Conducting External Profile Analysis with Multiple Regression

Internal profile analysis methods that employ multidimensional scaling or cluster analysis continue to receive application in educational and psychological research. One critique of these methods is that there is no guarantee that the identified profiles will exhibit criterion or diagnostic validity. Recently, an external profile analysis technique was developed using multiple regression. The external profile analysis method yields a profile that is derived to explicitly relate to a criterion. This paper introduces the new external profile analysis method and presents an application that uses 8th grade NAEP reading test scores as the criterion and background questions pertaining to students’ out-of-school reading and writing behaviors and experiences as predictors. The external profile analysis sought to uncover a type or pattern of out-of-school experiences that related to reading achievement. The profile analysis findings were also used to interpret group performance differences and to identify possible recommendations for closing the male reading achievement gap. Accessed 15,725 times on https://pareonline.net from January 09, 2008 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Vocational Evaluation – Deafness

Non

Wildfire Smoke Effects on Lake-Habitat Specific Metabolism: Toward a Conceptual Understanding

The impacts of wildfire smoke on lake habitats remains unclear. We determined the metabolic response to smoke in the epi-pelagic and two littoral habitats in Castle Lake, California. We compared light regime, gross primary production, ecosystem respiration, and net ecosystem production in years with and without smoke. During the smoke period incident ultraviolet-B (UV-B) radiation and photosynthetically active radiation (PAR) decreased by 53% and 28%, respectively, while the water column extinction coefficient of UV-B and PAR increased by 20% and 18% respectively. Epi-pelagic productivity increased during smoke cover because of decreased solar inputs. PAR values remained sufficient to saturate productivity, suggesting observed differences were primarily the result of changes in UV-B. Littoral-benthic productivity did not change, possibly reflecting adaptation to high-intensity UV-B light in these habitats. Our results highlight the importance of understanding how prolonged wildfire smoke alters the amount of energy produced from specific habitats in lakes.Fil: Scordo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. University of Nevada; Estados UnidosFil: Sadro, Steven. University of California at Davis; Estados UnidosFil: Culpepper, Joshua. University of California at Davis; Estados Unidos. University of Nevada; Estados UnidosFil: Seitz, Carina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. University of Nevada; Estados UnidosFil: Chandra, Sudeep. University of Nevada; Estados Unido

Structural considerations for aircraft payload modification-P-3H zero fuel weight increase.

The Navy is considering the feasibility of increasing the patrol aircraft P-3C zero fuel weight enabling avionics and payload growth. This analysis examines the consequences to the structural requirements of the center section wing box. Two solutions to the structures field equations are investigated: a simplified hand solution for preliminary feasibility calculations and a more precise solution for design analysis. Together, the solutions provide a necessary check for the results. The simplified solution employs the Euler-Bernoulli assumption which generates a set of integrals expressed in terms of the assumed displacements. These integrals, when combined with simplified geometric shapes and symmetry, ultimately produce a decoupled matrix solution. The precise solution uses a PC based finite element method which simultaneously solves the field equations for basic elements to be linked together with the appropriate boundary conditions. For the current 135,000 pound gross weight lg load condition, the internal stresses calculated by finite element are in accord with those by simplified hand calculation. Extensions from this modeling will generate design criterion for the target 95,000 pound zero fuel weight aircraft as well as alternate flight or taxi conditions.http://archive.org/details/structuralconsid00culpLieutenant, United States NavyApproved for public release; distribution is unlimited

Vocational Evaluation – Deafness

Non

Clearer Analysis, Interpretation, and Communication in Organizational Research: A Bayesian Guide

Historically, organizational researchers have fully embraced frequentist statistics and null hypothesis significance testing (NHST). Bayesian statistics is an underused alternative paradigm offering numerous benefits for organizational researchers and practitioners: e.g., accumulating direct evidence for the null hypothesis (vs. ‘fail to reject the null’), capturing uncertainty across a distribution of population parameters (vs. a 95% confidence interval on a single point estimate) – and through these benefits, communicating statistical findings more clearly. Although organizational methodologists in the past have promoted Bayesian methods, only now is easy-to-use JASP statistical software available for more widespread implementation. Moreover, the software is free to download and use, is menu-driven, and is supported by an active multidisciplinary user community. Using JASP, our tutorial compares and contrasts frequentist and Bayesian approaches for two analyses: a multiple linear regression analysis and a linear mixed regression analysis

Differential prediction generalization in college admissions testing

We introduce the concept of differential prediction generalization in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student\u27s ethnicity and gender and whether this difference varies across samples. We compared 257,336 female and 220,433 male students across 339 samples, 29,734 Black and 304,372 White students across 247 samples, and 35,681 Hispanic and 308,818 White students across 264 samples collected from 176 colleges and universities between the years 2006 and 2008. Overall, results show a lack of differential prediction generalization because variability remains after accounting for methodological and statistical artifacts including sample size, range restriction, proportion of students across ethnicity- and gender-based subgroups, subgroup mean differences on the predictors (i.e., HSGPA, SAT-Critical Reading, SATMath, and SAT-Writing), and SDs for the predictors. We offer an agenda for future research aimed at understanding several contextual reasons for a lack of differential prediction generalization based on ethnicity and gender. Results from such research will likely lead to a better understanding of the reasons for differential prediction and interventions aimed at reducing or eliminating it when it exists