EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH

Cengiz Özkan; Ahmet Sinan Türkyılmaz

doi:10.18490/sosars.1111384

EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH

Öz

It is of great importance for researchers to find out different ways of accessing microdata, due to the ever-increasing demand for data and the expectation of reducing the response burden and costs at the same time. In this sense, statistical matching methods have been used extensively to produce new data using existing microdata of surveys and registers recently. It has an increasing application area in social studies such as poverty, deprivation, the effects of newborn on the economic situation of the household, indebtedness and demography, due to the gradual improvement of the micro estimation levels. Selection of matching variables among common variables, at this point, is a critical step in terms of the quality of the microdata to be reached. In the study, while selecting the common variables in order to estimate consumption expenditures by using Statistics on Income and Living Conditions (2018) and Household Budget Survey (2018), weights were added to Hellinger Distance and Spearman2 applications as a new approach. In addition, the effects of design variables (stratum and cluster) were also included in the processes, taking into account the complex structure of both samples. Adding household level weights and design variables to the statistical processes changed the selected or unselected common variables dramatically.

Anahtar Kelimeler

Kaynakça

Ahi, L. (2015). Veri Madenciliği Yöntemleri İle Ana Harcama Gruplarının Paylarının Tahmini., Hacettepe Üniversitesi, Yüksek Lisans Tezi.
Alexander, C. H. (2001), Stıll Rollıng: Leslie Kish’s “Rolling Samples” and The American Community Survey.
Balin, M., D’ORAZIO, M., Di Zio, M., Scanu, M., & Torelli, N. (2009). Statistical Matching of Two Surveys with a Common Subset (No. 124). Working Paper.
Byrne, D. (1971). The Attraction Paradigm. New York: Academic Press.
Cochran W.G. (1937). Problems Arising in the Analysis of a Series of Similar Experiments. Supplement to the Journal of the Royal Statistical Society, 4, 102-118.
De Waal, T. (2015). Statistical matching: experimental results and future research questions. Statistics Netherlands.
D’orazio, M., Di Zio, M., & Scanu, M. (2001, June). Statistical Matching: a tool for integrating data in National Statistical Institutes. In Proc. of the Joint ETK and NTTS Conference for Official Statistics.
D’Orazio, M., Di Zio, M., Scanu, M. (2006), Statistical Matching: Theory and Practice. John Wiley & Sons, Chichester, ISBN: 0-470-02353-8.

D’Orazio, M. (2017). Statistical Matching and Imputation of Survey Data with StatMatch.
Katz, D. (1942). Do Interviewers Bias Poll Results? Public Opinion Quaretrly, 6(2), 248-268.
Kim, D. (2018) “Development of a statistical matching method with categorical data”
Kish, L. (1990), “Rolling Samples and Censuses”, Survey Methodology, 16, 63-79.
Kum and Masterson (2008), Statistical Matching Using Propensity Scores: Theory and Application to the Levy Institute Measure of Economic Well-Being, The Levy Economics Institute of Bard College, Working Paper No:535.
Laan, P. van der. 2000. ‘Integrating Administrative Registers and Household Surveys’. Netherlands Official Statistics, Vol. 15 (Summer 2000): Special Issue, Integrating Administrative Registers and Household Surveys, ed. P.G. Al and B.F.M. Bakker, pp. 7-15.
Okner, B. (1972), "Constructing a New Data Base from Existing Microdata Sets: the 1966 Merge File", Annals of Economic and Social Measurement 1, pp. 325-342.
Öztürk, C. (2019), Nonparametric Statistical Matching Methods: An Application On Household Surveys in Turkey, master thesis, University of Hacettepe, Turkey.
Rässler, S. (2002). Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches. New York: Springer. Rasner, A., J. R. Frick, and M. M. Grabka. 2011. Extending the Empirical Basis for Wealth Inequality Research Using Statistical Matching of Administrative and Survey Data. SOEP papers 359. Berlin: DIW.
Renssen, R. H. (1998), “Use of Statistical Matching Techniques in Calibration Estimation”, Survey Methodology, 24, 171-183.
Saraç M. (2021). The Contribution of Rapport Between Interviewer and Respondent On Interview Quality from Non-Sampling Error Perspective: Evidence from 2014 Research On Domestic Violence Against Women in Turkey.
Turkstat, (2018a), Handbook for Household Budget Survey, Ankara.
Turkstat, (2018b), Handbook for Statistics on Income and Living Conditions Survey, Ankara.
Uçar, Baris, and Gianni Betti. (2016). “Longitudinal Statistical Matching: Transferring Consumption Expenditure from HBS to SILC Panel Survey.” Papers of the Department, No. 739. Siena: Department of Economics, University of Siena. Available at: http://econpapers.repec.org/paper/usiwpaper/739.htm
Uçar, B. (2017), The Effect of a New Born on Household Poverty in Turkey: The Current Situation and Future Prospects by Simulations, PHD thesis, University of Hacettepe, Turkey.
Vercruyssen, A. Wuyts, C. & Loosveldt, G. (2017). The Effect of Sociodemographic (Mis)match between Interviewer and Respondents on Unit and Item Nonresponse in Belgium. Social Science Research, 67, 229-238.
Zacharias, A., Masterson, T., Kim, K. (2014), "The Measurement of Time and Income Poverty in Korea". Economics Working Paper Archive, Levy Economics Institute, http://www.levyinstitute.org/pubs/rpr_8_14.pd

Ayrıntılar

Birincil Dil

Türkçe

Konular

Sosyoloji

Bölüm

Araştırma Makalesi

Yazarlar

Cengiz Özkan Bu kişi benim
0000-0001-7427-0431
Türkiye

Ahmet Sinan Türkyılmaz Bu kişi benim
0000-0002-2783-932X
Türkiye

Yayımlanma Tarihi

29 Nisan 2022

Gönderilme Tarihi

31 Ocak 2021

Kabul Tarihi

19 Nisan 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 25 Sayı: 2

DOI

https://doi.org/10.18490/sosars.1111384

IZ

https://izlik.org/JA73PU85WA

Kaynak Göster

RIS / Bibtex

APA

Özkan, C., & Türkyılmaz, A. S. (2022). EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH. Sosyoloji Araştırmaları Dergisi, 25(2), 318-340. https://doi.org/10.18490/sosars.1111384

AMA

1.Özkan C, Türkyılmaz AS. EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH. SAD / JSR. 2022;25(2):318-340. doi:10.18490/sosars.1111384

Chicago

Özkan, Cengiz, ve Ahmet Sinan Türkyılmaz. 2022. “EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH”. Sosyoloji Araştırmaları Dergisi 25 (2): 318-40. https://doi.org/10.18490/sosars.1111384.

EndNote

Özkan C, Türkyılmaz AS (01 Nisan 2022) EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH. Sosyoloji Araştırmaları Dergisi 25 2 318–340.

IEEE

[1]C. Özkan ve A. S. Türkyılmaz, “EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH”, SAD / JSR, c. 25, sy 2, ss. 318–340, Nis. 2022, doi: 10.18490/sosars.1111384.

ISNAD

Özkan, Cengiz - Türkyılmaz, Ahmet Sinan. “EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH”. Sosyoloji Araştırmaları Dergisi 25/2 (01 Nisan 2022): 318-340. https://doi.org/10.18490/sosars.1111384.

JAMA

1.Özkan C, Türkyılmaz AS. EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH. SAD / JSR. 2022;25:318–340.

MLA

Özkan, Cengiz, ve Ahmet Sinan Türkyılmaz. “EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH”. Sosyoloji Araştırmaları Dergisi, c. 25, sy 2, Nisan 2022, ss. 318-40, doi:10.18490/sosars.1111384.

Vancouver

1.Cengiz Özkan, Ahmet Sinan Türkyılmaz. EFFECT OF COMPLEX SAMPLE DESIGN ON DETERMINING COMMON VARIABLES IN STATISTICAL MATCHING METHOD FOR SOCIAL RESEARCH. SAD / JSR. 01 Nisan 2022;25(2):318-40. doi:10.18490/sosars.1111384