Accession Number : ADA606803


Title :   Forecasting Advancement Rates to Petty Officer Third Class for U.S. Navy Hospital Corpsmen


Descriptive Note : Master's thesis


Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA


Personal Author(s) : McCrink, Sean H


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a606803.pdf


Report Date : Jun 2014


Pagination or Media Count : 83


Abstract : We develop forecasting models to identify the most influential decision variables in predicting advancement probabilities to petty officer third Class (E-4) in the Hospital Corpsman rating in the U.S. Navy. Analyzing a Sailor s first three opportunities at advancement to E-4, the possible outcomes are advancement, failure to advance, or separation from the Navy between advancement opportunities. Using data collected from 1996 through 2004, on more than 50,000 Sailors in this rating, multivariate logistic regression models are developed to estimate Sailors advancement probabilities based on their individual personal and professional attributes. We find that the three corresponding models developed are nearly identical with respect to the influences of year of promotion, length of service, Navy enlisted classification code, the total number of sea months, the proportion of vacancies to test takers, Armed Forces Qualification Test score, and performance mark average (PMA). Among the variables considered, PMA is found to be the most influential in predicting a Sailor s estimated advancement probability, supporting the hypothesis that sustained superior performance is the key to success in a military career.


Descriptors :   *FORECASTING , *MANPOWER , *MEDICAL PERSONNEL , *NAVAL PERSONNEL , *PROMOTION(ADVANCEMENT) , ACCEPTANCE TESTS , CAREERS , CLASSIFICATION , CODING , DECISION MAKING , ENLISTED PERSONNEL , HOSPITALS , HYPOTHESES , LOGISTICS , MATHEMATICAL MODELS , MILITARY PERSONNEL , MODELS , MULTIVARIATE ANALYSIS , NAVY , OFFICER PERSONNEL , PROBABILITY , RATES , RATINGS , REGRESSION ANALYSIS , SEPARATION , VARIABLES


Subject Categories : Personnel Management and Labor Relations
      Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE