Acknowledgements

No good learning happens without community. At least, that has always been true for me. I am grateful for many creative and energizing discussions with the other members of the MICS (UNICEF data) research team: Professor Shawna Lee, Professor Julie Ma, Dr. Kaitlin Ward, and Professor Garrett Pace. I’m thankful for their collegiality, their friendship, their patience with me, and their dedication to good science. Working with these colleagues has greatly deepened my understanding of multilevel models. I’m also very grateful to one of my mentors, Professor Sandra Danziger, who has taught me so much about the what and the why of mentoring, teaching, and doing research. I’d like to thank Ross Grogan-Kaylor for continued interest in the progress of this document, and probing thoughtful questions. Shari Grogan-Kaylor had many important and challenging questions about the what and the why of this document, and most importantly to me, has believed in it. Don Deutsch showed ongoing interest in the development of this document, and has asked some hard questions that have improved its logic. Thank you to Professor Jim Allen for our discussions about how quantitative methods can better listen to lived experience. Importantly, I’d like to express gratitude to the many students in my class on Multilevel and Longitudinal Modeling who over the years have helped me think more deeply about statistical and substantive issues, including Dr. Kaitlin Ward, Professor Garrett Pace, Professor Julie Ma, Professor Yoonsun Han, Professor Berenice Castillo, Professor Maria Galano, Dr. Sara Stein, Madhur Singh, and Tong Suo. Thank you for the many valuable discussions during class breaks, and after class. These discussions have also greatly extended my understanding of multilevel models. Lastly, I’d like to thank Marty Betts and Greg Knollmeyer for their help and support. While I’m thankful for the inspiration and colleagueship provided by others, any remaining errors and omissions in this document are of course my responsibility.