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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
Time-use data
Regression models
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
Keywords: Surveys and Survey Methodology
Research collection: Journal Articles
Appears in Collections:Journal Articles

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