Questionnaire Dwelling Unit-Level and Person Pair-Level Sampling ...

C.3 How to Interpret Collapsing and Dropping of Factor Effects
To help visualize what effects are directly controlled for in our model, one can construct
the table that reflects the collapsing scheme employed. The following is a complex example from
the 2004 person-level modeling.
1. Locate the Factor Effect—Model 9 Person Nonresponse Adjustment:
Three-Factor Effects
Comments
State × Age × Race (3 Levels) Coll. (2,1,2) & (2,1,3); hier. Repeat for all levels of age in State
(2); hier. Drop (3,4,2); sing. Collapse (1,4,2) & (1,4,3); conv.
Drop (3,*,*); conv. Coll. (4,1,2) & (4,1,3); conv. Repeat for all
levels of age in State (4).
2. Determine the initial range of possible levels for the variables by referring to the variable
definitions. See Exhibits C.1 and H.1 for QDU- and pair-level variable definitions. In
addition, the columns "Levels," "Proposed," and "Final" will provide counts of all factor
effects, all explicitly proposed factors, and all explicitly controlled factors, but these are not
necessary for construction of the cross-classification table. The following example is based
upon person-level variables, but the process is the same.
- State (for the model group in question, in this case, Model Group 9)
Model Group 9: 1: Alaska, 2: Hawaii, 3: Oregon, 4: Washington, 5: California 1,2,3
- Age
1: 12 to 17, 2,3 2: 18 to 25, 3: 26 to 34, 4: 35 to 49, 5: 50+ 1
- Race (3 Levels)
1: white, 1,2,3 2: black or African American, 3: other
Note that the superscript numbers indicate the reference level of the variable for a
particular stage of modeling. In our case, the model stage is "Person Nonresponse Adjustment."
3. Construct the cross-classification table.
For example, Race (4 Levels) is defined this way:
Race (4 Levels)
white
Indicates the reference-level set.
black or African
American
Asian
American Indian or
Alaska Native
C-8