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  "Package": "multpois",
  "Title": "Analyze Nominal Response Data with the Multinomial-Poisson Trick",
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  "Authors@R": "person(\"Jacob O.\", \"Wobbrock\", , \"wobbrock@uw.edu\", role = c(\"aut\", \"cre\",\"cph\"),\ncomment = c(ORCID = \"0000-0003-3675-5491\"))",
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  "Description": "Dichotomous responses having two categories can be\nanalyzed with stats::glm() or lme4::glmer() using the\nfamily=binomial option. Unfortunately, polytomous responses\nwith three or more unordered categories cannot be analyzed\nsimilarly because there is no analogous family=multinomial\noption. For between-subjects data, nnet::multinom() can address\nthis need, but it cannot handle random factors and therefore\ncannot handle repeated measures. To address this gap, we\ntransform nominal response data into counts for each\ncategorical alternative. These counts are then analyzed using\n(mixed) Poisson regression as per Baker (1994)\n<doi:10.2307/2348134>. Omnibus analyses of variance can be run\nalong with post hoc pairwise comparisons. For users wishing to\nanalyze nominal responses from surveys or experiments, the\nfunctions in this package essentially act as though\nstats::glm() or lme4::glmer() provide a family=multinomial\noption.",
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