ABSTRACT: We demonstrate that fixed- and random-effects models for pooled cross-sectional and time series data, and latent growth curve
models for panel data are special cases of a more general model. We compare the estimates obtained from each type of model
for a data set consisting of homicide rates and a vector of explanatory variables for 400 US counties over a 15-year period.
Most, but not all, estimates are similar in the two models. We identify circumstances under which one approach may be advantageous
to the other.
Journal of Quantitative Criminology 04/2012; 24(1):51-72. · 2.12 Impact Factor