Evaluation of the measurement error of Iranian labor force indicators due to changing data gathering mode based on the Markov latent class model

Articles in Press

Document Type : Applied Paper

Authors

1 Technical Designs and Statistical Methods Department, Statistical Research and Training Center, Tehran, Iran

2 Technical Designs and Statistical Methods Department. Statistical Research and Training Center. Tehran,Iran.

Abstract

One of the most important non-sampling errors is measurement error, which causes the measured value of the target variable to be different from its true value. The markov latent class model allows for the estimation of measurement error for categorical variables in panel surveys that have at least three repetition periods, with the advantage that it does not require re-interviews. In the Iranian labor force survey, which is conducted with rotational sampling panel with a 2-2-2 pattern, this model can be applied. In this article, the challenges of changing the survey mode in times of crisis and the advantages of telephone interviews compared to face-to-face interviews are reviewed. Also, in order to evaluate the results of the labor force survey in the context of the COVID-19 pandemic, when the survey mode was suddenly changed from face-to-face to telephone interviews, the markov latent class model was used to evaluate the measurement error using data from four survey periods from spring 2018 to summer 2021. The results indicate that the measurement error increased in the first period of changing the interview mode, but decreased in subsequent periods. Overall, it can be stated that telephone interviews can be a suitable method for collecting labor force survey data.

Keywords

Main Subjects

References

1] P. Biemer, Latent class analysis of survey error, Wiley Series in Survey Methodology, John Wiley & Sons, Inc., Hoboken, NJ, 2011.
[2] P. Biemer and M. Bushery, On the validity of markov latent class analysis for estimating classification error in labor force data, Surv. Methodol., 26 no. 2 (2000) 139–152.
[3] International Labour Organization (ILO), COVID-19: Guidance for labour statistics data collection, Guidance to data producers to maintain labour force survey data collection, ILO Technical Note, Geneva: ILO, 2020.
[4] L . Kalhori Nadrabadi and Z. Fallah Mohsekhani, Using Markov Latent Class Models in Estimating the Classification Error of Iranian Labor Flow Statistics, JSS, 16 no. 1 2022 189–207. [In Persian]
[5] K. Khalagi, M. A. Mansournia, A. Rahimi-Movaghar, K. Nourijelyani, M. Amin-Esmaeili, A. Hajebi, V. Sharif, R. Radgoodarzi, M. Hefazi and A. Motevalian, Assessing measurement error in surveys using latent class analysis: application to self-reported illicit drug use in data from the Iranian Mental Health Survey, Epidemiology and Health, 38 (2016) 1–11.
[6] F. Mehran, M. Nourmohammadi, Z. Rezaee, Z. Fallah Mohsenkhani, L. Kalhori Nadrabadi, A. Izadi, M. Reyhani, T. Baghfalaki, M. Naghikhani, N. Yousefi and R. Aliakbari Saba, Identifying and controlling non-response and measurement errors in survey designs, Statistical Research and Training Center, Tehran, Iran, 2017. [In Persian]
[7] B. D. Meyer and N. Mittag, An empirical total survey error decomposition using data combination, J. Econometrics, 224 no. 2 (2021) 286–305.
[8] H. Navvabpour, T. Chegini and A. Safarnejadborojeni, An application of the estimation of total survey error in a small-scale survey, Journal of Official Statistics of Iran, 25 (2014) 47–68. [In Persian]
[9] H. Navvabpour, T. Chegini and A. Safarnejadborojeni, An application of measurement error evaluation using latent class analysis, Andisheye Amari, 22 (2017) 85–96. [In Persian]
[10] H. Navvabpour, M. Safakish and A. Izadi, Offitial Statistics, Statistical Research and Training Center, Tehran, 2018. [In Persian]
[11] C. A. Poulsen, Latent structure analysis with choice modeling applications, Arhus School of Business Administration and Economics, Arhus, Denmark, 1982.
[12] F. Van de Pol and R. Langeheine, Mixed markov latent class models, in C.C. Clogg ed., Sociological Methodology, 20 (1990) 213–247.
[13] F. Van de Pol and J. De Leeuw, A latent markov model to correct for measurement error, Sociological Methods and Research, 15 no. 1-2 (1986) 118–141.
[14] J. K. Vermunt, LEM: a general program for the analysis of categorical data, Department of Methodology and Statistics, Tilburg University, 1997.
[15] L. M. Wiggins, Panel analysis, latent probability models for attitude and behavior processing, Elsevier SPC, Amsterdam, 1973.
Mathematics and Society

Articles in Press, Corrected Proof
Available Online from 20 May 2025

Files

History

  • Receive Date: 09 October 2024
  • Revise Date: 14 May 2025
  • Accept Date: 20 May 2025
  • Publish Date: 20 May 2025

Share

How to cite

Statistics