One of the variables (Gender) is categorical. It uses three variables to describe 10 students. Variable is treated just like any other quantitative variable.Ĭonsider the table below. The categorical variable is expressed in dummy form, the analysis proceeds in routine fashion. The example begins with two independent variables - one quantitative and one categorical. In this section, we work through a simple example to illustrate the use of dummy variables in regression analysis. Statistically significant, the income discrepancy with the reference group is also statistically The reference group a negative regression coefficient means Means that income is higher for the dummy variable political affiliation than for In this example, a positive regression coefficient In analysis, each dummy variable is compared with the reference group. In this example, the reference group consists of Independent voters. The value of the categorical variable that is not represented explicitly by a dummy X 1Īnd X 2 are regression coefficients defined as: Where b 0, b 1, and b 2 are regression coefficients. Regression analysis just like any other quantitative variable.įor example, suppose we wanted to assess the relationship between household income and politicalĪffiliation (i.e., Republican, Democrat, or Independent). Once a categorical variable has been recoded as a dummy variable, the dummy variable can be used in Using k dummy variables when only k - 1 dummy variablesĪre required is known as the dummy variable trap. Remember, youĪ k th dummy variable is redundant it carries no new information. If a categorical variableĬan take on k values, it is tempting to define k dummy variables. When defining dummy variables, a common mistake is to define too many variables. Voter is neither Republican nor Democrat. If X 1 equals zero and X 2 equals zero, we know the In this example, notice that we don't have to create a dummy variable to represent the "Independent" category X 2 = 1, if Democrat X 2 = 0, otherwise.X 1 = 1, if Republican X 1 = 0, otherwise.Might assume three values - Republican, Democrat, or Independent. That can assume k different values, a researcher would need to define k - 1įor example, suppose we are interested in political affiliation, a categorical variable that The number of values that the categorical variable can assume. The number of dummy variables required to represent a particular categorical variable depends on Typically, 1 represents the presence of a qualitative Variables are limited to two specific values, 1 or 0. As a practical matter, regression results are easiest to interpret when dummy Their range of values is small they can take Technically, dummy variables are dichotomous, quantitative variables.
To the analysis is to express categorical variables as dummy variables.Ī dummy variable (aka, an indicator variable) is a numeric variable that represents categoricalĭata, such as gender, race, political affiliation, etc.
#HOW TO USE DUMMY VARIABLES IN EVIEWS 10 HOW TO#
In this lesson, we show how to analyze regression equations when one or more independent variables are Discriminant Analysis Dummy Variables in Regression.Linear Regession: Table of Contents Introduction