Premium
Parameter redundancy in mark‐recovery models
Author(s) -
Cole Diana J.,
Morgan Byron J. T.,
Catchpole Edward A.,
Hubbard Ben A.
Publication year - 2012
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201100210
Subject(s) - covariate , redundancy (engineering) , estimation theory , range (aeronautics) , computer science , model parameter , statistics , econometrics , mathematics , data mining , engineering , aerospace engineering , operating system
We provide a definitive guide to parameter redundancy in mark‐recovery models, indicating, for a wide range of models, in which all the parameters are estimable, and in which models they are not. For these parameter‐redundant models, we identify the parameter combinations that can be estimated. Simple, general results are obtained, which hold irrespective of the duration of the studies. We also examine the effect real data have on whether or not models are parameter redundant, and show that results can be robust even with very sparse data. Covariates, as well as time‐ or age‐varying trends, can be added to models to overcome redundancy problems. We show how to determine, without further calculation, whether or not parameter‐redundant models are still parameter redundant after the addition of covariates or trends.