How to Analyze the Association between Two Categorical Variables Based on Census Data with a High Level of Nonresponse
DOI:
https://doi.org/10.47743/saeb-2023-0009Keywords:
census data, nonresponse, association between two categorical variables, residuals, odds ratio.Abstract
Statistical surveys are often used in shaping managerial policy and practice. In this paper we study, how to analyze the association between two categorical variables based on census data with a high level of nonresponse. The purpose is to discuss the suggested approach to the investigation. We used the census data from the survey executed at one Slovak University for testing the new process. The proposed process offers the methods of analysis of the association between two categorical variables based on pseudo-population estimated from the census data with a high level of nonresponse. We recommend using the process in the surveys in which the costs of survey execution by the census are practically not different from sample survey costs, and the connections to all units of the population are available.
References
Agresti, A. (2010). Analysis of Ordinal Categorical Data (2nd ed. ed.): John Wiley & Sons. http://dx.doi.org/10.1002/9780470594001
Agresti, A. (2013). Categorical Data Analysis (3rd ed. ed.): Wiley and Sons.
Agresti, A. (2018). Statistical Methods for the Social Sciences (5th ed. ed.): Pearson.
Agresti, A., & Finlay, B. (2014). Statistical Methods for the Social Sciences (4th ed. ed.): Pearson.
Chaudhuri, A. (2014). Modern Survey Sampling. New York: Chapman and Hall. http://dx.doi.org/10.1201/b17087
Cochran, W. G. (1977). Sampling Techniques. New York: Wiley and Sons.
Eltinge, J. L., & Yansaneh, I. S. (1997). Diagnostics for formation of nonresponse adjustment cells, with an application to income nonresponse in the U.S. Consumer Expenditure Survey. Survey Methodology, 23(1), 33-40.
Freund, J. E. (1992). Mathematical Statistics (5th ed. ed.): Prentice-Hall.
Gelman, A., & Carlin, J. B. (2001). Poststratification and Weighting Adjustments Survey Nonresponse (pp. 289–302). New York: Wiley and Sons.
Levy, P. S., & Lemeshow, S. (2008). Sampling of Populations. Methods and Applications (4th ed. ed.): Wiley and Sons. http://dx.doi.org/10.1002/9780470374597
Little, R. J., & Vartivarian, S. (2003). On weighting the rates in non-response weights. Statistics in Medicine, 22(9), 1589-1599. http://dx.doi.org/10.1002/sim.1513
Lohr, S. L. (2019). Sampling: Design and Analysis (2nd ed. ed.): CRC Press Taylor & Francis Group. http://dx.doi.org/10.1201/9780429296284
Miller, I., & Miller, M. (2014). John E. Freund’s Mathematical Statistics with Applications (8th ed. ed.): Pearson Education Limited.
Särndal, C. E., & Lundström, S. (2005). Estimation in Surveys with Nonresponse: Wiley and Sons. http://dx.doi.org/10.1002/0470011351
Terek, M. (2016). Information channels effectiveness assessment on the basis of data from statistical survey. Scientific Annals of Economics and Business, 63(2), 225–235. http://dx.doi.org/10.1515/saeb-2016-0118
Terek, M. (2017). Interpretácia štatistiky a dát. 5. doplnené vydanie: Equilibria.
Terek, M. (2019a). Dotazníkové prieskumy a analýzy získanych dát. 1. vydanie: Equilibria.
Terek, M. (2019b). Obtaining the information about incomes from EU-SILC data and market analysis. Journal of Eastern European and Central Asian Research (JEECAR), 6(2), 205-219. http://dx.doi.org/10.15549/jeecar.v6i2.313
Terek, M. (2020). Možnosti riešenia problému neodpovedania v analýzach dát pri vyčerpávajúcom skúmaní prostredníctvom dotazníkových zisťovaní. Slovenská štatistika a demografia, 30(4), 28-41.
Terek, M., & Muchova, E. (2017). The structure of Incomes Analysis in Slovak Republic and Regions of the Slovak republic Based on EU-SILC Data. International Journal of Economic Research, 14(20), 425-434.
Terek, M., Muchova, E., & Lesko, P. (2021). How to make estimates with compensation for nonresponse in statistical analysis of census data. Journal of Eastern European and Central Asian Research (JEECAR), 8(2), 149-159. http://dx.doi.org/10.15549/jeecar.v8i2.619
Tillé, Y. (2001). Théorie de sondages. Echantillonnage et estimation en populations finies: Dunod.
Tillé, Y. (2020). Sampling and Estimation from Finite Populations: Wiley and Sons. http://dx.doi.org/10.1002/9781119071259
Vartivarian, S., & Little, R. (2003). On the Formation of Weighting Adjustment Cells for Unit Nonresponse. Paper presented at the The University of Michigan Department of Biostatistics Working Paper Series.
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