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Titel:

Modeling individual migraine severity with autoregressive ordered probit models.

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Czado, C., Heyn, A., Müller, G.
Abstract:
This paper considers the problem of modeling migraine severity assessments and their dependence on weather and time characteristics. We take on the viewpoint of a patient who is interested in an individual migraine management strategy. Since factors influencing migraine can differ between patients in number and magnitude, we show how a patient’s headache calendar reporting the severity measurements on an ordinal scale can be used to determine the dominating factors for this special patient....     »
Stichworte:
Bayes factor; Deviance; Ordinal valued time series; Markov ChainMonte Carlo (MCMC); Proportional odds; Regression
Zeitschriftentitel:
Statistical Methods and Applications
Jahr:
2011
Band / Volume:
20
Heft / Issue:
1
Seitenangaben Beitrag:
101-121
Reviewed:
ja
Sprache:
en
Status:
Erstveröffentlichung
Semester:
SS 11
Format:
Text
 BibTeX