Stata package for estimating age-period-cohort models

apc_cglim estimates generalized linear models in which a single equality constraint on the coefficients is used to solve the age-period-cohort identification problem

apc_ie estimates generalized linear models with age, period and cohort  effects using the intrinsic estimator (IE)

fit age-period-cohort models using restricted cubic splines

models age, period, and cohort as continuous variables through the use of spline functions

fitting of smooth age–period–cohort models to event data

the plotting of observed and fitted rates.

module for estimating age-period-cohort effects with detrended coefficients

apcd estimates age-period-cohort APC-D (detrended) models and provides detrended (0 sum and 0 slope) parameters of age, period and cohort effects

module for estimating age-period-cohort and hysteresis effects apch is an age-period-cohort model packages that tests

module to calculate age-period-cohort effects for the gap between two groups (based on a Blinder-Oaxaca decomposition), including trends for each parameter

module to conduct age, period, and cohort (APC) analysis of tabular rate data using the intrinsic estimator

Routines for Descriptive and Model-Based APC Analysis

The 'APCtools' package offers visualization techniques and general routines to simplify the workflow of an APC analysis

Age-Period-Cohort Analysis – A Way Forward

What we are claiming is that we have developed a set of methods that allows researchers to get around and go beyond the classic APC identification problem. Of course, in the end the real test is whether the methods we propose are useful for doing actual empirical analyses. As described below we have a beta versions of R programs for analyzing APC data.

Functions for age-period-cohort analysis. Aggregate data can be organised in matrices indexed by age-cohort, age-period or cohort-period

新增加apc.indiv：acceleration-based age-period-cohort regressions with individual-level data

A New Age-Period-Cohort Model for Describing and Investigating Inter-Cohort Differences and Life Course Dynamics

It implemented Age-Period-Interaction Model (APC-I Model) proposed in the paper of Liying Luo and James S. Hodges in 2019. A new age-period-cohort model for describing and investigating inter-cohort differences and life course dynamics

Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data. In particular representation, manipulation, rate estimation and simulation for multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.

BAMP is a software package to analyze incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. Such models have been described in, e.g., Berzuini and Clayton (1994), Besag, J.E., P.J. Green, D.M. Higdon and K.L. Mengersen (1995) and Knorr-Held and Rainer (2001). For each pixel in the Lexis diagram (that is for a specific age group and specific period) data must be available on the number of persons under risk (population number) and the number of disease cases (typically cancer incidence or mortality). A hierarchical model is assumed with a binomial model in the first-stage.

Lee, J. (2024). Age, Period, and Cohort Analysis With Bounding and Interactions. Sociological Methods & Research, 00491241241266279.

对比了两个新方法的效用