Multinomial and ordinal logistic regression using PROC LOGISTIC
نویسنده
چکیده
Logistic regression may be useful when we are trying to model a categorical dependent variable (DV) as a function of one or more independent variables. This paper reviews the case when the DV has more than two levels, either ordered or not, gives and explains SAS R © code for these methods, and illustrates them with examples.
منابع مشابه
Using the Proportional Odds Model for Health-Related Outcomes: Why, When, and How with Various SAS® Procedures
Health-related outcomes often possess an intrinsic ordering but fail to meet the assumptions usually needed to perform an ordinary least-squares (OLS) regression. When the distribution of scores is highly non-normal, as occurs when the majority of respondents score at the very bottom or top of the scale, ordinal regression can be more valid, and sometimes more informative, than OLS regression. ...
متن کاملStereotype Ordinal Regression
There are a number of reasonable approaches to analysing an ordinal outcome variable. One common approach, known as the Proportional Odds (PO) Model, is implemented in Stata as ologit. If the assumptions of the PO model are not satisfied, an alternative is to treat the outcome as categorical, rather than ordinal, and use multinomial logistic regression (mlogit) in Stata. This insert describes a...
متن کاملLog-Link Regression Models for Ordinal Responses
The adjacent-categories, continuation-ratio and proportional odds logit-link regression models provide useful extensions of the multinomial logistic model to ordinal response data. We propose fitting these models with a logarithmic link to allow estimation of different forms of the risk ratio. Each of the resulting ordinal response log-link models is a constrained version of the log multinomial...
متن کاملOrdinal logistic regression.
©FSRH J Fam Plann Reprod Health Care 2008: 34(3) What is it? When a response variable has only two possible values (e.g. recurrence/not), binary logistic regression is commonly used to test or model the association between that response and a number of potential explanatory variables, with each association estimated in terms of an odds ratio (OR). Multinomial logistic regression is an extension...
متن کاملMultilevel Modeling of Categorical Response Variables
Data ......................................................................................................................483 Response and Explanatory Variables ..........................................................483 Weights ............................................................................................................484 Missing Data ...........................................
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2005