Best practices for addressing missing data through multiple imputation

A common challenge in developmental research is the amount of incomplete and missing data that occurs from respondents failing to complete tasks or questionnaires, as well as from disengaging from the study (i.e., attrition). This missingness can lead to biases in parameter estimates and, hence, in the interpretation of findings. These biases can be addressed through statistical techniques that adjust for missing data, such as multiple imputation. Although multiple imputation is highly effective, it has not been widely adopted by developmental scientists given barriers such as lack of training or misconceptions about imputation methods. Utilizing default methods within statistical software programs like listwise deletion is common but may introduce additional bias. This manuscript is intended to provide practical guidelines for developmental researchers to follow when examining their data for missingness, making decisions about how to handle that missingness and reporting the extent of missing data biases and specific multiple imputation procedures in publications

A Picture of the Research Field of Doctoral Education from the Students’ Perspectives : Studies Using Questionnaires and Scales

Peer reviewe

diversification as part of a csa strategy the cases of zambia and malawi

Climate variability, associated with farm-income variability, is recognized as one of the main drivers of livelihood diversification strategies in developing countries. In this chapter, we present a synthesis of two comprehensive studies from Zambia and Malawi on the drivers of diversification and its impacts on selected welfare outcomes with a specific attention to climatic variables and institutions. We use geo-referenced farm-household-level data merged with data on historical rainfall and temperature as well as with administrative data on relevant institutions. The two case studies demonstrate that diversification is clearly an adaptation response, as long term trends in climatic shocks have a significant effect on livelihood diversification, albeit with different implications. Whereas the long term variation in growing period rainfall is associated with increased crop, labour and income diversification in Malawi, it is only associated with increased livestock diversification in Zambia. With regard to institutions, we find that access to extension agents positively and significantly correlates with crop diversification in both countries, underlining the role of extension in promoting more resilient farming systems in rural Zambia and Malawi. Fertilizer subsidies are among the most important agricultural policies in both countries, where they significantly affect incentives for income diversification – though in opposing ways – providing important policy implications. The two case studies document distinct ways in which incentives for livelihood diversification (measured along different dimensions) are shaped by increased variability in rainfall and rural institutions. The results also demonstrate that diversification can be an effective adaptation response and the risk-return trade-offs are not as pronounced as might be expected

CloudBank: Managed Services to Simplify Cloud Access for Computer Science Research and Education

CloudBank is a cloud access entity founded to enable the computer science research and education communities to harness the profound computational potential of public clouds. By delivering a set of managed services designed to alleviate common points of friction associated with cloud adoption, Cloudbank serves as an integrated service provider to the research and education community these services include front-line help desk support, cloud solution consulting, training, account management, cost monitoring and optimization support, and automated billing. CloudBank has a multi-cloud pay-per-use billing model and aims to serve the spectrum of cloud users from novice to advanced