Non-Randomly Sampled Networks: Biases and Corrections

78 Pages Posted: 19 Nov 2018 Last revised: 20 Jul 2023

See all articles by Chih-Sheng Hsieh

Chih-Sheng Hsieh

National Taiwan University

Stanley Ko

University of Macau

Jaromír Kovářík

University of the Basque Country

Trevon Logan

Ohio State University; National Bureau of Economic Research (NBER)

Date Written: November 2018

Abstract

This paper analyzes statistical issues arising from networks based on non-representative samples of the population. We first characterize the biases in both network statistics and estimates of network effects under non-random sampling analytically and numerically. Sampled network data systematically bias the properties of population networks and suffer from non-classical measurement-error problems when applied as regressors. Apart from the sampling rate and the elicitation procedure, these biases depend in a nontrivial way on which subpopulations are missing with higher probability. We propose a methodology, adapting post-stratification weighting approaches to networked contexts, which enables researchers to recover several network-level statistics and reduce the biases in the estimated network effects. The advantages of the proposed methodology are that it can be applied to network data collected via both designed and non-designed sampling procedures, does not require one to assume any network formation model, and is straightforward to implement. We apply our approach to two widely used network data sets and show that accounting for the non-representativeness of the sample dramatically changes the results of regression analysis.

Suggested Citation

Hsieh, Chih-Sheng and Ko, Stanley and Kovářík, Jaromír and Logan, Trevon, Non-Randomly Sampled Networks: Biases and Corrections (November 2018). NBER Working Paper No. w25270, Available at SSRN: https://ssrn.com/abstract=3286935

Chih-Sheng Hsieh (Contact Author)

National Taiwan University ( email )

1 Sec. 4, Roosevelt Road
Taipei 106, 106
Taiwan

Stanley Ko

University of Macau

Jaromír Kovářík

University of the Basque Country

Barrio Sarriena s/n
Leioa, 48940
Spain

Trevon Logan

Ohio State University ( email )

2100 Neil Avenue
Columbus, OH OH 43210
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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