Please use this identifier to cite or link to this item: https://hdl.handle.net/10620/17363
Longitudinal Study: LSAC
Title: Comparisons of Tobit, Linear, and Poisson-Gamma Regression Models : An Application of Time Use Data
Authors: Dunn, P.K.
Brown, J.E. 
Publication Date: 29-Jul-2011
Pages: 511-535
Keywords: Linear
Tobit
Time-use data
Regression models
Poisson-gamma
Abstract: Time use data (TUD) are distinctive, being episodic in nature and consisting of both continuous and discrete (exact zeros) values. TUD is non-negative and generally right skewed. To analyze such data, the Tobit, and to a lesser extent, linear regression models are often used. Tobit models assume the zeros represent censored values of an underlying normally distributed latent variable that theoretically includes negative values. Both the linear regression and Tobit models have normality as a key assumption. The Poissongamma distribution is a distribution with both a point mass at zero (corresponding to zero time spent on a given activity) and a continuous component. Using generalized linear models, TUD can be modeled utilizing the Poisson-gamma distribution. Using TUD, Tobit and linear regression models are compared to the Poisson-gamma with respect to the interpretation of the model, the model fit (analysis of residuals), and model performance through the use of a simulated data experiment. The Poisson-gamma is found to be theoretically and empirically more sound in many circumstances.
DOI: 10.1177/0049124111415370
URL: https://journals.sagepub.com/doi/abs/10.1177/0049124111415370
Keywords: Surveys and Survey Methodology
Research collection: Journal Articles
Appears in Collections:Journal Articles

Show full item record

Page view(s)

1,562
checked on Feb 29, 2024
Google icon

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.