Nonlinear mixed-effect (NLME) models are very useful in many longitudinal studies. In practice, covariates in NLME models may contain missing data, and the missing data may be nonignorable. Likelihood inference for NLME models with missing covariates can be computationally very intensive. We...

Lattice conditional independence (LCI) models (Anderson and Perlman, 1991. Statist. Probab. Lett. 12, 465-486; 1993 Ann. Statist. 21, 1318-1358) can be applied to the analysis of missing data problems with non-monotone missing patterns. Closed-form maximum likelihood estimates can always be...

We measure the green technology innovation efficiency of 288 cities in China from static and dynamic dimensions using the [[EQUATION]] model and [[EQUATION]] Index and employ the "Difference in Difference" (DID) model to evaluate the impact of FTZs construction on green technology innovation...