Random responses inflate statistical estimates in heavily skewed addictions data.

ABSTRACT:

Background

Some respondents may respond at random to self-report surveys, rather than responding conscientiously (Meade and Craig, 2012), and this has only recently come to the attention of researchers in the addictions field (Godinho et al., 2016). Almost no research in the published addictions literature has reported screening for random responses. We illustrate how random responses can bias statistical estimates using simulated and real data, and how this is especially problematic in skewed data, as is common with substance use outcomes.

Method

We first tested the effects of varying amounts and types of random responses on covariance-based statistical estimates in distributions with varying amounts of skew. We replicated these findings in correlations from a real dataset

SUBMITTER: King KM 

PROVIDER: S-EPMC5803341 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature