Open Journal of Statistics, 2017, 7, 264-289 http://www.scirp.org/journal/ojs ISSN Online: 2161-7198 ISSN Print: 2161-718X DOI: 10.4236/ojs.2017.72021 April 26, 2017 Does Missing Data in Studies of Hard-to-Reach Populations Bias Results? Not Necessarily Anneliese C. Bolland 1 , Sara Tomek 2 , John M. Bolland 1 1 Institute for Social Science Research, The University of Alabama, Tuscaloosa, Alabama, USA 2 Department of Educational Studies in Psychology, Research Methodology, and Counseling, The University of Alabama, Tusca- loosa, Alabama, USA Abstract Missing data are always an issue in community-based longitudinal studies, call- ing into question the representativeness of samples and bias in conclusions, the research has generated. This may be due to the difficulty of implementing ran- dom sampling procedures in these studies and/or the inherent difficulty in sam- pling hard-to-reach segments of the population being studied. In fact, the ability to accurately study hard-to-reach populations in light of potential bias created by missing data remains an open question. In this study, missing data are de- fined as both failure to interview potential research participants identified in the sampling frame and failure to retain enrolled research participants longitudi- nally. Using the sample from the Mobile Youth Survey, a multiple-cohort, lon- gitudinal study of adolescents living in highly impoverished neighborhoods in Mobile, Alabama, we examined sample representativeness and dropout to de- termine whether missing data led to a nonrepresentative, and therefore, biased sample. Results indicate that even though random procedures are not strictly used to draw the sample, (a) the sample appears to be largely representative of the population that was studied, and (b) attrition is largely uncorrelated with characteristics of those who dropped out. This suggests that it is possible to study with validity hard-to reach populations in community settings. Keywords Hard-to-Reach Populations, Missing Data, Representativeness, Community-Based Research 1. Introduction In research, some units of the analysis are more difficult to study than others. In survey research, where people are the units of analysis, some people (or more gen- How to cite this paper: Bolland, A.C., Tomek, S. and Bolland, J.M. (2017) Does Missing Data in Studies of Hard-to-Reach Populations Bias Results? Not Necessarily. Open Journal of Statistics, 7, 264-289. https://doi.org/10.4236/ojs.2017.72021 Received: January 25, 2017 Accepted: April 23, 2017 Published: April 26, 2017 Copyright © 2017 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access