Use logistic regression to model a binomial, multinomial or ordinal variable using quantitative and/or qualitative explanatory variables.
Multinomial logistic regression is an extension of this approach to situations where the response variable is categorical and has more than two possible values. Ordinal logistic regression is a special type of multinomial regression, which can be advantageous when the response variable is ordinal. [...
Multinomial logistic regression: This is similar to doing ordered logistic regression, except that it is assumed that there is no order to the categories of the outcome variable (i.e., the categories are nominal). The downside of this approach is that the information contained in the ordering ...
We can perform a similar analysis for data in raw format. When data is in raw format, then we have two choices. The first of these choices is to use theOLogitSummaryarray function to convert the data from raw format to summary format and then use theOrdinal Regressiondata analysis tool, ...
Multinomial logistic regression: This is similar to doing ordered logistic regression, except that it is assumed that there is no order to the categories of the outcome variable (i.e., the categories are nominal). The downside of this approach is that the information contained in the ordering ...
over-dispersion. As a result, we rely on the multinomial distribution as the basis of our model and we hypothesize that an ordered multinomial probit model (MN model), also known as an ordinal regression model, can represent a wide range of regression models (i.e., conditional distributions)...
Shouldyousubstitutesomesortofscale(forexample,numbers1to5)andpretendthevariablesareinterval?Shouldyouusesomeothertransformationofthevalueshopingtocapturesomeofthatextrainformationintheordinalscale?Whenyourdependentvariableisordinalyoualsofaceaquandary.Youcanforgetabouttheorderingandfitamultinomiallogitmodelthatignoresany...
Campbell M, Donner A: Classification efficiency of multinomial logistic regression relative to ordinal logistic regression. Journal of the American Statistical Association. 1989, 84: 587-591. 10.2307/2289946. Article Google Scholar Vaupel J, Manton K, Stallard E: The Impact of Heterogeneity in Indiv...
Imagine I have use the logit link, and plotted the cumulative curves corresponding to 3 classes with a series of binomial regressions (first case), then I applied multinomial and ordinal regressions (cases 2 and 3, say for 4 classes, one of which is a reference class - n...
Classical categorical regression models such as the multinomial logit and proportional odds models are shown to be readily handled by the vector generalize... TW Yee - 《Journal of Statistical Software》 被引量: 502发表: 2010年 Regression Models for Ordinal Data [R package ordinal version 2015.6-...