An Analysis of the U.S. Pilot Population From 1983-2005: Evaluating the Effects of Regulatory Change

Rogers PB, V�ronneau SJH, Peterman CL, Whinnery JE, Forster EM

FAA Office of Aerospace Medicine - Civil Aerospace Medical Institute

关键词: Segmented Linear Regression;    U.S. Civil Pilot Population;    Scientific Information System;    Database;    Bioinformatics;    Data Analysis;    Aviation Safety;    Epidemiology;    Gender;    Medical Class;    Age;    Experience;   

RP-ID  :  DOT/FAA/AM-09/9

美国|英语

来源: Federal Aviation Administration

【 摘 要 】

IntroductionThe size of the U.S. civil aviator community has been of interest to researchers, policy makers, and special interest groups. A strict definition for membership in the U.S. pilot population was used that was based on Scientific Information System principles. This approach provides methods for scientists to describe, quantify, and predict changes in this population over the 23-year study period. The Bioinformatics Research Team at the Civil Aerospace Medical Institute (CAMI) analyzed and modeled the counts of the U.S. pilot population using a segmented linear regression model.MethodsA dataset was constructed, based upon the methods prescribed by Scientific Information System principles of data construction, from 1983 to 2005. This methodology was selected since the data represent the entire population of pilots, rather than just a sample. Thus, the statistical results are population parameters, rather than estimates, and are not subject to sampling error. The airmen population was constructed and examined for each year of the study period. The criterion for membership of the U.S. civil pilot population is based on the medical examination that each airman must pass to hold a pilot certificate. A segmented linear regression model was chosen because of its flexibility in accounting for any policy changes that occurred over the 23-year study period. DiscussionThe CAMI Scientific Information System provided the foundation to build a segmented linear regression model pertaining to the counts of the U.S. civil pilot population; from these results it was possible for the first time to� explain the changing frequencies over time and make fact-based predictions concerning future population numbers. The capability now exists to categorize the population by gender, medical class, age, and experience over a two-decade time period, which may provide hints at some of the changes taking place within the aviation community as a whole. ConclusionThe model constructed clearly shows a decline in the overall U.S. civil aviator community. This decline is most evident in second-and third-class medical certificate holders. The percentage of women in the largely male-dominated population remained relatively stable over the study years. The age composition of both men and women changed substantially from the beginning of the study in 1983 to the end in 2005. Both segments of this population have grown significantly older. As a group, men were older than women over the study period. Therefore, when average flight time was calculated and categorized by medical class and gender, men were shown to have more flight experience.