A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables.
Australian National University · University of Illinois Urbana-Champaign
Abstract
Uncorrectable skew and heteroscedasticity are among the "lemons" of psychological data, yet many important variables naturally exhibit these properties. For scales with a lower and upper bound, a suitable candidate for models is the beta distribution, which is very flexible and models skew quite well. The authors present maximum-likelihood regression models assuming that the dependent variable is conditionally beta distributed rather than Gaussian. The approach models both means (location) and variances (dispersion) with their own distinct sets of predictors (continuous and/or categorical), thereby modeling heteroscedasticity. The location sub-model link function is the logit and thereby analogous to logistic…
Citation impact
- FWCI
- 10.37
- Percentile
- 100%
- References
- 60
Authors
2Topics & keywords
- Heteroscedasticity
- Categorical variable
- Statistics
- Mathematics
- Econometrics
- Skew
- Regression analysis
- Logistic regression