A procedure in regression analysis where Predictor or Independent Variables are coded as 1 or 0 (representing categories) and can be used to produce ANOVA Tables under the General Linear Model is known as…?

I think you are referring to "dummy coding" but you may want to check this.

The procedure you are referring to is called "dummy coding" or "indicator coding" in regression analysis. Dummy coding is used when you have categorical predictor variables that need to be included in a regression model. It involves representing each category of a predictor variable as a dichotomous (binary) variable, with values of 1 or 0 indicating the presence or absence of that category.

To perform dummy coding, you need to follow these steps:

1. Identify the categorical variable in your dataset that you want to include as a predictor in the regression analysis.
2. Determine the number of categories or levels within that variable.
3. Create a set of binary (dummy) variables, equal to the number of categories minus one. For example, if you have a variable with three categories (A, B, C), you would create two binary variables (A vs. B and A vs. C).
4. Assign a value of 1 to the category you want to use as the reference or baseline category, and assign a value of 0 to the other categories.
5. Include the created dummy variables as independent variables in your regression model.

By using dummy coding, you can then perform regression analysis and obtain ANOVA tables under the General Linear Model framework, which allows you to assess the significance of the categorical variables in predicting the outcome variable.