the reference answer GPT ᴼ ᴾ ᴱ ᴺ ᴬ ᴵ < br / > when the binary logistic regression analysis, multiple choice to virtual variable(dummy variable), For example, for a multiple choice with three choices, it can be converted into three binary variables, indicating that the first choice, the second choice and the third choice are selected respectively, and then binary logistic regression analysis is carried out respectively. Therefore, it can be analyzed as a single choice.
However, it should be noted that each choice of multiple choice can be selected independently or not. In binary logistic regression, the value of each binary variable can only be 0 or 1, so it is necessary to consider the correlation between the options. If there is A strong correlation between the options, such as people who choose option A are more likely to choose option B, then multicollinearity problems may result when regression analysis is performed, affecting the accuracy of the results.
When explaining the degree of influence of variables on dependent variables, the positive and negative of the coefficient can be used to represent the positive or negative influence of corresponding options on dependent variables, and the size of the coefficient can represent the degree of influence. However, it should be noted that the influence of other variables should be controlled to avoid the error correlation problem when making causal inference.
