Nan Laird is the first woman to be awarded the International Prize of Statistics, which is most popularly known as the Nobel Prize of Statistics.
The Woman Post | Catalina Mejía Pizano
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Laird was born In Gainsville, Florida in 1943. Her mother was a schoolteacher and her father was a political science professor who later on started working on state government at Tallahassee. During her school years, Laird’s favorite subject was mathematics. In 1961, she followed her passion and started studying at Rice University in Houston. She was the only woman in her class since careers in science fields were more popular among men during those times. Shen then began studying to learn french and married a colleague from Rice University. They had a baby and she paused her career for a while, and she only focused again on her career some years later when they moved to Georgia.
This time, she focused on informatics and took a lecture in the field of decision analysis. Then Laird took graduate studies in statistics, culminating in 1969. She entered Harvard University as a doctoral student in statistics in 1971 and became an assistant professor. She has published more than 400 papers throughout her career and has been cited more than 180,000 times. Fifty-two years later, thanks to her valuable contributions to the field of statistics, she was awarded the International Prize which came with an $80,000 award, which she received this July at the biennial International Statistical Institute World Statistics Congress virtually.
It is worth highlighting that the first International Prize in Statistics was awarded to statistician David R. Cox, who created the Cox Proportional Hazards Model which enables researchers to track patient’s survival rates in different investigations. In 2019, Bradley Efron was the winner of the award, for the development of a statistical method named “bootstrap”, which is useful for assessing uncertainty in applied statistics.
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Her contributions to longitudinal analyses and genetics have been enormous. Back in the early 1980s, existing analysis methods required various assumptions that didn't hold for longitudinal data. At the time, most statistical methods also required the data to be unrealistically complete, which is complicated in reality because usually participants don’t assist to some of the appointments or show up later. This is why Laird developed a framework and implementation to solve these analytical constraints, making an important contribution to the analysis of data collected over time on individuals.
The framework that Laird and Ware described in their Biometrics paper from 1982, “Random effects Models for Longitudinal Data: An Overview of Recent Results” proved to be appropriate for accomodating various real-life situations, even ones with missing data. It also allowed researchers to capture each participant’s changes over time, as well as noting the general effects on a population.
Laird claims that we should always promote creativity among students, to avoid traditional and limited education models. She also believes that following your passion and enjoying your work is the only road to success. She claims that even though many people choose careers that make the world a better place and enable them to help others, women tend to be particularly interested in making a positive impact and this explains why many of them opt for careers in the health sector.