Introduction to statistical modelling 2: categorical variables and interactions in linear regression
نویسندگان
چکیده
منابع مشابه
Review Introduction to statistical modelling: linear regression
In many studies we wish to assess how a range of variables are associated with a particular outcome and also determine the strength of such relationships so that we can begin to understand how these factors relate to each other at a population level. Ultimately, we may also be interested in predicting the outcome from a series of predictive factors available at, say, a routine clinic visit. In ...
متن کاملLinear latent structure analysis and modelling of multiple categorical variables
Linear latent structure analysis is a new approach for investigation of population heterogeneity using high-dimensional categorical data. In this approach, the population is represented by a distribution of latent vectors, which play the role of heterogeneity variables, and individual characteristics are represented by the expectation of this vector conditional on individual response patterns. ...
متن کاملIntroduction to Generalized Linear Modelling
Preliminary statement. When I first wrote my lecture notes for the Part II course, Sarah Shea–Simonds very kindly typed the core notes in TeX, and I added to them bit by bit, again in TeX. However, my style was still rather like a telegram, partly as I was trying to save on paper. Now that I am retired, I have time to retype the notes in LaTeX. I have tried to make the style rather more ‘flowin...
متن کاملIntroduction to Generalized Linear Modelling
Preliminary statement. When I first wrote my lecture notes for the Part II course, Sarah Shea– Simonds very kindly typed the core notes in TeX, and I added to them bit by bit, again in TeX. However, my style was still rather like a telegram, partly as I was trying to save on paper. Now that I am retired, I have time to retype the notes in LaTeX. I have tried to make the style rather more ‘flowi...
متن کاملRole of Categorical Variables in Multicollinearity in the Linear Regression Model
The present article discusses the role of categorical variable in the problem of multicollinearity in linear regression model. It exposes the diagnostic tool condition number to linear regression models with categorical explanatory variables and analyzes how the dummy variables and choice of reference category can affect the degree of multicollinearity. Such an effect is analyzed analytically a...
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ژورنال
عنوان ژورنال: Rheumatology
سال: 2013
ISSN: 1462-0324,1462-0332
DOI: 10.1093/rheumatology/ket172