VID Colloquium
Modelling and decomposing vital rates: a non-parametric approach
Carlo G. Camarda, Max Planck Institute for Demographic Research, Rostock, Germany and Institut National d' Etudes D emographiques, Paris, France
Jutta Gampe, Max Planck Institute for Demographic Research, Rostock
Paul H. C. Eilers, Dept. of Biostatistics, Erasmus Medical Centre, Rotterdam, The Netherlands
Date: Wed, 12 Sep. 2012, Time: 17:00 - 18:00
Demographic events, such as marriage, migration, childbirth or death, have characteristic age-specific patterns of occurrence. Finding so-called model schedules to summarize the age pattern of demographic rates has a long tradition, however, parametric models are predominantly used. Many demographic rates shows complex shape in their overall age pattern. However such pattern can be attributed to different distinct components. Models that can separate these components are particularly welcome. While some of the components can be well described by a parametric model, such as the Gompertz hazard for adult mortality, many others cannot. An additional complication arises if data are provided only in age groups, which is still the case in many official statistics, and is standard if one goes back in time. In the presentation I will propose a general model that allows to specify (demographic) rates across a wide range of ages as the sum of several components, which are modelled on the log scale and are assumed to be smooth, but do not have to follow a particular parametric form. A penalized composite link model is used to decompose the complex rate trajectory into smooth additive components. Parametric and non-parametric models can be used for describing each component. Data can be given in grouped form, and the age groups can be of variable lengths. Furthermore, monotonicity or shape constraints on the components can be incorporated by special penalty matrices. The model can also cope with two-dimensional settings in which age patterns change over time.
About the presenterCarlo Giovanni Camarda is research scientist in the Laboratory of Survival & Longevity at the Max Planck Institute for Demographic Research (Germany) and chargé de recherche at the Institut National d' Etudes D emographiques (France). He has received his first university education at the Universit a \La Sapienza" in Rome on Social and Demographic Statistical Sciences. Later he continued his study at the Max Planck Institute for Demographic Research within the Laboratory of Statistical Demography. He was awarded his Ph.D. in Mathematical Engineering: Statistical Sciences and Techniques Area at the Department of Statistics at Universidad Carlos III in Madrid. His interests range from the general theory for the biodemography of human ageing to modeling patterns of digit preference, warping models for lifetime distributions, modelling and smoothing mortality surfaces, reconstruction of mortality series by causes of death, analysis of social contact data and methodological issues in measuring alcohol consumptions. Carlo G. Camarda has numerous collaboration in European research institutions and he has been involved in several teaching activities. He has written several research papers in the field of demography and statistics and he has devised an R package for smoothing and forecasting mortality.