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  • 1
    Online Resource
    Online Resource
    Berlin [u.a.] : Springer
    Keywords: Kontrollierte klinische Studie ; Kontrollierte klinische Studie
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource
    Edition: 2., überarb. und erw. Aufl.
    ISBN: 3540369899 , 9783540369899 , 9783540369905
    Series Statement: Statistik und ihre Anwendungen
    DDC: 519.5
    RVK:
    RVK:
    Language: German
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Berlin ; Heidelberg : Springer
    Keywords: Kontrollierte klinische Studie ; Kontrollierte klinische Studie
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (XXIII, 436 Seiten) , Diagramme
    Edition: Dritte, überarbeitete Auflage
    ISBN: 9783540851363
    Series Statement: Statistik und ihre Anwendungen
    DDC: 615.50724
    RVK:
    RVK:
    Language: German
    Location Call Number Limitation Availability
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Breast cancer research and treatment 49 (1998), S. 87-91 
    ISSN: 1573-7217
    Keywords: breast cancer ; local recurrence ; statistical method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Notes: Abstract Local recurrence rates play an important role in the evaluation and judgement of local treatment modalities in breast cancer. In the medical literature different methods for the calculation of these rates have been used. In this note we discuss the methods, the observed differences, and the interpretation of the resulting estimates.
    Type of Medium: Electronic Resource
    Location Call Number Limitation Availability
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Lifetime data analysis 2 (1996), S. 219-240 
    ISSN: 1572-9249
    Keywords: Extra hospital stay ; Markov processes ; Multistate models ; Structured nested failure time models ; Time-dependent covariates
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Evaluation of the impact of nosocomial infection on duration of hospital stay usually relies on estimates obtained in prospective cohort studies. However, the statistical methods used to estimate the extra length of stay are usually not adequate. A naive comparison of duration of stay in infected and non-infected patients is not adequate to estimate the extra hospitalisation time due to nosocomial infections. Matching for duration of stay prior to infection can compensate in part for the bias of ad hoc methods. New model-based approaches have been developed to estimate the excess length of stay. It will be demonstrated that statistical models based on multivariate counting processes provide an appropriate framework to analyse the occurrence and impact of nosocomial infections. We will propose and investigate new approaches to estimate the extra time spent in hospitals attributable to nosocomial infections based on functionals of the transition probabilities in multistate models. Additionally, within the class of structural nested failure time models an alternative approach to estimate the extra stay due to nosocomial infections is derived. The methods are illustrated using data from a cohort study on 756 patients admitted to intensive care units at the University Hospital in Freiburg.
    Type of Medium: Electronic Resource
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