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

Saline seep diagnosis, control and reclamation

Please contact the NWISRL if you have a copy of this publication

Saline seep diagnosis, control and reclamation

Please contact the NWISRL if you have a copy of this publication

Repercussion of anthropogenic landscape changes on pedodiversity and preservation of the pedological heritage

Over a period of time people have lived in and with their surrounding landscapes and for several thousand years transformed the soilscapes and the vegetation into cultural landscape types important for their economy and to meet their needs (Richter 2007, Ellis 2011, Hjelle 2012). The sustainable provision of goods and services depends critically on managing soils without damaging the natural soilscapes and the related natural resources. To support the transition towards sustainable development, science needs to understand how land-use change affects the environment and how this, in turn, feeds back into human livelihood strategies or infl uences the vulnerability of the environment (Rounsevell et al. 2012a). Interactions between decision-making, governance structures, production and consumption, technology, ecosystem services and global environmental change infl uence human activities at the local and regional scale, and are infl uenced by and feed back to the global scale, thereby shaping trajectories of human–environment interaction in land systems (Lambin and Meyfroidt 2011)