Research for CRM

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August 1, 1986
The survival rates of prior-service Navy personnel from FY 1978 through FY 1984 are examined. Survival rates for this group of recruits (i.e., at what rate and for how long they remain in the Navy) depend primarily on paygrade at enlistment. The analysis shows a sharp distinction between E1-to-E3 enlistees and E4-to-E7 enlistees, with the latter group having the higher rates. It also examines other factors influencing survival rates including age, education level, enlistment program, and previous military experience.
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August 1, 1986
This paper reports on the construction of an interactive, historical database for recruit survival probabilities. This FY 1978-1984 base includes accession and monthly survival information for non-prior service recruits by accession program, gender, shipment mode, educational category, mental group, and age. An important finding is that for recruits who are otherwise identical, survival is worse if they are shipped within the month they signed their initial contract.
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August 1, 1986
This is a summary report of a CNO-directed study of factors that affect the costs of training Navy personnel. It focuses on the relationship between retention and specialized skill training for enlisted personnel on the expectation that increased retention could be expected to reduce training requirements and costs. Other detailed findings of the study are contained in several earlier CNA documents; this memorandum summarizes those findings, highlighting the more important patterns and trends.
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August 1, 1986
Within a few years the Department of Defense may begin administering the Armed Services Vocational Aptitude Battery (ASVAB) using Computerized Adaptive Testing (CAT). In CAT, each test item is characterized by an Item Response Curve (IRC), which describes how the probability of correctly answering the item increases with ability. A recent study conducted by the Center for Naval Analyses found that IRCs of many items in the experimental CAT item pool for the ASVAB changed substantially from paper-pencil to CAT administration. This research memorandum examines the effects of these changes on scores of individual examinees.
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August 1, 1986
Females tend to have higher performance than males in clerical and food services training courses, when aptitude scores are held constant. To help account for the differences, educational level and interest in clerical-type activities are included in this analysis, along with aptitude composite scores. A recommendation is made about adjusting aptitude qualifying scores for females.
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July 1, 1986
Knowing the magnitude of performance differences among individuals is critical in making personnel decisions in the Marine Corps. Recent research at the Center for Naval Analyses has focused on quantifying the magnitude of these performance differences. The purpose of this analysis was to cross-validate those results using hands-on measures of job performance and other published research findings.
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June 1, 1986
The FY 1985 Master Course Reference File (MCRF) data file is documented in this paper. It describes alternative ways the data can be accessed within CNA and through an analysis of these data documents institutional features of formal training.
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June 1, 1986
Computerized Adaptive Test (CAT) and Paper-and-Pencil (PP) Armed Services Vocational Aptitude Battery (ASVAB) scores are equated in several subpopulations to determine if racial minorities, females, those who did not complete high school, or individuals lacking experience using computers would be at a disadvantage if CAT rather than PP scores were used for selection. Equating is generally independent of population group.
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June 1, 1986
The cost that the Marine Corps incurs when first-term enlisted personnel leave the service is estimated in this paper. The expected cost of attrition is calculated for several personnel categories that are defined according to levels of education and ability.
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May 1, 1986
The Armed Forces Qualification Test (AFQT) is currently constructed from a sum of subtest raw scores converted to percentile scores. This paper examines advantages and disadvantages of constructing AFQT percentile scores from sums of subtest standard scores.
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