• A
• A
• A
• ABC
• ABC
• ABC
• А
• А
• А
• А
• А
Regular version of the site

# Elimination of multicollinearity in the binary logistic regression model

Student: Oleg Yaksin

Supervisor:

Educational Programme: Bachelor

<p>Binary Logistic regression model is the type of a regression model that estimates the probability of the belonging of an object to one of two classes. It is widely used in medicine, credit score, sociologic researches and other currently central areas.</p><p>The multicollinearity is the situation when some factors of regression model have high dependences, this fact can lead to a bad conditionality of a sampling matrix (a learning sample).Corrolary is that estimations of model parametric variables are labile, has big variances and signs that are in contrast to the theory.</p><p>In this paper Principal Component Analysis (PCA) is used to eliminate multicollinearity. The main idea of it is to find linear combinations of the factors called principal components that don&rsquo;t correlate among themselves at all. To evaluate principal components the covariance (corraletion) matrix of regressors is needed to be defined. The research of paper is based on method of forming a correlation matrix using Kramer and association coefficients. Using these coefficients is explained by that regressors can be nominal or have high linear or nonlinear dependences, that correlation coefficient identifies inaccurately.</p><p>With the help of modeled and real data it is shown that using method of the research in binary logistic regression model provides better predictive capability than models that don&rsquo;t use this method.</p>

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.