1 1 A two-phase life-cycle model of integrated statistical micro data Li-Chun Zhang Statistics Norway

2 Register-based statistics & early years of survey sampling N. Kiær (1895). The representative method. ISI Session, Bern. A. Jensen (ISI-committee, 1924): “When ISI discussed the matter twentytwo years ago, it was the question of the recognition of the method in principle that claimed most interest. Now it is otherwise. I think I may venture to say that nowadays there is hardly one statistician, who in principle will contest the legitimacy of the representative method. Nevertheless, I believe that the representative method is capable of being used to a much greater extent than now is the case.” 20?? J. Neyman (1934). On the two different aspects of the representative method: The method of stratified sampling and the method of purposive selection. JRSS 97, (Source: UNECE 2007)

3 Survey life cycle from a quality perspective (Groves et al., 2004, Survey Methodology, Figure 2.5) Construct Measurement Response Edited Response Target Population Sampling frame Sample Postsurvey Adjustments Survey Statistic MeasurementRepresentation Validity Measurement Error Processing Error Coverage Error Sampling Error Adjustment Error Respondents Nonresponse Error

4 A two-phase life-cycle model -Secondary use -Combination of sources

5 Single-source primary-phase statistical micro data Target Concept Measurement Response/ Registration Editing Target Set Accessible Set Accessed Set Observed/ Validated Set Single-source Micro Data (Primary) Measurement (Variables) Representation (Objects) Validity Measurement Processing Frame Selection Missing/ Redundancy

6 Integrated secondary-phase statistical micro data Target Concept Harmonization Classification Adjustment Target Population Data Linkage Alignment Statistical Units Integrated Micro Data (Secondary) Measurement (Variables) Representation (Units) Relevance Mapping Compatibility Coverage Identification Unit Transformation (Object to Unit) Unit vs. Object Measurement vs. Representation Missing Values vs. Coverage Base Unit No. 1 Base Unit No. 2 Base Unit No. N Composite Unit No. 1 Composite Unit No. 2 Composite Unit No. M Composite Unit No. 1 Composite Unit No. 2 Composite Unit No. K m:1 Composite Unit No. 1 Composite Unit No. 2Composite Unit No. H m:1

7 An illustration of register-based household data: Kongsvinger at the time point of census 2001

8 Representing unit error by allocation matrix (Equivalence on row permutation & sequential upper-triangular by definition)

9 Value matrix (or vector): X Statistics: y = A X

10 Two more examples of statistics

11 Results: Statistical uncertainty w.r.t. unit errors

12 The 20th Century = Survey Sampling The 21th Century = Data Integration Welcome to a new age!