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  "Title": "Fitting GLMs with Missing Data in Both Responses and Covariates",
  "Description": "Fits generalized linear models (GLMs) when there is\nmissing data in both the response and categorical covariates.\nThe functions implement likelihood-based methods using the\nExpectation and Maximization (EM) algorithm and optionally\napply Firth’s bias correction for improved inference. See\nPradhan, Nychka, and Bandyopadhyay (2025) <https:>, Maiti and\nPradhan (2009) <doi:10.1111/j.1541-0420.2008.01186.x>, Maity,\nPradhan, and Das (2019) <doi:10.1080/00031305.2017.1407359> for\nfurther methodological details.",
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