apc: Age-Period-Cohort Analysis

Functions for age-period-cohort analysis. The data can be organised in matrices indexed by age-cohort, age-period or cohort-period. The data can include dose and response or just doses. The statistical model is a generalized linear model (GLM) allowing for 3,2,1 or 0 of the age-period-cohort factors. The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) <DOI:10.1093/biomet/asn026> is used. Thus, the analysis does not rely on ad hoc identification.

AuthorBent Nielsen
Date of publication2016-12-01 08:28:22
MaintainerBent Nielsen <bent.nielsen@nuffield.ox.ac.uk>

View on CRAN

Man pages

apc_1.3-package: Age-period-cohort analysis

apc.data.list: Arrange data as an apc.data.list

apc.data.list.subset: Cut age, period and cohort groups from data set.

apc.data.sums: Computes age, period and cohort sums of a matrix

apc.fit.model: Fits an age period cohort model

apc.forecast: Forecasts from age-period-cohort models.

apc.forecast.ac: Forecast for Poisson response model with AC structure.

apc.forecast.ap: Forecast for Poisson response model with AP structure.

apc.forecast.apc: Forecast models with APC structure.

apc.get.design: Create design matrices

apc.get.index: Get indices for mapping data into trapezoid formation

apc.identify: Identification of time effects

apc.plot.data.all: Make all descriptive plots.

apc.plot.data.level: Level plot of data matrix.

apc.plot.data.sparsity: This plot shows heat map of the sparsity of a data matrix.

apc.plot.data.sums: This plot shows sums of data matrix by age, period or cohort.

apc.plot.data.within: This plot shows time series of matrix within age, period or...

apc.plot.fit: Plots of apc estimates

apc.plot.fit.all: Make all fit plots.

apc.plot.fit.pt: Plot probability transform of responses given fitted values

apc.plot.fit.residuals: Level plots of residuals / fitted values / linear predictors

apc.polygon: Add connected line and standard deviation polygons to a plot

data.aids: UK aids data

data.asbestos: Asbestos data

data.Belgian.lung.cancer: Belgian lung cancer data

data.Italian.bladder.cancer: Italian bladder cancer data

data.Japanese.breast.cancer: Japanese breast cancer data

data.loss.BZ: Motor data

data.loss.TA: Motor data

data.loss.VNJ: Motor data

data.RH.mortality: 2-sample mortality data.

data.US.prostate.cancer: Japanese breast cancer data

internal: Internal apc Functions

vector.2.triangle: Organise vector as matrix with triangle structure

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.