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AIDS and Behavior

, Volume 16, Issue 6, pp 1382–1393 | Cite as

Are We Missing the Importance of Missing Values in HIV Prevention Randomized Clinical Trials? Review and Recommendations

  • Ofer Harel
  • Jennifer Pellowski
  • Seth Kalichman
Substantive Review

Abstract

Missing data in HIV prevention trials is a common complication to interpreting outcomes. Even a small proportion of missing values in randomized trials can cause bias, inefficiency and loss of power. We examined the extent of missing data and methods in which HIV prevention randomized clinical trials (RCT) have managed missing values. We used a database maintained by the HIV/AIDS Prevention Research Synthesis (PRS) Project at the Centers for Disease Control and Prevention (CDC) to identify related trials for our review. The PRS cumulative database was searched on June 15, 2010 and all citations that met the following criteria were retrieved: All RCTs which reported HIV/STD/HBV/HCV behavioral interventions with a biological outcome from 2005 to present. Out of the 57 intervention trials identified, all had some level of missing values. We found that the average missing values per study ranged between 3 and 97%. Averaging over all studies the percent of missing values was 26%. None of the studies reported any assumptions for managing missing data in their RCTs. Under some relaxed assumptions discussed below, we expect only 12% of studies to report unbiased results. There is a need for more detailed and thoughtful consideration of the missing data problem in HIV prevention trials. In the current state of managing missing data we risk major biases in interpretations. Several viable alternatives are available for improving the internal validity of RCTs by managing missing data.

Keywords

Incomplete data Missing data Bias HIV prevention RCT 

Notes

Acknowledgments

This project was partially supported by Award Number K01MH087219 from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Ofer Harel
    • 1
  • Jennifer Pellowski
    • 2
  • Seth Kalichman
    • 2
  1. 1.Department of StatisticsUniversity of ConnecticutStorrsUSA
  2. 2.Department of PsychologyUniversity of ConnecticutStorrsUSA

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