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Census Processing Procedures

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2. English Translation. 8. Dissemination. 6. Data ... a) Data translation matrices. b) Specialized variable programming. Where one-to-one recoding ... – PowerPoint PPT presentation

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Title: Census Processing Procedures


1
Census Processing Procedures
Matt Sobek
Minnesota Population Center
Funded by the National Science Foundation
2
IPUMS Work Process
1. Inventory
2. English Translation
3. Data Restructuring
4. Sample Creation
5. Confidentiality Measures
6. Data Harmonization
7. Data Improvement
8. Dissemination
3
IPUMS Work Process
  • For each sample
  • data
  • data dictionary
  • census questionnaire and instructions
  • sample design
  • census design
  • published tabulations, post-enumeration
  • surveys, demographic analyses
  • (when available)

1. Inventory
2. Translation
3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
7. Data Improvement
8. Dissemination
4
IPUMS Work Process
1. Inventory
2. Translation
  • Census questionnaire
  • Census instructions
  • Data dictionary codes and labels

3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
7. Data Improvement
8. Dissemination
5
IPUMS Work Process
1. Inventory
2. Translation
a) Create labels/set-up file
3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
7. Data Improvement
8. Dissemination
6
Labels File, Costa Rica 2000
7
IPUMS Work Process
1. Inventory
2. Translation
a) Create labels/set-up file
3. Data Restructuring
b) Analyze data
4. Sample Creation
  • Basic record structure

5. Confidentiality
  • Unique IDs or other means
  • of distinguishing household
  • membership

6. Harmonization
7. Data Improvement
8. Dissemination
8
IPUMS Work Process
1. Inventory
2. Translation
a) Create labels/set-up file
3. Data Restructuring
b) Analyze data
4. Sample Creation
  • Basic record structure

5. Confidentiality
  • Unique IDs or other means
  • of distinguishing household
  • membership

6. Harmonization
7. Data Improvement
8. Dissemination
c) Reformat the data
  • Convert to household-person
  • hierarchical structure

9
Reformat Rectangular Sample
(Person records only household data duplicated
on person records)
(Brazil 1980)
10
Reformat Dwelling-Household-Person Sample
(Separate dwelling and household records)
(Chile 1992)
11
Reformat Dwelling-Person Sample
(Multi-household dwellings no separate household
record)
(Colombia 1993)
12
Merge Separate Household and Person Files
Household File
Person File
(Brazil 2000)
13
Reformat Individual-level Data
(Individuals only not organized in households)
(Mexico 1960)
14
IPUMS Work Process
1. Inventory
2. Translation
a) Create labels/set-up file
3. Data Restructuring
b) Analyze data
4. Sample Creation
  • Basic record structure

5. Confidentiality
  • Unique IDs or other means
  • of distinguishing household
  • membership

6. Harmonization
7. Data Improvement
8. Dissemination
c) Reformat the data
  • Convert to household-person
  • hierarchical structure

d) Identify and flag errors in structure
15
Flags Identifying Structural Issues, Chile 1970
16
IPUMS Work Process
1. Inventory
a) Formerly, systematic samples
2. Translation
  • We developed a household-
  • substitution technique to exclude
  • corrupt records during sampling

3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
7. Data Improvement
8. Dissemination
17
Sampling Procedure Colombia 1973
Take
Take
No
No
Take
No
Take
18
IPUMS Work Process
1. Inventory
a) Formerly, systematic samples
2. Translation
  • We developed a household-
  • substitution technique to exclude
  • corrupt records during sampling

3. Data Restructuring
4. Sample Creation
5. Confidentiality
b) Stratified samples
6. Harmonization
  • Variables for variance estimation

7. Data Improvement
8. Dissemination
  • Develop strata for each sample
  • using geography, ethnicity, hh size,
  • hh type, socioeconomic status
  • adjusted as necessary for census

19
IPUMS Work Process
1. Inventory
2. Translation
3. Data Restructuring
5 measures, as required
4. Sample Creation
5. Confidentiality
  • Limit geographic specificity

6. Harmonization
  • Swap across geographic units

7. Data Improvement
  • Randomize order within geographies

8. Dissemination
  • Merge small variable categories
  • Top-code sensitive numeric variables

20
IPUMS Work Process
1. Inventory
2. Translation
3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
a) Data translation matrices
7. Data Improvement
8. Dissemination
21
Translation Matrix Marital Status
22
Translation Matrix Marital Status
23
Translation Matrix Marital Status
24
Translation Matrix Marital Status
25
IPUMS Work Process
1. Inventory
2. Translation
3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
a) Data translation matrices
7. Data Improvement
b) Specialized variable programming
8. Dissemination
  • Where one-to-one recoding
  • of the translation matrix is
  • insufficient

26
IPUMS Work Process
1. Inventory
2. Translation
3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
a) Constructed variables
7. Data Improvement
  • Family structure and
  • other derived variables

8. Dissemination
  • Location of mother, father
  • and spouse

27
IPUMS Pointer Variables
(Simple household)
Spouses
2
1
0
0
0
0
Mothers
Fathers
0
0
0
0
0
0
2
1
1
2
1
2
(Colombia 1985)
28
IPUMS Pointer Variables
(Complex household)
Spouses
Fathers
Mothers
0
0
0
0
0
0
0
0
0
6
0
5
0
0
0
5
6
0
5
6
0
0
0
0
9
0
0
9
0
(Colombia 1985)
29
IPUMS Work Process
1. Inventory
2. Translation
3. Data Restructuring
4. Sample Creation
5. Confidentiality
6. Harmonization
a) Constructed variables
7. Data Improvement
Location of mother, father, and spouse.
8. Dissemination
Family structure and other derived variables.
b) Data editing and missing data allocation
30
Missing Data Allocation Occupation Script
OCC allocated when 975, 996, 998
sex (2 categories) 1 2
empstat (3 categories) 10-19 20-29 30-39
classwkr (3 categories) 10-19 20-29 99
age (6 categories) 10-19 20-29 30-39 40-49
50-59 60-126
race (3 categories) 100-199 200-299 300-899
(USA pre-1940 samples)
31
IPUMS Work Process
1. Inventory
a) Metadata
2. Translation
  • Static pages

3. Data Restructuring
  • Dynamic pages

4. Sample Creation
  • Translation matrices

5. Confidentiality
  • Control files

6. Harmonization
7. Data Improvement
8. Dissemination
32
IPUMS Work Process
1. Inventory
a) Metadata
2. Translation
  • Static pages

3. Data Restructuring
  • Dynamic pages

4. Sample Creation
  • Translation matrices

5. Confidentiality
  • Control files

6. Harmonization
b) Dissemination Programming
7. Data Improvement
  • Documentation system

8. Dissemination
  • Extract interface (front end)
  • Extract engine (back end)
  • On-line data analysis

33
End
Matt Sobek sobek_at_pop.umn.edu
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