Subject oriented approach to the «battle» with the missing data in typological analysis


Tatarova G.G.

Dr. Sci. (Soc.), Prof., Chief Researcher, Institute of Sociology, Federal Center of Theoretical and Applied Sociology, Russian Academy of Sciences, Moscow, Russia tatarova-gg@rambler.ru

Bessokirnaya G.P.

Cand. Sci. (Ec.), Assoc. Prof., Senior Researcher, Institute of Sociology, Federal Center of Theoretical and Applied Sociology, Russian Academy of Sciences, Moscow, Russia gala@isras.ru

DOI: 10.7868/S0132162517120054
ID of the Article: 6972


For citation:

Tatarova G.G., Bessokirnaya G.P. Subject oriented approach to the «battle» with the missing data in typological analysis. Sotsiologicheskie issledovaniya [Sociological Studies]. 2017. No 12. P. 42-54




Abstract

This article addresses the problems of quality assessment in mass surveys’ primary data during the process of «work files» preparation for solving multidimensional analysis problems. Such problems include introduction of quality criteria, some of which are of general nature, applicable to different methods of analysis, and some are specific and dependent on the proposed research practice of analysis. As an example of the latter, typological analysis for the purpose of reconstructing of social types as objects of functional management is being examined. Based on primary survey data of industrial workers as an example, the quality of variables and objects for the purpose of typologization is assessed. The logic of the «battle» with the missing data that presupposes a subjectoriented approach is also proposed here. It is based on the idea of restoration (imputation) not of the original values for the analysis of variables, but of indices that are playing, in particular, the role of classification characteristics. These are the variables that are fed to the input for procedures of separating objects into classes. Several steps are identified in the process of work files accumulation for typological analysis: evaluation of the quality of variables that correspond to the first part of the type-forming characteristics and are used to define and establish classification characteristics (step 1); refinement of the factor structure of these variables (step 2); formation of classification characteristics (step 3); assignment of values to the indexes for missing data cases (step 4); inclusion of variables from the second and third part of the generative attributes in the work file (step 5).


Keywords
data quality; typological analysis; methods of data imputation; local data imputation; type-forming attributes; classification characteristics; indices

References

Bessokirnaya G.P. (2002) Factor Analysis: Traditions of Using and New Possibilities. Sociology: Methodology, Methods, Mathematical Models. No. 12: 142–153. (In Russ.)

Bessokirnaya G.P., Tatarova G.G. (2014a) Identification of Now: a Conceptual Model and Research Tools. In: Supplement to the Annual «Reforming Russia». Iss. 2014. [Electronic resource.] Moscow: IS RAN. 1 CD ROM. (In Russ.)

Bessokirnaya G.P., Tatarova G.G. (2011) Social Types of Employees as Subjects of Management. In: Modern Management: Problems, Hypotheses, Research: Scientific Research Digest. Iss. 3. Part 2. Moscow: Izd. dom Vysshej shkoly ekonomiki: 253–264. (In Russ.)

Fabrykant M.S. (2015) Model-oriented Approach to Missing Values: Multiple Imputation in Multilevel Regression Using R (on the Example of Analyzing Survey Data). Sociology: Methodology, Methods, Mathematical Modeling. No. 41: 7–29. (In Russ.)

Galitskaya E.G., Galitskiy E.B. (2006) Cluster Analysis in the Factor Space: Ways to Avoid the Typical Mistakes. Sociology: Methodology, Methods, Mathematical Modeling. No. 22: 145–161. (In Russ.)

Karahanova T.M., Bessokirnaya G.P., Bol’shakova O.A. (2014) Work and Leisure Time of the Employees (Blueprint, Toolkit and Some Preliminary Results of the Repeat Examination). URL: http://www.isras.ru/publ.html?id=3224 (accessed 19.05.2017). (In Russ.)

Kryshtanovsky A.O. (2005) «Clusters on Factors» – Regarding One Common Misconception. Sociology: Methodology, Methods, Mathematical Modeling. No. 21: 172–187. (In Russ.)

Kutlaliev A. Kh. (2011) The Method of Multiple Data Recovery. In: Oberemko O.A. (ed.) Sociological Methods of Modern Research Practice: a Collection of Articles Dedicated to the Memory of A.O. Kryshtanovskiy, the First Dean of Sociology Department of the Higher School of Economics. Moscow: Izdatel’skij dom NIU VSHE: 201–208. (In Russ.)

Little R.J.A, Rubin D.B. (1990) Statistical Analysis with Missing Data. Moscow: Finansy i statistika. (In Russ.)

Tatarova G.G. (2007b) Fundamentals of Typological Analysis in Sociological Research. Moscow: Vysshee obrazovanie i nauka. (In Russ.)

Tatarova G.G. (2007a) Typological Analysis as a Research Strategy. In: Sociological Methods in Modern Research Practice: Proceedings of the Scientific Conference in Memory of A.O. Kryshtanovskiy. Moscow: GU VSHE: 114–123. (In Russ.)

Tatarova G.G., Bessokirnaya G.P. (2016) Identification with an Enterprise: Classification of Employees and Identification of Controlled Factors of Labor Activity. In: Supplement to the Annual «Reforming Russia». Iss. 2. 2015: collected articles. [Electronic resource.] Moscow: IS RAN. 1 CD ROM. (In Russ.)

Tatarova G.G., Bessokirnaya G.P. (2014a) Identification with an Enterprise: Indices for the Typological Analysis of Workers. In: Supplement to the Annual «Reforming Russia». Iss. 2014. [Electronic resource.] Moscow: IS RAN. 1 CD ROM. (In Russ.)

Tatarova G.G., Bessokirnaya G.P. (2014b) On the Formation of Basic Type-building Variables for Identification of the Social Types of Workers as object of Managing. Sotsiologicheskaja nauka i sotsial’naja praktika [Sociological Science and Social Practice]. No. 1: 32–50. (In Russ.)

Tatarova G.G., Bessokirnaya G.P. (2011) Typological Analysis for the Reconstruction of Social Types of Workers (Conceptual and Empirical Basis). Sotsiologicheskie issledovanija [Sociological Studies]. No. 7: 3–15. (In Russ.)

Tatarova G.G., Bessokirnaya G.P. (2016b) Typological Analysis of Employees in the Context of Their Social Adaptation. Reforming Russia. Yearbook. Iss. 14: 21–49. (In Russ.)

Tolstova Yu.N., Zangieva I.K. (2012) Statistical Approach to Data Analysis while Filling Missing Values. In: Tolstova Yu.N., Oberemko O.A. (eds) Problems of Raw Data Preparation in Sociological Research: collected articles. Moscow: Rossijskoe obschestvo sotsiologov: 114–127. (In Russ.)

Voronin G.L. (2010) Once More about «Clusters on Factors». Sotsiologicheskij zhurnal [Sociological Journal]. No. 3: 21–34. (In Russ.)

Zangieva I.K. (2011). The Problem of Missing Values in Sociological Data: Essence and Solution Methods. Sociology: Methodology, Methods, Mathematical Modeling. No. 33: 28–56. (In Russ.)

Zangieva I.K., Suleymanova A.N. (2016) Comparative Analysis of Approaches to Aggregation of Multiple Imputation Results. Sociology: Methodology, Methods, Mathematical Modeling. No. 42: 7–60. (In Russ.)

Zangieva I.K., Timonina E.S. (2014) Comparing Imputation Algorithms Efficiency Respective to the Data Analysis Methods. The Monitoring of Public Opinion: Economic and Social Changes Journal. No. 1(119): 41–55. (In Russ.)

Content No 12, 2017