MAPLES (version 1.0)

MAPLES-package: Smoothed age profile estimation.

Description

MAPLES is a general method for the estimation of age profiles that uses standard micro-level demographic survey data. The aim is to estimate smoothed age profiles and relative risks for time-fixed and time-varying covariates.

Details

Package:

MAPLES

Type:

Package

Version:

1.0

Date:

2011-04-08

License:

GPL-2

LazyLoad:

yes

LazyData:

yes

Main functions in the package: - epdata: prepare episode data for event history analysis - splitter: Creates a time-varying factor variables within a episode-data. - ageprofile: Computes smoothed transition rates by respondent's age (age profiles) - plotap: plots age profiles. Utilities: - tabx: Prints univariate or a bivariate frequency distribution table including marginal distribution and total number of cases. - tabm: Print regression estimates for previously fitted linear and logit regression models. - mkdate: computes dates in continuous years or CMC. - listvar: shows variables in a dataframe.

References

Impicciatore R. and Billari F.C., (2010), MAPLES: a general method for the estimation of age profiles from standard demographic surveys (with an application to fertility), DEAS WP, http://ideas.repec.org/p/mil/wpdepa/2010-40.html

Examples

# creates an episode-data structure relating to the transition 
# childless-->first child
ep1<-with(demogr,epdata(start=dbirth, event=dch1, rcensor=dint, 
          birth=dbirth,id=id,
          addvar=subset(demogr,select=c(-id,-dbirth)))) 

# creates a new episode-data structure with a time-varying factor 
# variable relating to the status "never married" (not_marr) or 
# "ever married" (marr)  
ep2<-splitter(ep1,split=ep1$d1marr,tvar.lev=c("not_marr","marr"),
              tvar.name="mar")

# Estimates age profiles for the transition to the first birth 
# according to the following factors: 
# sex (respondent'sex w/2 levels: 'Male', 'Female');
# edu ('Level of education w/3 levels: 'low_sec','upp_sec', 'tert');
# mar (ever married w/2 levels: 'not_marr', 'marr') 

ch1.ap<-ageprofile(formula=~sex+edu+mar, epdata=ep2, 
                   tr.name="First child", agelimits=c(15,50))        

# Plot age profiles in three different graphs
plotap(ch1.ap,base=TRUE, unsmoo=TRUE,
        lev=c("Male","Female"),title='first child by sex')
plotap(ch1.ap,base=TRUE, unsmoo=TRUE,
        lev=c("low_sec","upp_sec","tert"),title='first child by education')
plotap(ch1.ap,base=TRUE, unsmoo=TRUE,
        lev=c("not_marr","marr"),title='first child by marital status', 
        ylim=0.4)