Individual fixation effect refers to controlling the influence of individual invariant factors on dependent variables when analyzing individual data. These constant factors may include gender, age, education level, etc. In heterogeneity analysis, individual fixation effect can be realized by introducing dummy variables. Virtual variables refer to the transformation of classified variables into binary variables, for example, the transformation of gender variables into male and female virtual variables. By introducing dummy variables, we can better control the differences between individuals and analyze the influence of independent variables on dependent variables more accurately.
Therefore, if the individual gaze effect is not added, the results may be biased and inaccurate. In heterogeneity analysis, individual fixation effect should be introduced as much as possible to obtain more accurate results and more reliable conclusions.
In practical analysis, we can use Stata, R and other statistical software to introduce the individual gaze effect. The specific method can be set according to the requirements of different software. At the same time, when introducing the individual gaze effect, we should also pay attention to controlling other possible influencing factors in order to obtain more accurate results.
In a word, it is very important to add the individual fixation effect when analyzing the heterogeneity of individuals, which can better control the differences between individuals and obtain more accurate results and conclusions.