SOC200 - The Elaboration Model (Chapter 15 + 16) Flashcards
The Elaboration Model
Elaboration Paradigm, The Interpretation Method, the Lazarsfeld Method; the Columbia School Method
logical approach used for understanding relationship betw two variables
The Elaboration Model
observing impact on other variables when third variable (a “control/test” variable) is introduced.
The Central Logic of the Elaboration Model
observed relationship betw 2 variables + hunch that one variable is causing other
Think of 3rd variable then divide sample into groups based on the categories in that third variable
The Central Logic of the Elaboration Model
students and non-students
for each subgroup, recompute relationship betw 2 original variables
The Central Logic of the Elaboration Model
Partial Table – partialing out relationship betw 2 variables via 3rd variable
compare relationship exhibited in partial (3-way) table with relationship in the zero-order relationship (2-way table)
The Central Logic of the Elaboration Model
Partial Relationships: full-time/part time + student status
Compare relationship with relationship in zero order
Regardless of student status – larger % of part time still female
The Central Logic of the Elaboration Model
Zero-order relationship: without added 3rd variable
student status – lot of students work part time
Zero order relationship for students are reduced
Student status is important as well
Relationship betw male + female for not a student about same as zero order
The Central Logic of the Elaboration Model
However, student status is also important: Compared to the non-student group, % of PT workers is much higher in the student group, regardless of sex
diff betw sexes smaller in PT category (was 14% now 9%)
An Elaboration Analysis is Guided by the Type of Test Variable: Intervening Test Variable (not prior in time to the IV and DV)
test variable affects way iv affects dv
Student Status
An Elaboration Analysis is Guided by the Type of Test Variable: Antecedent Test Variable (prior in time to the IV and DV)
iv + dv not actually related appear to show relationship, affected by a test variable directly affecting both
Sex affects both IV + DV
Types of relationships shown when partial table is compared against original table
Summary of potential outsomes in elaboration analysis
Antecedent:
Same relationship: replication
Smaller relationship: explanation
Replication
Relationship betw sex + PT status substantially same for students and non-students.
zero-order relationship: 11.4% of M + 25.4% of F PT – diff of about 14%
Numbers might change, but diff doesn’t change
Replication because numbers don’t change
Explanation
original relationship shrinks/made nonexistent in both partial relationships after introducing test variable
test variable logically precedes IV + DV (antecedent variable)
assumes relationship betw student & PT status is preceded by sex
Because relationship betw student status + part time status shrunk, we would call this an explanation
Interpretation
Like explanation except test variable does not precede IV + DV
Relationship shrunk from zero-order relationship
Interpretation
relationship betw sex + PT status genuine one, but substantially shrinks because student status (intervening variable) helps interpret mechanism through which sex “causes” PT status
Specification
When partial relationships differ significantly from each other (one same as/stronger than original table + other is less than original table/reduced to zero
Specification
Among non student no diff from original table
Among students shrunk to almost no diff
Non student doesn’t explain anything
Student status only explains relationship betw iv + dv
Suppression
3rd variable hiding relationship betw bivariate relationship
No diff betw M + F working Δ = 1.4%
BUT expected difference appears after controlling for student status Δ = 31% for each partial
