When the values of the outcome variable Y are either 0 or 1, the function lsm() calculates the estimation of the log likelihood in the saturated model. This model is characterized by Llinas (2006, ISSN:23898976) in section 2.3 through the assumptions 1 and 2. The function LogLik() works (almost perfectly) when the number of independent variables K is high, but for small K it calculates wrong values in some cases. For this reason, when Y is dichotomous and the data are grouped in J populations, it is recommended to use the function lsm() because it works very well for all K.
Package details 


Author  Humberto Llinas [aut], Omar Fabregas [aut], Jorge Villalba [aut, cre] 
Maintainer  Jorge Villalba <[email protected]> 
License  MIT + file LICENSE 
Version  0.1.7 
URL  https://github.com/jlvia1191/lsm 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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