Regression quantiles for panel data (longitudinal data)

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Description

The rqpd package provides quantile regression estimation routines and bootstrap inference for panel (longitudinal) data. Currently, the available estimation methods are the penalized fixed-effects model (Koenker, 2004) and a correlated-random-effects type model. (Abrevaya and Dahl, 2008; Bache et al. 2011).

Details

Package: rqpd
Type: Package
Version: 0.5
Date: 2011-04-26
License: GPL >= 2.0
LazyLoad: yes
LazyData: yes

Author(s)

Roger Koenker and Stefan Holst Bache

Maintainer: Stefan Holst Bache <pdqr@stefanbache.dk>

References

[1] Abrevaya, Jason and Christian M. Dahl. 2008. The effects of birth inputs on birthweight. Journal of Business and Economic Statistics. 26-4. Pages 379–397.

[2] Bache, Stefan Holst; Christian M. Dahl; Johannes Tang Kristensen. 2011. Headlights on tobacco road to low birthweight–Evidence from a battery of quantile regression estimators and a heterogeneous panel.

[3] Koenker, Roger. 2004. Quantile regression for longitudinal data. Journal of Multivariate Analysis. 91-1. Pages 74–89.

Examples

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data(bwd)

### A fixed-effects model:

# formula is specified as
fe.form <- dbirwt ~ smoke + dmage + agesq + 
   novisit + pretri2 + pretri3 | as.factor(momid3) 

# estimate the model:
fe.fit <- rqpd(fe.form, panel(lambda=0.5), data=bwd)

### A CRE model:

# formula is specified as
cre.form <- dbirwt ~ smoke + dmage + agesq + 
   novisit + pretri2 + pretri3 | momid3 | smoke + 
   dmage + agesq

# estimate the model:
cre.fit <- rqpd(cre.form, panel(method="cre"), data=bwd)