scholarly journals autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0257682
Author(s):  
Matthew G. R. Courtney ◽  
Kevin C. T. Chang ◽  
Bing Mei ◽  
Kane Meissel ◽  
Luke I. Rowe ◽  
...  
Keyword(s):  
Test Performance ◽  
Rasch Analysis ◽  
Large Scale ◽  
Secondary Data ◽  
Scoring Systems ◽  
Theory Model ◽  
Large Scale Assessment ◽  
R Shiny ◽  
Student Test ◽  
Credit Data

In this paper, we present autopsych, a novel online tool that allows school assessment experts, test developers, and researchers to perform routine psychometric analyses and equating of student test data and to examine the effect of student demographic and group conditions on student test performance. The app extends current open-source software by providing (1) extensive embedded result narration and summaries for written reports, (2) improved handling of partial credit data via customizable item-person Wright maps, (3) customizable item- and person-flagging systems, (4) item-response theory model constraints and controls, (5) many-facets Rasch analysis to examine item bias, (6) Rasch fixed item equating for mapping student ability across test forms, (7) tabbed spreadsheet outputs and immediate options for secondary data analysis, (8) customizable graphical color schemes, (9) extended ANOVA analysis for examining group differences, and (10) inter-rater reliability analyses for the verifying the consistency of rater scoring systems. We present the app’s architecture and functionalities and test its performance with simulated and real-world small-, medium-, and large-scale assessment data. Implications and planned future developments are also discussed.

scholarly journals A Bias-Corrected RMSD Item Fit Statistic: An Evaluation and Comparison to Alternatives

2019 ◽  
Vol 45 (3) ◽  
pp. 251-273 ◽  
Author(s):  
Carmen Köhler ◽  
Alexander Robitzsch ◽  
Johannes Hartig
Keyword(s):  
Unbiased Estimator ◽  
Large Scale ◽  
Type I Error ◽  
Significance Test ◽  
Theory Model ◽  
Type I ◽  
Test Statistic ◽  
Large Scale Assessment ◽  
Parametric Bootstrapping ◽  
Item Fit

Testing whether items fit the assumptions of an item response theory model is an important step in evaluating a test. In the literature, numerous item fit statistics exist, many of which show severe limitations. The current study investigates the root mean squared deviation (RMSD) item fit statistic, which is used for evaluating item fit in various large-scale assessment studies. The three research questions of this study are (1) whether the empirical RMSD is an unbiased estimator of the population RMSD; (2) if this is not the case, whether this bias can be corrected; and (3) whether the test statistic provides an adequate significance test to detect misfitting items. Using simulation studies, it was found that the empirical RMSD is not an unbiased estimator of the population RMSD, and nonparametric bootstrapping falls short of entirely eliminating this bias. Using parametric bootstrapping, however, the RMSD can be used as a test statistic that outperforms the other approaches—infit and outfit, S − X 2—with respect to both Type I error rate and power. The empirical application showed that parametric bootstrapping of the RMSD results in rather conservative item fit decisions, which suggests more lenient cut-off criteria.

scholarly journals Revisiting Differential Item Functioning: Implications for Fairness Investigation

2012 ◽  
Vol 4 (2) ◽  
pp. 74
Author(s):  
Jinyan Huang ◽  
Turgay Han
Keyword(s):  
Differential Item Functioning ◽  
Test Performance ◽  
Large Scale ◽  
Standard Procedure ◽  
American Psychological Association ◽  
American Educational Research Association ◽  
National Council ◽  
Research Association ◽  
Large Scale Assessment ◽  
Item Functioning

Fairness has been the priority in educational assessments during the past few decades. Differential item functioning (DIF) becomes an important statistical procedure in the investigation of assessment fairness. For any given large-scale assessment, DIF evaluation is suggested as a standard procedure by American Educational Research Association, American Psychological Association, and National Council on Measurement in Education. This procedure often affords opportunities to check for group differences in test performance and investigate whether or not these differences indicate bias. However, current DIF research has received several criticisms. Revisiting DIF, this paper critically reviews current DIF research and proposes new directions for DIF research in the investigation of assessment fairness.

Large-Scale Assessment and English Language Learners With Disabilities

2015 ◽  
Vol 31 (5) ◽  
pp. 551-583 ◽  
Author(s):  
Kristin K. Liu ◽  
Jenna M. Ward ◽  
Martha L. Thurlow ◽  
Laurene L. Christensen
Keyword(s):  
English Language Learners ◽  
School Improvement ◽  
Language Learners ◽  
Test Performance ◽  
Large Scale ◽  
English Language ◽  
Large Scale Assessment ◽  
State Education ◽  
Education Agencies ◽  
High Standards

This article highlights a set of principles and guidelines, developed by a diverse group of specialists in the field, for appropriately including English language learners (ELLs) with disabilities in large-scale assessments. ELLs with disabilities make up roughly 9% of the rapidly increasing ELL population nationwide. In spite of the small overall percentage of students that they represent, this group experiences significant learning and assessment challenges. In the context of successfully educating all students to high standards, it is important for state education agencies, policymakers, and local education agencies to improve achievement outcomes for these students. One of the first steps in improving test performance is to design and implement comprehensive and accessible assessment policies, and consequently assessments, that address the specific needs of ELLs with disabilities. Doing so will give them the chance to demonstrate the knowledge and skills they have, thus allowing the test results to more accurately show areas for school improvement.

Using Web-based Testing for Large-Scale Assessment

2013 ◽  
Author(s):  
Laura S. Hamilton ◽  
Stephen P. Klein ◽  
William Lorie
Keyword(s):  
Large Scale ◽  
Web Based ◽  
Large Scale Assessment ◽  
Scale Assessment

Crowdfunding as an Alternative Method of Raising Capital

e-Finanse ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 56-66
Author(s):  
Katarzyna Wierzbicka
Keyword(s):  
Financial Market ◽  
Comparative Research ◽  
Large Scale ◽  
New Ventures ◽  
Secondary Data ◽  
Polish Literature ◽  
Investment Projects ◽  
Research Task ◽  
Type Of Institution ◽  
Insufficient Knowledge

AbstractCrowdfunding is a method of financing new ventures, commercial, cultural or social, often in return for future products or actions, engaged in by many investors. Currently, it is an important element in the structure of available sources of financing for investment projects. Despite the interest of potential investors, individual social sponsors and large-scale activities of institutions promoting knowledge about the functioning of crowdfunding aimed at encouraging and promoting it as a source of capital for new ventures, there is a lack of knowledge and, consequently, experience on its development and achievement. The aim of this study is to analyze this source of financing, assess its development globally and in Poland. In the preparation of the article,. a critical analysis of foreign and Polish literature was carried out, and descriptive and comparative research methods applied. The research task undertaken in the study was to analyze the crowdfunding market globally and in Poland. The Polish crowdfunding platforms were detailed and compared in terms of value in relation to the largest global platforms. The source for analyses of crowdfunding development in Poland was available literature on the analyzed topic and secondary data from the websites of specialized internet platforms. The article depicts a new, but important, aspect of financing the activity of enterprises, which is crowdfunding. It should be emphasized that there is still insufficient knowledge about this type of institution and, as a result, the importance and role that social financing plays in the financial market.

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

2020 ◽  
Author(s):  
Christina Schindler ◽  
Hannah Baumann ◽  
Andreas Blum ◽  
Dietrich Böse ◽  
Hans-Peter Buchstaller ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Large Scale ◽  
Active Drug ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Energy Calculation ◽  
Large Scale Assessment ◽  
New Public ◽  
Binding Free Energy Calculations

Here we present an evaluation of the binding affinity prediction accuracy of the free energy calculation method FEP+ on internal active drug discovery projects and on a large new public benchmark set.<br>

scholarly journals Diagnosis of tuberculosis in wildlife: a systematic review

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Jobin Thomas ◽  
Ana Balseiro ◽  
Christian Gortázar ◽  
María A. Risalde
Keyword(s):  
Systematic Review ◽  
Test Performance ◽  
Diagnostic Tests ◽  
Large Scale ◽  
Diagnostic Techniques ◽  
Review Literature ◽  
Meat Industry ◽  
Post Mortem ◽  
Serological Tests ◽  
Ongoing Research

AbstractAnimal tuberculosis (TB) is a multi-host disease caused by members of the Mycobacterium tuberculosis complex (MTC). Due to its impact on economy, sanitary standards of milk and meat industry, public health and conservation, TB control is an actively ongoing research subject. Several wildlife species are involved in the maintenance and transmission of TB, so that new approaches to wildlife TB diagnosis have gained relevance in recent years. Diagnosis is a paramount step for screening, epidemiological investigation, as well as for ensuring the success of control strategies such as vaccination trials. This is the first review that systematically addresses data available for the diagnosis of TB in wildlife following the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The article also gives an overview of the factors related to host, environment, sampling, and diagnostic techniques which can affect test performance. After three screenings, 124 articles were considered for systematic review. Literature indicates that post-mortem examination and culture are useful methods for disease surveillance, but immunological diagnostic tests based on cellular and humoral immune response detection are gaining importance in wildlife TB diagnosis. Among them, serological tests are especially useful in wildlife because they are relatively inexpensive and easy to perform, facilitate large-scale surveillance and can be used both ante- and post-mortem. Currently available studies assessed test performance mostly in cervids, European badgers, wild suids and wild bovids. Research to improve diagnostic tests for wildlife TB diagnosis is still needed in order to reach accurate, rapid and cost-effective diagnostic techniques adequate to a broad range of target species and consistent over space and time to allow proper disease monitoring.

scholarly journals Predicting Shifts in Land Suitability for Maize Cultivation Worldwide Due to Climate Change: A Modeling Approach

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 295
Author(s):  
Yuan Gao ◽  
Anyu Zhang ◽  
Yaojie Yue ◽  
Jing’ai Wang ◽  
Peng Su
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Large Scale ◽  
Land Suitability ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
Maize Cultivation ◽  
Large Scale Screening ◽  
Selection Of

Suitable land is an important prerequisite for crop cultivation and, given the prospect of climate change, it is essential to assess such suitability to minimize crop production risks and to ensure food security. Although a variety of methods to assess the suitability are available, a comprehensive, objective, and large-scale screening of environmental variables that influence the results—and therefore their accuracy—of these methods has rarely been explored. An approach to the selection of such variables is proposed and the criteria established for large-scale assessment of land, based on big data, for its suitability to maize (Zea mays L.) cultivation as a case study. The predicted suitability matched the past distribution of maize with an overall accuracy of 79% and a Kappa coefficient of 0.72. The land suitability for maize is likely to decrease markedly at low latitudes and even at mid latitudes. The total area suitable for maize globally and in most major maize-producing countries will decrease, the decrease being particularly steep in those regions optimally suited for maize at present. Compared with earlier research, the method proposed in the present paper is simple yet objective, comprehensive, and reliable for large-scale assessment. The findings of the study highlight the necessity of adopting relevant strategies to cope with the adverse impacts of climate change.

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