I completely agree that the development of full-information maximum
likelihood (FIML) estimation for use in packages like lm, lme, lmer, etc.
would make R much more attractive. FIML is better than other approaches to
missing data (e.g., multiple imputation; see Graham, Olchowski, Gilreath,
2007
Does anyone know if someone is developing full-information maximum likelihood
(FIML) estimation algorithms for basic regression functions, like glm()? I
think that having FIML options for workhorse functions that typically use ML
would give R an edge over other statistical software, given how
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