It may range from 0.
Lambda provides us with an indication of the strength of the relationship between independent and dependent variables. To calculate lambda, you need two numbers: E1 and E2. E1 is the error of prediction made when the independent variable is ignored. To find E1, you first need to find the mode of the dependent variable and subtract its frequency from N. E2 is the errors made when the prediction is based on the independent variable.
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To find E2, you first need to find the modal frequency for each category of the independent variables, subtract it from the category total to find the number of errors, then add up all the errors. Lambda may range in value from 0. Zero indicates that there is nothing to be gained by using the independent variable to predict the dependent variable. In other words, the independent variable does not, in any way, predict the dependent variable.
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A lambda of 1. That is, by using the independent variable as a predictor, we can predict the dependent variable without any error.
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Gamma is defined as a symmetrical measure of association suitable for use with ordinal variable or with dichotomous nominal variables. It can vary from 0.
Whereas lambda is an asymmetrical measure of association, gamma is a symmetrical measure of association. This means that the value of gamma will be the same regardless of which variable is considered the dependent variable and which variable is considered the independent variable.
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The direction of the relationship between ordinal variables can either be positive or negative. With a positive relationship, if one person ranked higher than another on one variable, he or she would also rank above the other person on the second variable. My profile My library Metrics Alerts.
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