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Ornulf Borgan

Dados Biográficos

ID616461
NOMEOrnulf Borgan
PRENOMESOrnulf
SOBRENOMEBorgan
ASSINATURABORGAN O
AFILIAÇÕESUniversity of Oslo
ORCID0000-0002-4687-1202
VERIFICADOSim
TOTAL DE OBRAS4
TOTAL DE CITAÇÕES14
TOTAL COMO AUTOR4
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO1987
ANO MAIS RECENTE DE PUBLICAÇÃO2019
ÍNDICE H1
  • Do Japanese and Italian Women Live Longer than Women in Scandinavia

    Open Access•Ornulf Borgan, Nico Keilman•ARTICLE•European Journal of Population /…•2019•Referências: 18

  • Causal inference in multi-state models–sickness absence and work for 1145 participants after work rehabilitation

    Open Access•Jon Michael Gran, Stein Atle Lie et al.•ARTICLE•BMC Public Health•2015

    Detailed covariate information is important for explaining transitions between different states of sickness absence and work, also for patient specific cohorts. Methods for causal inference can provide the needed tools for going from covariate specific estimates to population average effects in multi-state models, and identify causal parameters with a straightforward interpretation based on interventions

  • Statistical Models Based on Counting Processes

    Open Access•Xavier Bry, Per Kragh Andersen et al.•ARTICLE•Population•1997•Citada por: 14

    Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a-half decades. The exposition of the theory is integrated with the careful presentation of many practical ex…

  • Demographic Reproduction Rates and the Estimation of an Expected Total Count Per Person in an Open Population

    Open Access•N Bo, Ornulf Borgan et al.•ARTICLE•Population•1987

  • Statistical Models Based on Counting Processes

    Open Access•Xavier Bry, Per Kragh Andersen et al.•ARTICLE•Population•1997•Citada por: 14

    Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a-half decades. The exposition of the theory is integrated with the careful presentation of many practical ex…

  • Demographic Reproduction Rates and the Estimation of an Expected Total Count Per Person in an Open Population

    Open Access•N Bo, Ornulf Borgan et al.•ARTICLE•Population•1987

  • Statistical Models Based on Counting Processes

    Open Access•Xavier Bry, Per Kragh Andersen et al.•ARTICLE•Population•1997•Citada por: 14

    Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a-half decades. The exposition of the theory is integrated with the careful presentation of many practical ex…

  • Causal inference in multi-state models–sickness absence and work for 1145 participants after work rehabilitation

    Open Access•Jon Michael Gran, Stein Atle Lie et al.•ARTICLE•BMC Public Health•2015

    Detailed covariate information is important for explaining transitions between different states of sickness absence and work, also for patient specific cohorts. Methods for causal inference can provide the needed tools for going from covariate specific estimates to population average effects in multi-state models, and identify causal parameters with a straightforward interpretation based on interventions

  • Do Japanese and Italian Women Live Longer than Women in Scandinavia

    Open Access•Ornulf Borgan, Nico Keilman•ARTICLE•European Journal of Population /…•2019•Referências: 18

Mathematics (3 obras) · Statistics (3 obras) · Demography (2 obras) · Demography (2 obras) · Econometrics (2 obras) · Medicine (2 obras) · Population (2 obras) · Sociology (2 obras) · Advanced Causal Inference Techniques (1 obras) · Bayesian Methods and Mixture Models (1 obras)

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