Fixed-effects modeling has become the method of choice in several panel data settings, including models for stochastic frontier analysis. A notable instance of stochastic frontier panel data models is the true fixed-effects model, which allows to disentangle unit heterogeneity from efficiency evaluations. While such a model is theoretically appealing, its estimation is hampered by incidental panel data effects. This note proposes a simple and rather general estimation approach where the unit-specific intercepts are integrated out of the likelihood function. By applying some theory from composite group families, it is demonstrated that the resulting objective function is a marginal likelihood based on sufficient data reduction with desirable inferential properties. The derivation of the result is provided in full, along with some connections with the existing literature and some computational details. The method is illustrated for two notable models: the normal-half-normal specification and the heteroscedastic exponential model. Some simulation results are provided for the latter model.