@article {Simula.SE.124,
	title = {A Systematic Review of Quasi-Experiments in Software Engineering},
	journal = {Information and Software Technology},
	volume = {51},
	number = {1},
	year = {2009},
	month = {January},
	pages = {71-82},
	author = {Vigdis By {Kampenes} and Dyb{\r a}, Tore and Jo Erskine {Hannay} and Sj{\o}berg, Dag Ingar Kondrup}
}
@inproceedings {Simula.SE.275,
	title = {Flexibility in Research Designs in Empirical Software Engineering},
	journal = {Evaluation and Assessment in Software Engineering (EASE 2008)},
	year = {2008},
	publisher = {BCS},
	type = {Conference},
	abstract = {Problem outline:A common way of classifying empirical research designs is in qualitative and quantitative designs. Typically, particular research methods (e.g., case studies, action research, experiments and surveys) are associated to one or the other of these designs. Studies in empirical software engineering (ESE) are often exploratory and often involve software developers and development organizations. As a consequence, it may be difficult to pre-plan all aspects of the studies, and to be successful, ESE studies must often be designed to handle upcoming changes during the conduct of the study. A problem with the above classification is that it does not cater for the flexibility in the design. Position: This paper suggests viewing research in ESE along the axis of flexible and fixed designs, which is both orthogonal to the axis of quantitative and qualitative designs, and independent of the particular research method. According to the traditional view of ESE, changes to the research design in the course of a study are typically regarded as threats to the validity of the study results. However, by viewing the study designs as flexible, practical challenges can be turned to useful information. The validity of the results of studies with flexible research designs can be established by applying techniques that are traditionally used for qualitative designs. This paper urges for increased recognition of flexible designs in ESE and discusses techniques for establishing the trustworthiness in flexible designs.},
	author = {Vigdis By {Kampenes} and Anda, Bente Cecilie Dahlum and Dyb{\r a}, Tore},
	editor = {Giuseppe Visaggio M {Turner}}
}
@phdthesis {Simula.SE.178,
	title = {Quality of Design, Analysis and Reporting of Software Engineering Experiments: a Systematic Review},
	year = {2007},
	school = {University of Oslo},
	type = {phd},
	abstract = {Background: Like any research discipline, software engineering research must be of a certain quality to be valuable. High quality research in software engineering ensures that knowledge is accumulated and helpful advice is given to the industry. One way of assessing research quality is to conduct systematic reviews of the published research literature. Objective: The purpose of this work was to assess the quality of published experiments in software engineering with respect to the validity of inference and the quality of reporting. More specifically, the aim was to investigate the level of statistical power, the analysis of effect size, the handling of selection bias in quasi-experiments, and the completeness and consistency of the reporting of information regarding subjects, experimental settings, design, analysis, and validity. Furthermore, the work aimed at providing suggestions for improvements, using the potential deficiencies detected as a basis. Method: The quality was assessed by conducting a systematic review of the 113 experiments published in nine major software engineering journals and three conference proceedings in the decade 1993-2002. Results: The review revealed that software engineering experiments were generally designed with unacceptably low power and that inadequate attention was paid to issues of statistical power. Effect sizes were sparsely reported and not interpreted with respect to their practical importance for the particular context. There seemed to be little awareness of the importance of controlling for selection bias in quasi-experiments. Moreover, the review revealed a need for more complete and standardized reporting of information, which is crucial for understanding software engineering experiments and judging their results. Implications: The consequence of low power is that the actual effects of software engineering technologies will not be detected to an acceptable extent. The lack of reporting of effect sizes and the improper interpretation of effect sizes result in ignorance of the practical importance, and thereby the relevance to industry, of experimental results. The lack of control for selection bias in quasi-experiments may make these experiments less credible than randomized experiments. This is an unsatisfactory situation, because quasi-experiments serve an important role in investigating cause-effect relationships in software engineering, for example, in industrial settings. Finally, the incomplete and unstandardized reporting makes it difficult for the reader to understand an experiment and judge its results. Conclusions: Insufficient quality was revealed in the reviewed experiments. This has implications for inferences drawn from the experiments and might in turn lead to the accumulation of erroneous information and the offering of misleading advice to the industry. Ways to improve this situation are suggested.},
	author = {Vigdis By {Kampenes}}
}
@article {Kampenes.2006.1,
	title = {A Systematic Review of Effect Size in Software Engineering Experiments},
	journal = {Information and Software Technology},
	volume = {49},
	number = {11-12},
	year = {2007},
	pages = {1073-1086},
	author = {Vigdis By {Kampenes} and Dyb{\r a}, Tore and Jo Erskine {Hannay} and Sj{\o}berg, Dag Ingar Kondrup}
}
@article {Li.2006.1,
	title = {An Empirical Study of Variations in COTS-Based Software Development Processes in Norwegian IT Industry},
	journal = {Empirical Software Engineering},
	volume = {11},
	number = {3},
	year = {2006},
	month = {September},
	pages = {433-461},
	author = {Li, Jingyue and Finn Olav {Bj{\o}rnson} and Conradi, Reidar and Vigdis By {Kampenes}}
}
@article {Dyba.2006.1,
	title = {A Systematic Review of Statistical Power in Software Engineering Experiments},
	journal = {Information and Software Technology},
	volume = {48},
	number = {8},
	year = {2006},
	month = {August},
	pages = {745-755},
	abstract = {Statistical power is an inherent part of empirical studies that employ significance testing and is essential for the planning of studies, for the interpretation of study results, and for the validity of study conclusions. This paper reports a quantitative assessment of the statistical power of empirical software engineering research based on the 103 papers on controlled experiments (of a total of 5453 papers) published in nine major software engineering journals and three conference proceedings in the decade 1993-2002. The results show that the statistical power of software engineering experiments falls substantially below accepted norms as well as the levels found in the related discipline of information systems research. Given this study{\textquoteright}s findings, additional attention must be directed to the adequacy of sample sizes and research designs to ensure acceptable levels of statistical power. Furthermore, the current reporting of significance tests should be enhanced by also reporting effect sizes and confidence intervals.},
	author = {Dyb{\r a}, Tore and Vigdis By {Kampenes} and Sj{\o}berg, Dag Ingar Kondrup}
}
@inproceedings {Kampenes.2005.1,
	title = {Effect Size in Empirical Software Engineering Experiments},
	journal = {Guidelines for Empirical Work in Software Engineering. 3rd International Workshop, WSESE2005, Oulu, Finland, June 13-16},
	year = {2005},
	month = {August},
	pages = {14-21},
	publisher = {A publication by Fraunhofer IESE},
	type = {Workshop},
	isbn = {iese-report no. 053.05/E},
	author = {Vigdis By {Kampenes}},
	editor = {Marcus Ciolkowski {Jedlitschka}}
}
@article {Li.2005.1,
	title = {An Empirical Study of Variations in COTS-Based Software Development Processes in Norwegian IT Industry},
	journal = {Empirical Software Engineering},
	year = {2005},
	author = {Li, Jingyue and Finn Olav {Bj{\o}rnson} and Conradi, Reidar and Vigdis By {Kampenes}}
}
@inproceedings {Conradi.2005.1,
	title = {Reflections on Conducting an International Survey of CBSE in ICT Industry},
	journal = {ISESE05 (Fourth International Symposium on Empirical Software Engineering)},
	year = {2005},
	pages = {214-223},
	publisher = {IEEE Computer Society},
	type = {1},
	address = {Noosa, Australia, November 17-18},
	author = {Conradi, Reidar and Li, Jingyue and Odd Petter {Slyngstad} and Vigdis By {Kampenes} and Bunse, Christian and Morisio, Maurizio and Torchiano, Marco}
}
@article {Sjoberg.2005.1,
	title = {A Survey of Controlled Experiments in Software Engineering},
	journal = {IEEE Transactions on Software Engineering},
	volume = {31},
	number = {9},
	year = {2005},
	month = {September},
	pages = {733-753},
	abstract = {The classical method for identifying cause-effect relationships is to conduct controlled experiments. This paper reports upon the present state of how controlled experiments in software engineering are conducted and the extent to which relevant information is reported. Among the 5,453 scientific articles published in 12 leading software engineering journals and conferences in the decade from 1993 to 2002, 103 articles (1.9 percent) reported controlled experiments in which individuals or teams performed one or more software engineering tasks. This survey quantitatively characterizes the topics of the experiments and their subjects (number of subjects, students versus professionals, recruitment, and rewards for participation), tasks (type of task, duration, and type and size of application) and environments (location, development tools). Furthermore, the survey reports on how internal and external validity is addressed and the extent to which experiments are replicated. The gathered data reflects the relevance of software engineering experiments to industrial practice and the scientific maturity of software engineering research.},
	author = {Sj{\o}berg, Dag Ingar Kondrup and Jo Erskine {Hannay} and Hansen, Ove and Vigdis By {Kampenes} and Karahasanovic, Amela and Liborg, Nils-Kristian and Anette C. {Rekdal}}
}
@article {Wright.2002.1,
	title = {Iodixanol in Paediatric Gastrointestinal Imageing: Safety and Efficacy Compariosn With Iodixanol},
	journal = {The British Journal of Radiology},
	year = {2002},
	author = {N. B. {Wright} and H. M. {Carty} and Sprigg, A. and Vigdis By {Kampenes} and Friis, M. and K. K. {Petersen} and Stake, G. and A. J. {Klaveness}}
}
@article {Rienmuller.2001.1,
	title = {Dimeric Versus Monomeric Contrast Agents in Vizualisation of Coronary Arteries},
	journal = {European Journal of Radiology},
	year = {2001},
	author = {Rienmuller, R. and Brekke, O. and Vigdis By {Kampenes}}
}
@article {Fischbach.1999.1,
	title = {Spiral CT Angiography of the Abdominal Aorta},
	journal = {Investigative Radiology},
	year = {1999},
	author = {Fischbach, Roman and Landwehr, Peter and Svaland, Marit and Pape, Heinz-Gerd and Brochhagen, Hans-Georg and Vigdis By {Kampenes} and Heindel, Walter and Lackner, Klaus}
}
@article {Skehan.1998.1,
	title = {A Comparison of a Non-Ionic Dimer, Iodixanol With a Non-Ionic Monomer, Iohexol in Low Dose Intravenous Urography},
	journal = {The British Journal of Radiology},
	year = {1998},
	author = {Skehan, S.J and Rasmussen, F. and Gibney, R.G and Lindequist, S. and Moller-Nielsen, S. and Svaland, M.G and Vigdis By {Kampenes} and Bjartveit, K. and Greaney, T. and Carlsen, Damgaard and Masterson, J.}
}
