University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School February 2018 Strategies to Adjust for Response Bias in Clinical Trials: A Simulation Study Victoria R. Swaidan University of South Florida, [email protected] Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the Biostatistics Commons, and the Public Health Commons Scholar Commons Citation Swaidan, Victoria R., "Strategies to Adjust for Response Bias in Clinical Trials: A Simulation Study" (2018). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/7648 This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Strategies to Adjust for Response Bias in Clinical Trials: A Simulation Study by Victoria R. Swaidan A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Public Health with a concentration in Biostatistics Department of Epidemiology and Biostatistics College of Public Health University of South Florida Major Professor: Wei Wang, Ph.D. Yangxin Huang, Ph.D. Henian Chen, M.D., Ph.D. Date of Approval: February 5, 2018 Keywords: survey research, self-report bias, bias correction, intervention studies, treatment effect, estimation, reliability, internal validity Copyright © 2018, Victoria R. Swaidan Dedication I dedicate this work to my loving and devoted family, without whom I would not be where I am today. To my sweet, beautiful daughter Aliyah, whose joy and laughter helped me get through so many long days/nights of studying and working on this project. To my husband Floyd, who kept me strong, helped me push through the trying times, and always kept me focused and motivated. And to my mother Peggy, who was full of encouragement and support, always helped me keep the end in sight, and devotingly sacrificed her working career to help make our house a home during these extraordinarily busy times. There are no words or gestures that could ever fully express the gratitude I feel for what each you have done to help me along this incredible journey. I truly appreciate each of you and thank you all from the bottom of my heart. Acknowledgments I express my deepest gratitude to my major professor Dr. Wei Wang for supporting me in the extention of his work in this area and for making this project possible. I am truly grateful for the immense amount of guidance, training, and mentorship that he provided throughout the entire thesis process. And to my committee members, Drs. Yangxin Huang and Henian Chen for the time and effort dedicated to the development and completion of this project. Without the guidance of this incredeible committee, this project would not be near the level of rigor that it is, and for that I am truly thankful. A special thank you to the faculty of the Department of Epidemiology and Biostatistics in the College of Public Health at the University of South Florida for providing an incredible curriculum and learning environment that allowed me to pursue this degree. Lastly, I express my sincere appreciation to Dr. Alison Salloum for the many years of research experience that she has provided, allowing me to grow and develop as a researcher under her mentorship. The experience I gained working on her clinical trials piqued my interest in statistics, inevitably bringing me into this program. Table of Contents List of Tables ................................................................................................................................... iii List of Figures .................................................................................................................................. iv Abstract ............................................................................................................................................ v Chapter 1: Overview of Bias............................................................................................................ 1 Bias in the Design Phase ..................................................................................................... 1 Bias in the Data Collection Phase ....................................................................................... 3 Bias in the Analysis Phase ................................................................................................... 5 Conclusion ........................................................................................................................... 6 Chapter 2: A Closer Look at Response Bias..................................................................................... 8 Sources ................................................................................................................................ 8 Prevention ......................................................................................................................... 10 Detection and Quantification ........................................................................................... 12 Data Collection Phase ........................................................................................... 12 Analysis Phase ....................................................................................................... 13 Adjustments ...................................................................................................................... 14 Conclusion ......................................................................................................................... 17 Chapter 3: Simulation ................................................................................................................... 20 Introduction ...................................................................................................................... 20 Methods ............................................................................................................................ 24 Sample Size ........................................................................................................... 24 Model Parameters ................................................................................................ 24 Treatment Effect ....................................................................................... 25 Covariate ................................................................................................... 26 Reliability Distribution .......................................................................................... 26 Unreliable Response Style .................................................................................... 27 Bias Correction Strategies and Models ................................................................. 28 Model Comparison................................................................................................ 30 Organizational Structure ........................................................................... 30 Bias and RRMSE (%) .................................................................................. 31 Selecting the Best Strategy ....................................................................... 32 i Results ............................................................................................................................... 34 Prediction Equations ............................................................................................. 34 Subject- and Sample-Level Reliability ................................................................... 35 Comparison of Bias Correction Strategies ............................................................ 37 Recommendations ................................................................................................ 45 Comparison of Unadjusted and Adjusted Estimates ............................................ 46 Conclusion ......................................................................................................................... 51 Chapter 4: Discussion .................................................................................................................... 53 Limitations......................................................................................................................... 56 Directions for Future Research ......................................................................................... 58 References .................................................................................................................................... 61 Appendices .................................................................................................................................... 69 Appendix A: R Code for Data Generation ......................................................................... 70 Appendix B: R Code for Bias Correction Models............................................................... 72 Appendix C: R Code for Bias and RRMSE (%) .................................................................... 89 Appendix D: R Code for RRMSE (%) Figures ...................................................................... 90 ii List of Tables Table 1: Summary of Response Bias Prevention, Detection/Quantification, and Adjustment Methods .................................................................................................. 18 Table 2: RRMSE (%) Margins by Scenario