: 9781461393320

Series Statement: Springer Series in Statistics, Statistics in the Health Sciences,

Content: Models to forecast changes in mortality, morbidity, and disability in elderly populations are essential to national and state policies for health and welfare programs. This volume presents a wide-ranging survey of the forecasting of health of elderly populations, including the modelling of the incidence of chronic diseases in the elderly, the differing perspectives of actuarial and health care statistics, and an assessment of the impact of new technologies on the elderly population. Amongst the topics covered are - uncertainties in projections from census and social security data and actuarial approaches to forecasting - plausible ranges for population growth using biol ogical models and epidemiological time series data - the financing of long term care programs - the effects of major disabling diseases on health expenditures - forecasting cancer risks and risk factors As a result, this wide-ranging volume will become an indispensable reference for all those whose research touches on these topics.

Note: One. Introduction -- 1 The Scientific and Policy Needs for Improved Health Forecasting Models for Elderly Populations -- Two. Methodological Issues -- 2 Actuarial and Demographic Forecasting Methods -- 3 Demographic Change in the United States, 1970–2050 -- 4 Health Forecasting and Models of Aging -- Three. Forecasting Techniques for Specific Diseases -- 5 Cancer Forecasting: Cohort Models of Disease Progression and Mortality -- 6 The Effects of Risk Factors on Male and Female Cardiovascular Risks in Middle and Late Age -- 7 Frailty and Forecasts of Active Life Expectancy in the United States -- 8 Risk Factors Affecting Multiple-Disease Efficacy and Effectiveness of Intervention Programs -- Four. Effects of Interventions on Health Costs -- 9 Estimates and Projections of Dementia-Related Service Expenditures -- 10 A Forecasting Model for the Assessment of Medical Technologies: End-Stage Renal Disease -- 11 Projections of the Aged Supplementary Security Income Population: The Implications of Uncertainty -- 12 Evaluation of Long-Term Care: Estimation of Health Transitions in Frail Populations -- 13 Financing and Use of Long-Term Care for the Elderly -- Five. Longitudinal Research: Current Status and Future Outlook -- 14 Molecular Biological Approaches to Understanding Aging and Senescence -- 15 Biomedical Research and Changing Concepts of Disease and Aging: Implications for Long-Term Health Forecasts for Elderly Populations.

In: Springer eBooks

Additional Edition: Printed edition: ISBN 9781461393344

Language: English

DOI: 10.1007/978-1-4613-9332-0

URL: http://dx.doi.org/10.1007/978-1-4613-9332-0

URL: Volltext

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Format: 1 online resource (xv, 410 pages) : , digital, PDF file(s).

ISBN: 9781139052146 (ebook)

Series Statement: Econometric Society monographs ; 10

Content: Longitudinal Analysis of Labor Market Data presents a set of papers by leading scholars on methods for analysing the longitudinal data that is available on numerous topics of interest to social scientists. Because many sources of longitudinal data record labour market phenomena such as unemployment, labour supply, earnings mobility, job turnover and participation in training programmes, all of the papers collected in this volume focus on models of the labour market. The main methodological points, however, are more general and apply to such diverse areas as demography, life science analysis and training evaluation, to name only a few, potential avenues of application. The book contains important methodological contributions to the emerging field of longitudinal analysis and is of interest to a wide range of social scientists.

Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Additional Edition: Print version: ISBN 9780521304535

Language: English

URL: https://doi.org/10.1017/CCOL0521304539

UID:

ISBN: 0120991942

In: Handbook of aging and the social sciences, San Diego [u.a.] : Acad. Press, 2001, (2001), Seite 44-65, 0120991942

In: year:2001

In: pages:44-65

Language: English