How to decentralize categorical variables

1. According to Hou Jietai: the so-called centralization refers to subtracting the mean value of a variable from its expected value. For sample data, each observation value of a variable is subtracted from the sample average value of the variable, and the transformed variable is centralized
for your question, subtract the mean from each measurement.

2. Centralization is to subtract the mean and Z-score is to divide it by the standard deviation. Both of them are centralization methods.

3. Not necessarily, centralization is only for the convenience of explanation, and does not affect the regression coefficients Central treatment of regulatory effect of South Heart Network

4.

According to the data types of independent variables and regulatory variables, it can be divided into the following four situations:

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5. 1. If x is a real 0 and 1 variable, such as gender, treat it as continuous. 4 m # @ + s # N8] 4 E
2. If x is an artificial 0 and 1 variable, such as above average vs. below average, then there is a problem. Because the artificial dichotomy can use any artificial standard. Different methods will seriously affect the results.

6. The coefficient of the interaction factor should be tested for the moderating effect. If the coefficient is significant, the moderating effect can be explained. You should put two variables in the first one and three variables in the second one. The regression method you choose is enter. But instead of putting variables in your order, SPSS adds all the variables you choose to the model and excludes the extra variables ring the first regression, so this table will appear. If you don't want to see this table, you can do the regression twice. The first time you put the center D, center h, and then you put the center D, center HD times h. If you do it twice, you won't have it.