Simulation Study of Technology for Predicted Flight Deck Alerting of Energy

At the level of manifest categorical variables, a large number of coefficients and models for the examination of rater agreement has been proposed and used. The most popular of these is Cohen's κ. In this article, a new coefficient, κ s , is proposed as an alternative measure of rater agreement. Both κ and κ s allow researchers to determine whether agreement in groups of two or more raters is significantly beyond chance. Stouffer's z is used to test the null hypothesis that κ s = 0. The coefficient κ s allows one, in addition to evaluating rater agreement in a fashion parallel to κ, to (1) examine subsets of cells in agreement tables, (2) examine cells that indicate disagreement, (3) consider alternative chance models, (4) take covariates into account, and (5) compare independent samples. Results from a simulation study are reported, which suggest that (a) the four measures of rater agreement, Cohen's κ, Brennan and Prediger's κ n , raw agreement, and κ s are sensitive to the same data characteristics when evaluating rater agreement and (b) both the z-statistic for Cohen's κ and Stouffer's z for κ s are unimodally and symmetrically distributed, but slightly heavy-tailed. Examples use data from verbal processing and applicant selection.

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Asiana Airlines Flight 214

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000066 ◽

2014 ◽

Vol 4 (2) ◽

pp. 113-121 ◽

Cited By ~ 5

Author(s):

Stephanie Chow ◽

Stephen Yortsos ◽

Najmedin Meshkati

Keyword(s):

Human Factors ◽

Aviation Safety ◽

Cultural Factors ◽

Vital Role ◽

Cultural Issues ◽

Flight Crew ◽

Pilot Performance ◽

Engineering Designs ◽

Flight Deck

This article focuses on a major human factors–related issue that includes the undeniable role of cultural factors and cockpit automation and their serious impact on flight crew performance, communication, and aviation safety. The report concentrates on the flight crew performance of the Boeing 777–Asiana Airlines Flight 214 accident, by exploring issues concerning mode confusion and autothrottle systems. It also further reviews the vital role of cultural factors in aviation safety and provides a brief overview of past, related accidents. Automation progressions have been created in an attempt to design an error-free flight deck. However, to do that, the pilot must still thoroughly understand every component of the flight deck – most importantly, the automation. Otherwise, if pilots are not completely competent in terms of their automation, the slightest errors can lead to fatal accidents. As seen in the case of Asiana Flight 214, even though engineering designs and pilot training have greatly evolved over the years, there are many cultural, design, and communication factors that affect pilot performance. It is concluded that aviation systems designers, in cooperation with pilots and regulatory bodies, should lead the strategic effort of systematically addressing the serious issues of cockpit automation, human factors, and cultural issues, including their interactions, which will certainly lead to better solutions for safer flights.

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Comparison of Principal Component Solutions in Two Populations

Methodology ◽

10.1027/1614-2241/a000099 ◽

2016 ◽

Vol 12 (1) ◽

pp. 11-20 ◽

Cited By ~ 1

Author(s):

Gregor Sočan

Keyword(s):

Simulation Study ◽

Principal Components ◽

Common Factor ◽

Principal Component ◽

Component Model ◽

Bootstrap Procedure ◽

Factor Loadings ◽

Component Loadings ◽

Principal Component Model ◽

Two Populations

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.

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Assessing Person Fit With the Information Matrix Test

Methodology ◽

10.1027/1614-2241/a000085 ◽

2015 ◽

Vol 11 (1) ◽

pp. 3-12 ◽

Cited By ~ 2

Author(s):

Jochen Ranger ◽

Jörg-Tobias Kuhn

Keyword(s):

Simulation Study ◽

Type I Error ◽

Information Matrix ◽

Small Samples ◽

Type I ◽

Person Fit ◽

Power Of The Test ◽

Order Expansion ◽

Trait Stability ◽

Information Matrix Test

In this manuscript, a new approach to the analysis of person fit is presented that is based on the information matrix test of White (1982) . This test can be interpreted as a test of trait stability during the measurement situation. The test follows approximately a χ2-distribution. In small samples, the approximation can be improved by a higher-order expansion. The performance of the test is explored in a simulation study. This simulation study suggests that the test adheres to the nominal Type-I error rate well, although it tends to be conservative in very short scales. The power of the test is compared to the power of four alternative tests of person fit. This comparison corroborates that the power of the information matrix test is similar to the power of the alternative tests. Advantages and areas of application of the information matrix test are discussed.

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