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Journal articles on the topic 'Test and validation'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Liao, Hsiu-Li, Chen-Huei Chou, and Wan-Chun Chao. "Functional Validation and Test Automation for Android Apps." International Journal of Machine Learning and Computing 4, no. 6 (2014): 553–58. http://dx.doi.org/10.7763/ijmlc.2014.v6.472.

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2

Yoneya, A., M. Nonokawa, Y. Hashimoto, and Y. Togari. "Model Validation Test." IFAC Proceedings Volumes 27, no. 2 (May 1994): 119–24. http://dx.doi.org/10.1016/s1474-6670(17)48140-7.

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3

Krumm, Stefan, Joachim Hüffmeier, and Filip Lievens. "Experimental Test Validation." European Journal of Psychological Assessment 35, no. 2 (March 2019): 225–32. http://dx.doi.org/10.1027/1015-5759/a000393.

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Abstract. Although the vast majority of validation studies rely on correlational validity evidence, there is an increased recognition that validity should also focus on whether variations in the focal psychological attribute lead to variations in the measurement outcomes. Therefore, calls have been made that validity evidence should also be gathered through experiments. Existing experimental validation strategies focus on manipulating psychological attributes and their effects on measurement outcomes. In the current manuscript, we present an additional and complementary approach that focuses on manipulating test elements (instead of psychological attributes) that are considered indispensable for test functioning. Examples from personality, situational judgment, emotional intelligence, and reading comprehension domains are presented to illustrate our approach. The presented approach is integrated into existing validation strategies.

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4

Ordóñez-Ordóñez, Leonardo Elías, Eveling Rojas-Roncancio, Víctor Hernández-Alarcón, Rafael Jaramillo-Safón, Jose Prieto-Rivera, Jose Guzmán-Durán, Jose Lora-Falquez, Marcela Escobar, and Esther Sofía Angulo-Martínez. "Diagnostic Test Validation." Otology & Neurotology 30, no. 6 (September 2009): 820–25. http://dx.doi.org/10.1097/mao.0b013e3181b11eb2.

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5

Flint, Oliver P. "In Vitro Test Validation." Alternatives to Laboratory Animals 19, no. 1 (February 1991): 140–42. http://dx.doi.org/10.1177/026119299101900122.

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6

Frederick, Richard I., and Stephen C. Bowden. "The Test Validation Summary." Assessment 16, no. 3 (October 6, 2008): 215–36. http://dx.doi.org/10.1177/1073191108325005.

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7

Lacot, Emilie, Mohammad H. Afzali, and Stéphane Vautier. "Test Validation Without Measurement." European Journal of Psychological Assessment 32, no. 3 (July 2016): 204–14. http://dx.doi.org/10.1027/1015-5759/a000253.

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Abstract. Test validation based on usual statistical analyses is paradoxical, as, from a falsificationist perspective, they do not test that test data are ordinal measurements, and, from the ethical perspective, they do not justify the use of test scores. This paper (i) proposes some basic definitions, where measurement is a special case of scientific explanation; starting from the examples of memory accuracy and suicidality as scored by two widely used clinical tests/questionnaires. Moreover, it shows (ii) how to elicit the logic of the observable test events underlying the test scores, and (iii) how the measurability of the target theoretical quantities – memory accuracy and suicidality – can and should be tested at the respondent scale as opposed to the scale of aggregates of respondents. (iv) Criterion-related validity is revisited to stress that invoking the explanative power of test data should draw attention on counterexamples instead of statistical summarization. (v) Finally, it is argued that the justification of the use of test scores in specific settings should be part of the test validation task, because, as tests specialists, psychologists are responsible for proposing their tests for social uses.

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8

Not Available, Not Available. "Validation of test methods." Accreditation and Quality Assurance 3, no. 1 (January 28, 1998): 29–32. http://dx.doi.org/10.1007/s007690050179.

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9

Ekstrøm, Claus Thorn. "Teaching ‘Instant Experience’ with Graphical Model Validation Techniques." Teaching Statistics 36, no. 1 (September 19, 2013): 23–26. http://dx.doi.org/10.1111/test.12027.

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10

Anastasi, Anne. "Evolving Concepts of Test Validation." Annual Review of Psychology 37, no. 1 (January 1986): 1–16. http://dx.doi.org/10.1146/annurev.ps.37.020186.000245.

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11

Geisinger, Kurt F. "The Metamorphosis to Test Validation." Educational Psychologist 27, no. 2 (March 1992): 197–222. http://dx.doi.org/10.1207/s15326985ep2702_5.

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12

Weinstock, Martin A. "Validation of a Diagnostic Test." Archives of Dermatology 125, no. 9 (September 1, 1989): 1260. http://dx.doi.org/10.1001/archderm.1989.01670210098018.

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13

Mayer, J. T. B., L. Montanez, J. A. Roberts, and R. D. Graves. "Avionics systems validation test environments." IEEE Aerospace and Electronic Systems Magazine 24, no. 1 (January 2009): 31–37. http://dx.doi.org/10.1109/maes.2009.4772752.

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14

Coleman, D. "Theoretical Evaluation Self-Test (TEST): A preliminary validation study." Social Work Research 28, no. 2 (June 1, 2004): 117–28. http://dx.doi.org/10.1093/swr/28.2.117.

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15

Durvasula, Srinivas, and Steven Lysonski. "Descriptive analytics: its power to test the applicability of cross-national scales in exploratory studies." Innovative Marketing 12, no. 3 (December 28, 2016): 34–44. http://dx.doi.org/10.21511/im.12(3).2016.03.

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Conventional methodology for validating measures in consumer research relies on structural equation modeling. But, this procedure requires a fairly large sample size and a clear conceptualization of the relationship between individual items and various scale dimensions. Neither of these requirements may be met in exploratory cross-national studies. Hence, this paper addresses scale validation issues in exploratory cross-national research, where sample size is a major concern. Specifically, it uses cross-national data on the vanity measure as an exemplar and a battery of descriptive analytics to show how to assess scaling assumptions, reliability, and dimensionality of consumer behavior measures. The scale validation procedure the authors describe in this paper has implications for researchers who use multi-item rating scales as measures of consumer behavior constructs. Keywords: cross-cultural, scale validation, exploratory research, cross-national, scale applicability JEL Classification: L1, L13, D11, D12, M31

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16

Griffith, D. Todd, Thomas G. Carne, and Joshua A. Paquette. "Modal Testing for Validation of Blade Models." Wind Engineering 32, no. 2 (March 2008): 91–102. http://dx.doi.org/10.1260/030952408784815817.

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The focus of this paper is a test program designed for wind turbine blades. Model validation is a comprehensive undertaking which requires carefully designing and executing experiments, proposing appropriate physics-based models, and applying correlation techniques to improve these models based on the test data. Structural models are useful for making decisions when designing a new blade or assessing blade performance, and the process of model validation is needed to ensure the quality of these models. Blade modal testing is essential for validation of blade structural models, and this report discusses modal test techniques required to achieve validation. Choices made in the design of a modal test can significantly affect the final test result. This study aims to demonstrate the importance of the proper pre-test design and test technique for validating blade structural models.

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17

Lutsik, Maksim Y., and Alexandra Y. Bergfeld. "MARI Card Test: Validation and Modification." Sibirskiy Psikhologicheskiy Zhurnal, no. 71 (March 1, 2019): 107–21. http://dx.doi.org/10.17223/17267080/71/6.

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18

Pinder, Craig C. "Rational/Statistical Method of Test Validation." Relations industrielles 34, no. 2 (April 12, 2005): 272–86. http://dx.doi.org/10.7202/028962ar.

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This study demonstrates the application of a test validation procedure similar to that described by Mobley and Ramsay (1973) but which avoids the use of factor analysis in isolating dimensions upon which subsequent job subgrouping is based. Instead, a semi-judgmental, semi-statistical method was employed. Actual test validation data are reported which, although missing in Mobley and Ramsay's (1973) article, attest to the utility of a job grouping approach to the validation problem.

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19

Kim, Jung Tae. "Validation of a test screen design." Multimedia-Assisted Language Learning 10, no. 1 (April 2007): 62–80. http://dx.doi.org/10.15702/mall.2007.10.1.62.

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20

Wu, Amery D., and Jake E. Stone. "Validation Through Understanding Test-Taking Strategies." Journal of Psychoeducational Assessment 34, no. 4 (October 2015): 362–79. http://dx.doi.org/10.1177/0734282915608575.

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21

ROBSON, A. K., A. C. WOOLLONS, J. RYAN, C. HORROCKS, S. WILLIAMS, and P. J. D. DAWES. "Validation of the combined olfactory test." Clinical Otolaryngology 21, no. 6 (December 1996): 512–18. http://dx.doi.org/10.1111/j.1365-2273.1996.tb01101.x.

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22

Lynch, Brian, Fred Davidson, and Grant Henning. "Person dimensionality in language test validation." Language Testing 5, no. 2 (December 1988): 206–19. http://dx.doi.org/10.1177/026553228800500206.

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23

Prasad, U., S. Pradhan, P. Raj, P. Varmora, A. Panchal, A. Bano, and M. Ghate. "Validation test of fusion grade superconductors." IOP Conference Series: Materials Science and Engineering 171 (February 2017): 012150. http://dx.doi.org/10.1088/1757-899x/171/1/012150.

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24

Villalobos, Nicholas, Ross Davidson, Uzair K. Ghori, Yara Abdou, Jawad Abukhalaf, and Rodrigo Vazquez Guillamet. "External Validation of the COmorbidity Test." COPD: Journal of Chronic Obstructive Pulmonary Disease 14, no. 5 (September 3, 2017): 513–17. http://dx.doi.org/10.1080/15412555.2017.1354981.

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25

Balls, Michael, and Walter Karcher. "The Validation of Alternative Test Methods." Alternatives to Laboratory Animals 23, no. 6 (November 1995): 884–86. http://dx.doi.org/10.1177/026119299502300616.

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26

FARRELL, JAMES L., and FRANK VAN GRAAS. "Statistical Validation for GPS Integrity Test." Navigation 39, no. 2 (June 1992): 205–16. http://dx.doi.org/10.1002/j.2161-4296.1992.tb01875.x.

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27

IJzerman-Boon, Pieta C., and Edwin R. van den Heuvel. "Validation of qualitative microbiological test methods." Pharmaceutical Statistics 14, no. 2 (November 21, 2014): 120–28. http://dx.doi.org/10.1002/pst.1663.

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28

Sireci, Stephen G. "On Validity Theory and Test Validation." Educational Researcher 36, no. 8 (November 2007): 477–81. http://dx.doi.org/10.3102/0013189x07311609.

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Lissitz and Samuelsen (2007) propose a new framework for conceptualizing test validity that separates analysis of test properties from analysis of the construct measured. In response, the author of this article reviews fundamental characteristics of test validity, drawing largely from seminal writings as well as from the accepted standards. He argues that a serious validation endeavor requires integration of construct theory, subjective analysis of test content, and empirical analysis of item and test score data. He argues that the proposals presented by Lissitz and Samuelsen require revision or clarification to be useful to practitioners for justifying the use of a test for a particular purpose. He discusses the strengths and limitations of their proposal, as well as major tenets from other validity perspectives.

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29

Fry, A. J. "Integrity-based self-validation test scheduling." IEEE Transactions on Reliability 52, no. 2 (June 2003): 162–67. http://dx.doi.org/10.1109/tr.2003.813154.

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30

Kim, Jungtae, and Daniel A. Craig. "Validation of a videoconferenced speaking test." Computer Assisted Language Learning 25, no. 3 (March 19, 2012): 257–75. http://dx.doi.org/10.1080/09588221.2011.649482.

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31

Watt, Neil J., Gordon D. Harkiss, Alastair Hayton, Keith Cutler, John Clarke, and Amanda O’Brien. "Validation of Enferplex bTB antibody test." Veterinary Record 187, no. 11 (November 27, 2020): 451.1–451. http://dx.doi.org/10.1136/vr.m4537.

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32

Hill, B. D., Charles A. Barkemeyer, Glenn N. Jones, Michael P. Santa Maria, Kyle S. Minor, and Jeffrey N. Browndyke. "Validation of the Coin Rotation Test." Neurologist 16, no. 4 (July 2010): 249–53. http://dx.doi.org/10.1097/nrl.0b013e3181b1d5b0.

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33

Fox, Benjamin Daniel, Nadav Sheffy, Baruch Vainshelboim, Leonardo Fuks, and Mordechai R. Kramer. "Step oximetry test: a validation study." BMJ Open Respiratory Research 5, no. 1 (August 2018): e000320. http://dx.doi.org/10.1136/bmjresp-2018-000320.

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IntroductionStep climbing is a potentially useful modality for testing exercise capacity. However, there are significant variations between test protocols and lack of consistent validation against gold standard cycle ergometry cardiopulmonary exercise testing (CPET). The purpose of the study was to validate a novel technique of exercise testing using a dedicated device.MethodsWe built a step oximetry device from an adapted aerobics step and pulse oximeter connected to a computer. Subjects performed lung function tests, a standard incremental cycle CPET and also a CPET while stepping on and off the step oximetry device to maximal exertion. Data from the step oximetry device were processed and correlated with standard measurements of pulmonary function and cycle CPET.ResultsWe recruited 89 subjects (57 years, 50 men). Oxygen uptake (VO2) was 0.9 mL/kg/min (95% CI −3.6 to 5.4) higher in the step test compared with the gold standard cycle CPET, p<0.001. VO2 in the two techniques was highly correlated (R=0.87, p<0.001). Work rate during stair climbing showed the best correlation with VO2 (R=0.69, p<0.0001). Desaturation during step climbing correlated negatively with diffusion capacity for carbon monoxide (r=−0.43, p<0.005). No adverse events occurred.ConclusionsThe step oximetry test was a maximal test of exertion in the subjects studied, achieving slightly higher VO2 than during the standard test. The test was safe to perform and well tolerated by the patients. Parameters derived from the step oximetry device correlated well with gold standard measurements. The step oximetry test could become a useful and standardisable exercise test for clinical settings where advanced testing is not available or appropriate.

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34

Lindquist, Timothy E., Kurt M. Gutzmann, David L. Remkes, and Gary McKee. "Optimization of validation test suite coverage." ACM SIGSOFT Software Engineering Notes 16, no. 3 (July 1991): 87–92. http://dx.doi.org/10.1145/127099.127126.

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35

Landy, Frank J. "Introduction: Case studies in test validation." Journal of Business and Psychology 7, no. 2 (1992): 111–17. http://dx.doi.org/10.1007/bf01013922.

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36

Henck, Judith W., Denise Traxler Frahm, and John A. Anderson. "Validation of automated behavioral test systems." Neurotoxicology and Teratology 18, no. 2 (March 1996): 189–97. http://dx.doi.org/10.1016/0892-0362(95)02058-6.

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37

Syer, Mark D., Weiyi Shang, Zhen Ming Jiang, and Ahmed E. Hassan. "Continuous validation of performance test workloads." Automated Software Engineering 24, no. 1 (April 1, 2016): 189–231. http://dx.doi.org/10.1007/s10515-016-0196-8.

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38

Ramoškienė, Eugenija, Mykolas Gladkovas, and Mudis Šalkauskas. "Validation of salt spray corrosion test." Accreditation and Quality Assurance 8, no. 5 (April 23, 2003): 235–41. http://dx.doi.org/10.1007/s00769-003-0624-x.

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39

Park, Jason Y., Paolo Fortina, and Larry J. Kricka. "Genomic Test Validation for Incidental Findings." Clinical Chemistry 60, no. 2 (February 1, 2014): 292–93. http://dx.doi.org/10.1373/clinchem.2013.210609.

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40

Anggawijayanto, Erydani, and Thomas Dicky Hastjarjo. "Validation of Indonesian Words Memory Test." Journal of Educational, Health and Community Psychology 10, no. 1 (March 11, 2021): 28. http://dx.doi.org/10.12928/jehcp.v10i1.18463.

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41

Kraft, Gina Leigh, and Maddie Dow. "Validation of the Polar Fitness Test." International Journal for Innovation Education and Research 6, no. 1 (January 31, 2018): 27–34. http://dx.doi.org/10.31686/ijier.vol6.iss1.893.

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Aerobic capacity testing can be beneficial to coaches, physical educators, and trainers in the process of designing aerobic training programs. However, testing in a laboratory can be costly. Polar heart rate monitors provide a fitness test that estimates aerobic capacity without having to use expensive equipment. The purpose of this study was to determine the efficacy of the Polar fitness test in comparison to the laboratory test. Eighteen college age students completed the Polar fitness test along with a laboratory test for aerobic capacity. The laboratory test consisted of a maximal Bruce protocol treadmill test while the subject was connected to a metabolic cart. The study found that the Polar fitness test provides results that are not statistically different from the metabolic cart results (t = 1.681, p = 0.111). Additionally, the 2 tests were strongly correlated (r = 0.545, p = 0.019). This indicates that the Polar fitness test may be an appropriate means of aerobic capacity testing for those not needing the accuracy of expensive laboratory equipment.

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42

Impellizzeri, Franco M., and Samuele M. Marcora. "Test Validation in Sport Physiology: Lessons Learned From Clinimetrics." International Journal of Sports Physiology and Performance 4, no. 2 (June 2009): 269–77. http://dx.doi.org/10.1123/ijspp.4.2.269.

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We propose that physiological and performance tests used in sport science research and professional practice should be developed following a rigorous validation process, as is done in other scientific fields, such as clinimetrics, an area of research that focuses on the quality of clinical measurement and uses methods derived from psychometrics. In this commentary, we briefly review some of the attributes that must be explored when validating a test: the conceptual model, validity, reliability, and responsiveness. Examples from the sport science literature are provided.

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43

Kim, Jin-Sun, Yeoung-Min Han, and Youngsung Ko. "Construction and Validation Test of Turbopump Real-propellant Test Facility." Journal of the Korean Society of Propulsion Engineers 19, no. 4 (August 1, 2015): 85–93. http://dx.doi.org/10.6108/kspe.2015.19.4.085.

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44

Zhang, J., H. Xie, PS Kandhal, and RD Powell. "Field Validation of Superpave Shear Test on NCAT Test Track." Journal of ASTM International 2, no. 3 (2005): 12281. http://dx.doi.org/10.1520/jai12281.

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45

Wu, Runhui, Jiaqi Liu, Jutao Liu, Liu Xin, Hanzhong Xu, and Wei Liang. "The Computation Model and Its Test Validation of Low-Energy Plasma Collision Frequency." International Journal of Applied Physics and Mathematics 5, no. 2 (2015): 94–104. http://dx.doi.org/10.17706/ijapm.2015.5.2.94-104.

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46

de Izarra, G., B. Geslot, S. Bréaud, A. Pepino, J.-F. Villard, and P. Filliatre. "Test Results of an Innovative and Modular Sensor Design for Fission Chamber Studies." EPJ Web of Conferences 225 (2020): 03006. http://dx.doi.org/10.1051/epjconf/202022503006.

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Since many years, the Instrumentation, Sensors and Dosimetry laboratory at CEA Cadarache has been working to propose innovative and robust design of fission chambers. In this framework, few simulation tools like Chester or PyFc were developed to make detector prototyping and optimisation possible. Up to now, the code experimental validations are scarce mainly because of the lack of flexibility of regular fission chambers. In order to set up an experimental database for code validation, an innovative modular twin fission chamber, the CFTM, was designed. It allows to set with precision the inter-electrode gap, the filling gas pressure as well as the fissile deposit used. This detector was irradiated in Minerve zero power reactor in order to gather results for code validation. Thanks to a calibration procedure, a bank of experimental results is available for simulation validation.

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47

Thall, Peter F., Richard Simon, and David A. Grier. "Test-Based Variable Selection via Cross-Validation." Journal of Computational and Graphical Statistics 1, no. 1 (1992): 41. http://dx.doi.org/10.2307/1390599.

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48

Jablonski, Michael R., Nina King, Yongbao Wang, Joel G. Winner, Lucas R. Watterson, Sandra Gunselman, and Bryan M. Dechairo. "Analytical validation of a psychiatric pharmacogenomic test." Personalized Medicine 15, no. 3 (May 2018): 189–97. http://dx.doi.org/10.2217/pme-2017-0094.

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49

Wang, Tie, Li Qing Wang, Cao Dai, and Jing Shang. "Test Validation Analysis Based on Fuzzy Assessment." Advanced Materials Research 433-440 (January 2012): 2749–54. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.2749.

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In the student culture work, the examination has turned into a recognized assessment tools in the society and different professional certificate authority depend on the examination in many institutions. While the strength and weakness of the examination quality will affect the fairness objectivity and effectiveness of the test results. The study of index and evaluation of the examination is not only a scale that evaluate the effectiveness of the examination but also an important tool that improve the quality of the examination. This paper adopts standard establishment distribution model of employer by the use of extended fuzzy evaluation and will use downhill simplex optimization to establish distribution model results of the examination and calculate index by Aitken interpolation and composite trapezoidal integration method. When the multiple targets are evaluated, COSINE similarity need be used. This method can realize the test validation analysis of small sample.

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50

Aglietti, Guglielmo S., Marcello Remedia, Matteo Appolloni, and Andrew Kiley. "Spacecraft Structure Model Validation and Test Philosophy." AIAA Journal 57, no. 5 (May 2019): 2109–22. http://dx.doi.org/10.2514/1.j057757.

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