Age-period-cohort models for the Lexis diagram

被引:342
作者
Carstensen, B. [1 ]
机构
[1] Steno Diabet Ctr, DK-2820 Gentofte, Denmark
关键词
age-period-cohort model; Lexis diagram; follow-up studies; Poisson model; parametrization; epidemiology; demography;
D O I
10.1002/sim.2764
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Analysis of rates from disease registers are often reported inadequately because of too coarse tabulation of data and because of confusion about the mechanics of the age-period-cohort model used for analysis. Rates should be considered as observations in a Lexis diagram, and tabulation a necessary reduction of data, which should be as small as possible, and age, period and cohort should be treated as continuous variables. Reporting should include the absolute level of the rates as part of the age-effects. This paper gives a guide to analysis of rates from a Lexis diagram by the age-period-cohon model. Three aspects are considered separately: (1) tabulation of cases and person-years; (2) modelling of age, period and cohort effects; and (3) parametrization and reporting of the estimated effects. It is argued that most of the confusion in the literature comes from failure to make a clear distinction between these three aspects. A set of recommendations for the practitioner is given and a package for R that implements the recommendations is introduced. Copyright (c) 2006 John Wiley & Sons, Ltd.
引用
收藏
页码:3018 / 3045
页数:28
相关论文
共 23 条
[1]   Age-period-cohort analysis of Swiss suicide data, 1881-2000 [J].
Ajdacic-Gross, Vladeta ;
Bopp, Matthias ;
Gostynski, Michael ;
Lauber, Christoph ;
Gutzwiller, Felix ;
Roessler, Wulf .
EUROPEAN ARCHIVES OF PSYCHIATRY AND CLINICAL NEUROSCIENCE, 2006, 256 (04) :207-214
[2]   STATISTICAL MODELING OF LUNG-CANCER AND LARYNGEAL-CANCER INCIDENCE IN SCOTLAND, 1960-1979 [J].
BOYLE, P ;
ROBERTSON, C .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 1987, 125 (04) :731-744
[3]   Increasing trend of Type I diabetes in children and young adults in the province of Turin (Italy). Analysis of age, period and birth cohort effects from 1984 to 1996 [J].
Bruno, G ;
Merletti, F ;
Biggeri, A ;
Cerutti, F ;
Grosso, N ;
De Salvia, A ;
Vitali, E ;
Pagano, G .
DIABETOLOGIA, 2001, 44 (01) :22-25
[4]  
CARTENSEN B, 2004, LECT NOTES U COPENHA
[5]   MODELS FOR TEMPORAL VARIATION IN CANCER RATES .1. AGE PERIOD AND AGE COHORT MODELS [J].
CLAYTON, D ;
SCHIFFLERS, E .
STATISTICS IN MEDICINE, 1987, 6 (04) :449-467
[6]   MODELS FOR TEMPORAL VARIATION IN CANCER RATES .2. AGE PERIOD COHORT MODELS [J].
CLAYTON, D ;
SCHIFFLERS, E .
STATISTICS IN MEDICINE, 1987, 6 (04) :469-481
[7]   Type 1 diabetes in Yorkshire, UK: time trends in 0-14 and 15-29-year-olds, age at onset and age-period-cohort modelling [J].
Feltbower, RG ;
McKinney, PA ;
Parslow, RC ;
Stephenson, CR ;
Bodansky, HJ .
DIABETIC MEDICINE, 2003, 20 (06) :437-441
[8]   Modeling of time trends and interactions in vital rates using restricted regression splines [J].
Heuer, C .
BIOMETRICS, 1997, 53 (01) :161-177
[9]  
HOEM J. M., 1969, Biometr.-Praxim., V10, P38
[10]   Approaches to fitting age-period-cohort models with unequal intervals [J].
Holford, TR .
STATISTICS IN MEDICINE, 2006, 25 (06) :977-993