The Dance of the Mechanisms: How Observed Information Influences the Validity of Missingness Assumptions

Rianne Margaretha Schouten and Gerko Vink

Sociological Methods & Research, 2021, vol. 50, issue 3, 1243-1258

Abstract: Missing data in scientific research go hand in hand with assumptions about the nature of the missingness. When dealing with missing values, a set of beliefs has to be formulated about the extent to which the observed data may also hold for the missing parts of the data. It is vital that the validity of these missingness assumptions is verified, tested, and that assumptions are adjusted when necessary. In this article, we demonstrate how observed data structures could a priori indicate whether it is likely that our beliefs about the missingness can be trusted. To this end, we simulate complete data and generate missing values according several types of MCAR, MAR, and MNAR mechanisms. We demonstrate that in scenarios where the data correlations are either low or very substantial, strictly different mechanisms yield equivalent statistical inferences. In addition, we show that the choice of quantity of scientific interest together with the distribution of the nonresponse govern the validity of the missingness assumptions.

Keywords: missing data methodology; missingness assumptions; multivariate amputation (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0049124118799376 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:50:y:2021:i:3:p:1243-1258

DOI: 10.1177/0049124118799376

Access Statistics for this article

More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().