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Journal articles on the topic 'Conducting experiments'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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1

Ganguly, Abhijit, and Jim Euchner. "Conducting Business Experiments." Research-Technology Management 61, no. 2 (2018): 27–36. http://dx.doi.org/10.1080/08956308.2018.1421381.

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2

Boruch, Robert F. "Conducting social experiments." New Directions for Program Evaluation 1987, no. 34 (1987): 45–66. http://dx.doi.org/10.1002/ev.1452.

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3

Arechar, Antonio A., Simon Gächter, and Lucas Molleman. "Conducting interactive experiments online." Experimental Economics 21, no. 1 (2017): 99–131. http://dx.doi.org/10.1007/s10683-017-9527-2.

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4

Heisel, B., R. Hempelmann, O. Hartmann та R. Wäppling. "μSR-Experiments on proton-conducting oxides". Physica B: Condensed Matter 289-290 (серпень 2000): 487–90. http://dx.doi.org/10.1016/s0921-4526(00)00442-7.

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Galan, Daniel, Ruben Heradio, Luis de la Torre, Sebastian Dormido, and Francisco Esquembre. "Conducting Online Lab Experiments with Blockly." IFAC-PapersOnLine 50, no. 1 (2017): 13474–79. http://dx.doi.org/10.1016/j.ifacol.2017.08.2323.

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6

Hong Shen, Zheng Xu, B. Dalager, et al. "Conducting laboratory experiments over the Internet." IEEE Transactions on Education 42, no. 3 (1999): 180–85. http://dx.doi.org/10.1109/13.779896.

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Lúcio, Alessandro Dal’Col, Darlei M. Lambrecht, Bruno G. Sari, Dionatan K. Krysczun, and Cassiane Ubessi. "Experimental planning for conducting experiments with cucumber." Horticultura Brasileira 38, no. 2 (2020): 112–16. http://dx.doi.org/10.1590/s0102-053620200201.

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ABSTRACT In order to be considered highly reliable (showing very accurate results), an experiment needs to be very well planned. Defining the experimental plot size and number of replicates is fundamental to control the experimental error at the beginning of the experiment. The aim of this study was to estimate the plot size and the number of replicates sufficient to perform experiments with Cucumis sativus. A uniformity trial was installed in the first week of January 2017. The spacing used was 0.3 m between plants and 1 m between rows, resulting in 12 plants in each of the 12 cultivation rows and each basic experimental unit was composed of one plant. The variables observed in 18 harvests were average fruit mass (MMF, in g), average fruit length (CMF, in cm) and average fruit diameter (DMF, in cm). The harvests were analyzed individually and grouped to reduce experimental variability. The number of replicates and the plot size were estimated using the method of maximum curvature of the coefficient of variation. The plot size and the number of replicates were influenced by the variability in the rows and between the harvests. We recommend plots consisting of four plants per cultivation row with six replicates for the minimum significant difference by Tukey’s test, expressed in 25% the means percentage.

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Hariharan, Anuja, Marc Adam, Verena Dorner, et al. "Brownie: A Platform for Conducting NeuroIS Experiments." Journal of the Association for Information Systems 18, no. 4 (2017): 264–96. http://dx.doi.org/10.17705/1jais.00457.

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Goldfarb, Avi, Catherine Tucker, and Yanwen Wang. "Conducting Research in Marketing with Quasi-Experiments." Journal of Marketing 86, no. 3 (2022): 1–20. http://dx.doi.org/10.1177/00222429221082977.

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This article aims to broaden the understanding of quasi-experimental methods among marketing scholars and those who read their work by describing the underlying logic and set of actions that make their work convincing. The purpose of quasi-experimental methods is, in the absence of experimental variation, to determine the presence of a causal relationship. First, the authors explore how to identify settings and data where it is interesting to understand whether an action causally affects a marketing outcome. Second, they outline how to structure an empirical strategy to identify a causal empirical relationship. The article details the application of various methods to identify how an action affects an outcome in marketing, including difference-in-differences, regression discontinuity, instrumental variables, propensity score matching, synthetic control, and selection bias correction. The authors emphasize the importance of clearly communicating the identifying assumptions underlying the assertion of causality. Last, they explain how exploring the behavioral mechanism—whether individual, organizational, or market level—can actually reinforce arguments of causality.

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10

Sharav, Vera Hassner. "The ethics of conducting psychosis‐inducing experiments." Accountability in Research 7, no. 2-4 (1999): 137–67. http://dx.doi.org/10.1080/08989629908573948.

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11

Aguinis, Herman, and Sola O. Lawal. "Conducting field experiments using eLancing's natural environment." Journal of Business Venturing 27, no. 4 (2012): 493–505. http://dx.doi.org/10.1016/j.jbusvent.2012.01.002.

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Aguinis, Herman, and Sola O. Lawal. "Conducting Field Experiments Using eLancing’s Natural Environment." Academy of Management Proceedings 2012, no. 1 (2012): 10842. http://dx.doi.org/10.5465/ambpp.2012.10842abstract.

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13

Majima, Yoshimasa. "4. Conducting Online Psychological Experiments Using Crowdsourcing." Journal of The Institute of Image Information and Television Engineers 75, no. 4 (2021): 480–84. https://doi.org/10.3169/itej.75.480.

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14

Yensebayeva, G. M. "FEATURES OF CONDUCTING PHYSICAL EXPERIMENTS EXTRA CURRICULAR." МАТЕМАТИКА, ФИЗИКА ЖӘНЕ ИНФОРМАТИКАНЫ ОҚЫТУДЫҢ ӨЗЕКТІ МӘСЕЛЕЛЕРІ 9, no. 1 (2025): 34–45. https://doi.org/10.52081/mpimet.2025.v09.i1.051.

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Бұл мақалада сыныптан тыс физикалық эксперименттердің орындалу ерекшеліктері қарастырылады. Физикалық эксперимент – теориялық білімдерді тәжірибе жүзінде тексерудің негізгі әдісі болып табылады және оқушылардың ғылыми-зерттеу дағдыларын дамытуға ықпал етеді. Сыныптан тыс эксперименттер оқушылардың физика пәніне қызығушылығын арттырып, олардың өз бетінше іздену дағдыларын дамытады. Мұндай жұмыстар зерттеу дағдыларын жетілдіруге, теориялық білімді нақты тәжірибемен ұштастыруға көмектеседі. Сонымен қатар, мақалада виртуалды зертханалардың рөлі қарастырылады. Виртуалды эксперименттер оқушыларға күрделі физикалық құбылыстарды модельдеуге мүмкіндік бере отырып, қол жетімділікті және оқушылардың физиканы түсінуін арттырады. Зерттеу нәтижелері оқу процесіне физикалық эксперимент элементтерін енгізу нәтижелерін көрсетеді. Дәстүрлі және заманауи әдістерді үйлестіру оқушылардың ғылыми-зерттеу қабілеттерін қалыптастыруға және білім сапасын жақсартуға ықпал ететіні көрсетіледі. Оқушылардың өз бетінше орындайтын тәжірибелері, үй жағдайында жүргізілетін эксперименттер мен цифрлық технологиялар арқылы жасалатын зерттеулер физиканы оқытудың тиімділігін арттырады. Мақалада сыныптан тыс эксперименттердің білім беру сапасын жақсартуға қосатын үлесі қарастырылады және де виртуалды әдістерді үйлестіре қолданудың маңыздылығына негізделеді. Осылайша, физикалық эксперименттерді тиімді ұйымдастыру арқылы оқушылардың пәнге деген қызығушылығын арттыруға және зерттеушілік қабілеттерін дамытуға болады.

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15

Chung, Seok Won, Sae Hoon Kim, and Joo Han Oh. "Animal Experiments Using Rotator Cuff." Clinics in Shoulder and Elbow 17, no. 2 (2014): 84–90. http://dx.doi.org/10.5397/cise.2014.17.2.84.

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In conducting animal studies using rotator cuff, researchers should select the appropriate types of animals and experimental models. This should also be followed by complete understanding of the selected experimental animals as well as the methods for evaluating the results. Thus, researchers could minimize errors and failure in conducting animal experimental studies. Further, this will provide a basis of establishing new idea and theory about rotator cuff diseases.

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16

Wilsdorf, Pia, Jakob Heller, Kai Budde, et al. "A Model-Driven Approach for Conducting Simulation Experiments." Applied Sciences 12, no. 16 (2022): 7977. http://dx.doi.org/10.3390/app12167977.

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With the increasing complexity of simulation studies, and thus increasing complexity of simulation experiments, there is a high demand for better support for them to be conducted. Recently, model-driven approaches have been explored for facilitating the specification, execution, and reproducibility of simulation experiments. However, a more general approach that is suited for a variety of modeling and simulation areas, experiment types, and tools, which also allows for further automation, is still missing. Therefore, we present a novel model-driven engineering (MDE) framework for simulation studies that extends the state-of-the-art of conducting simulation experiments in the following ways: (a) Providing a structured representation of the various ingredients of simulation experiments in the form of meta models and collecting them in a repository improves knowledge sharing across application domains and simulation approaches. (b) Specifying simulation experiments in the quasi-standardized form of the meta models (e.g., via a GUI) and, subsequently, performing the automatic generation of experiment specifications in a language of choice increases both the productivity and quality of complex simulation experiments. (c) Automatic code transformation between specification languages via the meta models enables the reusability of simulation experiments. (d) Integrating the framework using a command-line interface allows for further automation of subprocesses within a simulation study. We demonstrate the advantages and practicality of our approach using real simulation studies from three different fields of simulation (stochastic discrete-event simulation of a cell signaling pathway, virtual prototyping of a neurostimulator, and finite element analysis of electric fields) and various experiment types (global sensitivity analysis, time course analysis, and convergence testing). The proposed framework can be the starting point for further automation of simulation experiments and, therefore, can assist in conducting simulation studies in a more systematic and effective manner. For example, based on this MDE framework, approaches for automatically selecting and parametrizing experimentation methods, or for planning follow-up activities depending on the context of the simulation study, could be developed.

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17

Adams, D. C., M. K. Nielsen, W. H. Schacht, and R. T. Clark. "Designing and conducting experiments for range beef cows." Journal of Animal Science 77, E-Suppl (2000): 1. http://dx.doi.org/10.2527/jas2000.77e-suppl1u.

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18

Ledermann, Florian, and Georg Gartner. "Towards Conducting Reproducible Distributed Experiments in the Geosciences." AGILE: GIScience Series 2 (June 4, 2021): 1–7. http://dx.doi.org/10.5194/agile-giss-2-33-2021.

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Abstract. We present a system for running experiments and user studies that can be effortlessly distributed across multiple heterogeneous devices. By taking into account specific requirements of the geosciences (geovisualization, cartography, location-based services), and by providing a clear and simple conceptual model for defining experiments, this system can help researchers implement empirical studies in less time or with increased functionality, and can lead to increased transparency and reproducibility of studies for other researchers. The versatility of the proposed system is demonstrated in three case studies where the system is put to use in widely different application scenarios.

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19

Hawkins, Robert X. D. "Conducting real-time multiplayer experiments on the web." Behavior Research Methods 47, no. 4 (2014): 966–76. http://dx.doi.org/10.3758/s13428-014-0515-6.

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20

McGraw, Kenneth O., and Wei-Sheng Tsai. "A Computer Program for Conducting Mental Rotation Experiments." Teaching of Psychology 20, no. 4 (1993): 246–47. http://dx.doi.org/10.1207/s15328023top2004_16.

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Timed mental rotation tests produce reliable effects that are ideal for investigation in laboratory classes. This article describes a PASCAL computer program capable of conducting a variety of user-designed mental rotation experiments. Design factors that users control include type of stimulus and degree of rotation. The program can be run on MS-DOS computers with VGA or EGA displays. An 80286 or faster microprocessor is recommended.

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21

NeSmith, D. S., P. L. Raymer, M. S. S. Rao, and D. C. Bridges. "A Durable, Lightweight Structure for Conducting Field Shading Experiments." HortScience 27, no. 12 (1992): 1274–75. http://dx.doi.org/10.21273/hortsci.27.12.1274.

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A low-cost field shading structure was developed that offers durability and simplicity. The quonset-type structure uses readily available materials, including polyvinyl chloride pipe, construction-grade reinforcing bars, nylon rope, and commercial shade fabric. The total cost for a 3.0 × 6.0 × 2.4-m (width/length/height) structure that provided 47% shade was $88.00. The structure offers substantial flexibility in terms of size and degree of shading without significantly altering design. The structure was durable under a wide range of weather conditions, and the design allowed sufficient air movement to prevent a stagnant air layer from developing over the crop.

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22

Keegan, Brian, Katherine Ognyanova, Brooke Foucault Welles, et al. "Conducting Massively Open Online Social Experiments with Volunteer Science." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (October 14, 2014): 19–20. http://dx.doi.org/10.1609/hcomp.v2i1.13208.

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Volunteer Science is an online platform enabling anyone to participate in social science research. The goal of Volunteer Science is to build a thriving community of research participants and social science researchers for Massively Open Online Social Experiments (“MOOSEs”). The architecture of Volunteer Science has been built to be open to researchers, transparent to participants, and to facilitate the levels of concurrency needed for large scale social experiments. Since then, 14 experiments and 12 survey-based interventions have been developed and deployed, with subjects largely being recruited through paid advertising, word of mouth, social media, search, and Mechanical Turk. We are currently replicating several forms of social research to validate the platform, working with new collaborators, and developing new experiments. Moving forward our priorities are continuing to grow our user base, developing quality control processes and collaborators, diversifying our funding models, and creating novel research.

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23

Lancsar, Emily, and Jordan Louviere. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making." PharmacoEconomics 26, no. 8 (2008): 661–77. http://dx.doi.org/10.2165/00019053-200826080-00004.

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Inal, O. T., M. Bengisu, B. Morton, and R. H. Richman. "An apparatus for conducting experiments on solid‐particle erosion." Review of Scientific Instruments 66, no. 6 (1995): 3649–52. http://dx.doi.org/10.1063/1.1145482.

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Ilyas, Mohammad, Heike Grabsch, Ian O. Ellis, et al. "Guidelines and considerations for conducting experiments using tissue microarrays." Histopathology 62, no. 6 (2013): 827–39. http://dx.doi.org/10.1111/his.12118.

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26

Baekgaard, Martin, Caroline Baethge, Jens Blom-Hansen, et al. "Conducting Experiments in Public Management Research: A Practical Guide." International Public Management Journal 18, no. 2 (2015): 323–42. http://dx.doi.org/10.1080/10967494.2015.1024905.

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Rutgers, M. A., X. L. Wu, and W. B. Daniel. "Conducting fluid dynamics experiments with vertically falling soap films." Review of Scientific Instruments 72, no. 7 (2001): 3025–37. http://dx.doi.org/10.1063/1.1379956.

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Lau, Peter. "Conducting meaningful experiments: 40 steps to becoming a scientist." Evaluation Practice 17, no. 1 (1996): 93–94. http://dx.doi.org/10.1016/s0886-1633(96)90045-8.

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Huber, Bernd, and Krzysztof Z. Gajos. "Conducting online virtual environment experiments with uncompensated, unsupervised samples." PLOS ONE 15, no. 1 (2020): e0227629. http://dx.doi.org/10.1371/journal.pone.0227629.

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Deidda, Manuela, Claudia Geue, Noemi Kreif, Ruth Dundas, and Emma McIntosh. "A framework for conducting economic evaluations alongside natural experiments." Social Science & Medicine 220 (January 2019): 353–61. http://dx.doi.org/10.1016/j.socscimed.2018.11.032.

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31

Hoffman, Guy, and Xuan Zhao. "A Primer for Conducting Experiments in Human–Robot Interaction." ACM Transactions on Human-Robot Interaction 10, no. 1 (2020): 1–31. http://dx.doi.org/10.1145/3412374.

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Węgrzyn, Maria, Stanisław Wieteska, and Magdalena Janiszewska. "Compulsory Liability Insurance of the Entity Conducting Medical Experiments – Polemical Remarks." Financial Sciences 28, no. 2 (2023): 21–35. http://dx.doi.org/10.15611/fins.2023.2.03.

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Conducting medical experiments by healthcare entities is highly necessary as it is only through such actions that we can confirm the effectiveness of new solutions, however carrying out medical experiments involves unique risks that must/should be subject to special protection. The aim of this article is to address the debatable elements contained in the Regulation of the Minister of Finance regarding the civil liability of entities conducting medical experiments. The raised concerns are intended to improve the quality of the adopted legal solutions to increase the safety of all entities and individuals participating in the process of conducting medical experiments.

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MacKay, Douglas, and Averi Chakrabarti. "Government Policy Experiments and Informed Consent." Public Health Ethics 12, no. 2 (2018): 188–201. http://dx.doi.org/10.1093/phe/phy015.

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Abstract Governments are increasingly making use of field experiments to evaluate policy interventions in the spheres of education, public health and welfare. However, the research ethics literature is largely focused on the clinical context, leaving investigators, institutional review boards and government agencies with few resources to draw on to address the ethical questions they face regarding such experiments. In this article, we aim to help address this problem, investigating the conditions under which informed consent is required for ethical policy research conducted or authorized by government. We argue that investigators need not secure participants' informed consent when conducting government policy experiments if: (i) the government institution conducting or authorizing the experiment possesses a right to rule over the spheres of policy targeted by the research; and (ii) data collection does not involve the violation of participants' autonomy rights.

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Yerbekovna, Tillayeva Zebo. "CONDUCTING PROJECT WORK ON STUDYING AND GROWING BEAN SEEDS." International Journal of Advance Scientific Research 05, no. 12 (2024): 257–62. https://doi.org/10.37547/ijasr-04-12-39.

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Practical projects play a significant role in studying natural sciences. Linking theory with practice facilitates easier comprehension and retention of topics. For instance, examining the internal structure of a bean seed and observing its germination process in experiments can spark students' interest in science and develop their experimental skills. Additionally, such projects are beneficial in preparing students for life, teaching them to work systematically and according to plans.

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Li, Zhi, Po-Hsuan Lin, Si-Yuan Kong, Dongwu Wang, and John Duffy. "Conducting large, repeated, multi-game economic experiments using mobile platforms." PLOS ONE 16, no. 4 (2021): e0250668. http://dx.doi.org/10.1371/journal.pone.0250668.

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We demonstrate the possibility of conducting synchronous, repeated, multi-game economic decision-making experiments with hundreds of subjects in-person or remotely with live streaming using entirely mobile platforms. Our experiment provides important proof-of-concept that such experiments are not only possible, but yield recognizable results as well as new insights, blurring the line between laboratory and field experiments. Specifically, our findings from 8 different experimental economics games and tasks replicate existing results from traditional laboratory experiments despite the fact that subjects play those games/task in a specific order and regardless of whether the experiment was conducted in person or remotely. We further leverage our large subject population to study the effect of large (N = 100) versus small (N = 10) group sizes on behavior in three of the scalable games that we study. While our results are largely consistent with existing findings for small groups, increases in group size are shown to matter for the robustness of those findings.

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Honey-Rosés, Jordi, and Mark Stevens. "Commentary on the Absence of Experiments in Planning." Journal of Planning Education and Research 39, no. 3 (2017): 267–72. http://dx.doi.org/10.1177/0739456x17739352.

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A recent review by Jacques Du Toit, Nelius Boshoff, and Niclesse Mariette finds that planners rarely use experimental research designs. This commentary examines why experimentation is rare in planning and discusses the legitimate challenges involved with conducting experiments in a planning context. In doing so, we aim to foster a discussion on the feasibility of conducting experimental research in our field. While not all planning policies are amenable to experimentation, we see untapped potential in many areas of planning, especially on questions of public engagement. Collectively we hope that planners can begin to identify more instances in which experimental research is possible.

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Maxwell, Jordan, Kieran Wilson, Joseph Hughes, and Hanspeter Schaub. "Multisphere Method for Flexible Conducting Space Objects: Modeling and Experiments." Journal of Spacecraft and Rockets 57, no. 2 (2020): 225–34. http://dx.doi.org/10.2514/1.a34560.

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Smykowski, Krzysztof. "The Possibility of Conducting Experiments on Animals. Moral Theologian’s Reflections." Studia Ecologiae et Bioethicae 13, no. 2 (2015): 107–19. http://dx.doi.org/10.21697/seb.2015.13.2.06.

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The Catholic moral theology acknowledges a person’s right to use animals in compliance with their nature, while putting the emphasis on the obligation to treat them with proper sensitivity and kindness. !is right includes the possibility to conduct experiments on animals. Such experiments are allowed after meeting a range of conditions. Justifiable hopes for scientific development or for achieving practical goals are required. Also, the number of used animals should be limited and the pain and stress the animals feel ought to be minimized. The right balance should be maintained between those factors. Moreover, moral theology elevates the value of intentions, i.e., the objective for which the test results will be used. It can modify the moral classification of experiments, which on their own are good or neutral.

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Naumann, Anja, Angela Brunstein, and Josef F. Krems. "DEWEX: A system for designing and conducting Web-based experiments." Behavior Research Methods 39, no. 2 (2007): 248–58. http://dx.doi.org/10.3758/bf03193155.

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40

Theodore, Rachel M. "Conducting speech perception experiments remotely: Some tools, successes, and challenges." Journal of the Acoustical Society of America 149, no. 4 (2021): A109—A110. http://dx.doi.org/10.1121/10.0004670.

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41

Vendramini, Joao, Lynn Sollenberger, and Maria Lucia L. Silveira. "185 Opportunities and Challenges of Conducting Grazing Experiments in Pasturelands." Journal of Animal Science 99, Supplement_3 (2021): 99–100. http://dx.doi.org/10.1093/jas/skab235.179.

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Abstract Grasslands cover approximately 30% of the world area and research conducted in pasturelands has been crucial to realize the benefits of grassland contributions to livestock production and ecosystem services. The Forage and Grazing Terminology Task Force has developed a list of recommended nomenclature for grazing lands research and this effort has been a landmark to avoid misleading terms in research reports. Other challenges remain. The intrinsic variability of pastureland research data limits the capacity of researchers to detect differences among treatments. In addition, the quantity of resources and labor required by pastureland experiments may lead researchers to decrease the size of experimental units and/or number of replicates, exacerbating the limitations in detecting differences among treatments. In general, experimental units in grazing studies encompass relatively large areas, which may pose a challenge to identifying representative sampling units that reflect the experimental area. The use of indirect measurements to estimate forage mass is a feasible approach to increase the representativeness of forage quantity evaluations. The nutritive value determination of forage samples from grazing studies also has many limitations. The collection of samples representing the animal diet and the methods of nutritive value determination, primarily digestibility, are major areas of concern. For animal performance evaluations, determination of the correct experimental unit has been a frequent issue. Among animal measures, forage intake is one of the most influential factors affecting animal performance and the existent methodology to estimate forage intake by grazing animals has limitations, reducing the accuracy of the results. Development and validation of mathematical models to estimate the benefits of grasslands on livestock performance and ecosystem services are important steps in the evolution of grassland science, but in some cases additional data are needed to support this effort.

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42

Lekhu, Motshidisi A. "Physical Science Teachers’ Self-efficacy Beliefs on Conducting Laboratory Experiments." International Journal of Educational Sciences 14, no. 1-2 (2016): 102–9. http://dx.doi.org/10.1080/09751122.2016.11890483.

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43

Anand, Vic V., Ramji Balakrishnan, and Eva Labro. "A Framework for Conducting Numerical Experiments on Cost System Design." Journal of Management Accounting Research 31, no. 1 (2018): 41–61. http://dx.doi.org/10.2308/jmar-52057.

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ABSTRACT This paper aims to advance the use of numerical experiments in the study of cost system design. As with laboratory and field experiments, researchers must decide on the independent variables and their levels, the experimental design, and the dependent variables. Options for dependent and independent variables are ample, as are ways to model the relations among these variables. We provide a modular framework that provides structure to these variables, their definitions, and the modeling of connections among them. Further, we offer insights into the design and layout of output data files to facilitate data analysis. We also present tips on how to report the results from such numerical experiments effectively. Finally, we provide C# source code for many of these modules in an online appendix. We hope that the framework and guidance provided in this paper will promote further meaningful work in this important area of management accounting. Data Availability: The appendix and computer code that accompany this paper are available for downloading at https://github.com/vanand74/CostSystemSim. We request that anybody who downloads the code and amends it for their research paper purposes acknowledges their use of this code and references this paper in an acknowledgement section.

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Gumz, Michelle L. "Taking into account circadian rhythm when conducting experiments on animals." American Journal of Physiology-Renal Physiology 310, no. 6 (2016): F454—F455. http://dx.doi.org/10.1152/ajprenal.00549.2015.

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Do your kidneys know what time it is? Mounting evidence from human studies and animal models strongly suggests that the answer to this question is yes. The time has come to start reporting the time of day at which renal physiology studies are performed.

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Loewen, Peter John, Daniel Rubenson, and Leonard Wantchekon. "Help Me Help You: Conducting Field Experiments with Political Elites." ANNALS of the American Academy of Political and Social Science 628, no. 1 (2010): 165–75. http://dx.doi.org/10.1177/0002716209351522.

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Belser, Jessica A., Taronna R. Maines, Jacqueline M. Katz, and Terrence M. Tumpey. "Considerations regarding appropriate sample size for conducting ferret transmission experiments." Future Microbiology 8, no. 8 (2013): 961–65. http://dx.doi.org/10.2217/fmb.13.64.

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Abedi, Ali, Andrew Heard, and Tim Brecht. "Conducting Repeatable Experiments and Fair Comparisons using 802.11n MIMO Networks." ACM SIGOPS Operating Systems Review 49, no. 1 (2015): 41–50. http://dx.doi.org/10.1145/2723872.2723879.

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Piper, Alison I. "Conducting social science laboratory experiments on the world wide web." Library & Information Science Research 20, no. 1 (1998): 5–21. http://dx.doi.org/10.1016/s0740-8188(98)90003-2.

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Balasubramaniam, V. M., E. Y. Ting, C. M. Stewart, and J. A. Robbins. "Recommended laboratory practices for conducting high-pressure microbial inactivation experiments." Innovative Food Science & Emerging Technologies 5, no. 3 (2004): 299–306. http://dx.doi.org/10.1016/j.ifset.2004.04.001.

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Horton, John J., David G. Rand, and Richard J. Zeckhauser. "The online laboratory: conducting experiments in a real labor market." Experimental Economics 14, no. 3 (2011): 399–425. http://dx.doi.org/10.1007/s10683-011-9273-9.

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