Clarifying hierarchical age-period-cohort models: A rejoinder to Bell and Jones.
Previously, Reither et al. (2015) demonstrated that hierarchical age-period-cohort (HAPC) models perform well when basic assumptions are satisfied. To contest this finding, Bell and Jones (2015) invent a data generating process (DGP) that borrows age, period and cohort effects from different equations in Reither et al. (2015). When HAPC models applied to data simulated from this DGP fail to recover the patterning of APC effects, B&J reiterate their view that these models provide "misleading evidence dressed up as science." Despite such strong words, B&J show no curiosity about their own simulated data--and therefore once again misapply HAPC models to data that violate important assumptions. In this response, we illustrate how a careful analyst could have used simple descriptive plots and model selection statistics to verify that (a) period effects are not present in these data, and (b) age and cohort effects are conflated. By accounting for the characteristics of B&J's artificial data structure, we successfully recover the "true" DGP through an appropriately specified model. We conclude that B&Js main contribution to science is to remind analysts that APC models will fail in the presence of exact algebraic effects (i.e., effects with no random/stochastic components), and when collinear temporal dimensions are included without taking special care in the modeling process. The expanded list of coauthors on this commentary represents an emerging consensus among APC scholars that B&J's essential strategy--testing HAPC models with data simulated from contrived DGPs that violate important assumptions--is not a productive way to advance the discussion about innovative APC methods in epidemiology and the social sciences.
Department of Sociology and the Yun Kim Population Research Laboratory, Utah State University, 0730 Old Main Hill, Logan UT 84322-0730, USA. Electronic address: eric.reither@usu.edu.
Eric N
EN
Reither
Department of Sociology and Center for Population Health and Aging, Duke University, USA.
Kenneth C
KC
Land
Department of Sociology and the Yun Kim Population Research Laboratory, Utah State University, 0730 Old Main Hill, Logan UT 84322-0730, USA.
Sun Y
SY
Jeon
Department of Sociology, Population Research Center, The University of Texas at Austin, USA.
Daniel A
DA
Powers
Department of Sociology and Institute of Behavioral Science, University of Colorado at Boulder, USA.
Ryan K
RK
Masters
Department of Sociology, The Ohio State University, USA.
Hui
H
Zheng
Department of Sociology and Criminology, Population Research Institute, The Pennsylvania State University, USA.
Melissa A
MA
Hardy
Department of Epidemiology, Mailman School of Public Health, Columbia University, USA.
Katherine M
KM
Keyes
Department of Sociology, The University of British Columbia, Canada.
Qiang
Q
Fu
Department of Family and Preventive Medicine and the Huntsman Cancer Institute, The University of Utah, USA.
Heidi A
HA
Hanson
Department of Family and Consumer Studies and the Huntsman Cancer Institute, The University of Utah, USA.
Ken R
KR
Smith
Department of Sociology, The University of Utah, USA.
Rebecca L
RL
Utz
Department of Sociology and the Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, USA.
Y Claire
YC
Yang
D015988:Cohort Effect; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D008297:Male; D009765:Obesity / Q000453:epidemiology*
Age–period–cohort models; Body mass index; Cohort effects; Hierarchical modeling; Obesity epidemic; Random effects; Simulation models; Social change