Worse Than Spam: Issues In Sampling Software Developers

Background: Reaching out to professional software developers is a crucial part of empirical software engineering research. One important method to investigate the state of practice is survey research. As drawing a random sample of professional software developers for a survey is rarely possible, researchers rely on various sampling strategies. Objective: In this paper, we report on our experience with different sampling strategies we employed, highlight ethical issues, and motivate the need to maintain a collection of key demographics about software developers to ease the assessment of the external validity of studies. Method: Our report is based on data from two studies we conducted in the past. Results: Contacting developers over public media proved to be the most effective and efficient sampling strategy. However, we not only describe the perspective of researchers who are interested in reaching goals like a large number of participants or a high response rate, but we also shed light onto ethical implications of different sampling strategies. We present one specific ethical guideline and point to debates in other research communities to start a discussion in the software engineering research community about which sampling strategies should be considered ethical.Comment: 6 pages, 2 figures, Proceedings of the 2016 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2016), ACM, 201

Efficiency of propensity score adjustment and calibration on the estimation from non-probabilistic online surveys

Peer Reviewe

How to Balance Privacy and Money through Pricing Mechanism in Personal Data Market

A personal data market is a platform including three participants: data owners (individuals), data buyers and market maker. Data owners who provide personal data are compensated according to their privacy loss. Data buyers can submit a query and pay for the result according to their desired accuracy. Market maker coordinates between data owner and buyer. This framework has been previously studied based on differential privacy. However, the previous study assumes data owners can accept any level of privacy loss and data buyers can conduct the transaction without regard to the financial budget. In this paper, we propose a practical personal data trading framework that is able to strike a balance between money and privacy. In order to gain insights on user preferences, we first conducted an online survey on human attitude to- ward privacy and interest in personal data trading. Second, we identify the 5 key principles of personal data market, which is important for designing a reasonable trading frame- work and pricing mechanism. Third, we propose a reason- able trading framework for personal data which provides an overview of how the data is traded. Fourth, we propose a balanced pricing mechanism which computes the query price for data buyers and compensation for data owners (whose data are utilized) as a function of their privacy loss. The main goal is to ensure a fair trading for both parties. Finally, we will conduct an experiment to evaluate the output of our proposed pricing mechanism in comparison with other previously proposed mechanism

An Exploratory Study of Patient Falls

Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body