Specifically, a formula is used:
Professor Brennan (1998) calculated the attachment style types from the classification coefficient (Fisher linear discriminant formula) based on the sample of 1082 people.
Step 1: Click the calculation function to form four new variables. The calculation formula is:
SEC2 = avoidance * 3.2893296+ anxiety * 5.4725318-1.5307833.
Fear2 = avoidant type c * 7.27 1075+ anxious type * 8. 1448-32. 30867.866668666667
Pre 2 = avoidance * 3.94754+ anxiety * 9.7438+0446-28.1465865851
Dis 2 = avoidance * 7.5438+0+ anxiety * 4.939-22.50000.00000000005
Note: SEC2 stands for security dimension, FEAR2 dimension, PRE stands for concentration dimension and DIS2 stands for indifference dimension. Avoidance is the average score of attachment avoidance dimension (odd addition and subtraction 18), and anxiety is the average score of attachment anxiety dimension (even addition and subtraction 18). Four new variables were formed as a result.
Step 2: 1 Use the compute function to create a new variable named "Safe 1" and enter it into the box on the right "(sec 2 >；; FEAR2) and amp (sec2 & gtpre2)&; (SEC2 & gtDIS2)”。 Click OK to form a new variable "Safe 1" (the result is 0 or 1). The output is as follows:
Computer security1= (sec 2 >; FEAR2) and amp (sec2 & gtpre2)&; (SEC2 & gtDIS2)。
Execute.
2 also use the compute function to create a new variable named "Fear 2" and enter it into the box on the right "(Section 2 >; FEAR2) and amp (sec2 & gtpre2)&; (SEC2 & gtDIS2)”。 Click OK to form a new variable "Fear 2" (the result is 0 or 1), and the output is as follows:
Calculate fear 2 = (fear 2 > sec 2)&; (FEAR2 & gtPRE2)& amp； (FEAR2 & gtDIS2)。
Execute.
3 also use the compute function to create a new variable named "Focus 3" and enter it into the box on the right "(Section 2 >; FEAR2) and amp (sec2 & gtpre2)&; (SEC2 & gtDIS2)”。 Click OK to form a new variable "Focus 3" (the result is 0 or 1), and the output is as follows:
Calculation focus 3=(PRE2 > SEC2)(PRE2 & gtFEAR2) and amp(PRE2 & gtDIS2).
Execute.
4 also use the compute function to create a new variable named "Indifference 4" and enter it into the box on the right "(Section 2 >; FEAR2) and amp (sec2 & gtpre2)&; (SEC2 & gtDIS2)”。 Click OK to form a new variable "Indifference 4" (the result is 0 or 1), and the output is as follows:
Calculation difference 4 = (dis 2 > sec 2)&; (DIS2 & gtFEAR2) and amp(DIS2 & gtPRE2).
Execute.
Note: In short, which dimension the attachment type belongs to has the highest score. Four new variables were formed as a result.
Step 3: Use recode to form the same variable function. The specific process is as follows:
1. Click recode to form the same variable function, click the variable "Fear 2" in the variable box on the right, and then click "New Value and Old Value (O)" for numerical conversion to change 1 into 2. (similar to the function of reverse grading). The output is as follows:
Recode Fear 2 (1=2).
Execute.
2 Click recode to form the same variable function, click the variable "Focus 3" in the variable box on the right, and then click "New Value and Old Value (O)" for numerical conversion to change 1 into 3 (similar to the function of reverse scoring). The output is as follows:
Recode focus 3 (1=3).
Execute.
3 Click recode to form the same variable function, click the variable "Indifference 4" in the variable box on the right, and then click "New Value and Old Value (O)" for numerical conversion to change 1 into 4. (similar to the function of reverse grading). The output is as follows:
Re-encoding indifference 4 (1=4).
Execute.
Finally, click the calculation function to create a new variable "attachment type classification" and enter "security 1+ fear 2+ concentration 3+ indifference 4." Number four. "The output is as follows:
Calculate attachment type classification = security 1+ fear 2+ concentration 3+ indifference 4.
Execute.
5. The formation of four types, using frequency analysis, we can know the distribution of each type of people.