Multiple Imputation Using Gaussian Copulas

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use method for generating multiple imputations using a Gaussian copula. The Gaussian copula for multiple imputation (Hoff, 2007) allows scholars to attain estimation results that have good coverage and small bias. The use of copulas to model the dependence among variables will enable researchers to construct valid joint distributions of the data, even without knowledge of the actual underlying marginal distributions. Multiple imputations are then generated by drawing observations from the resulting posterior joint distribution and replacing the missing values. Using simulated and observational data from published social science research, we compare imputation via Gaussian copulas with two other widely used imputation methods: MICE and Amelia II. Our results suggest that the Gaussian copula approach has a slightly smaller bias, higher coverage rates, and narrower confidence intervals compared to the other methods. This is especially true when the variables with missing data are not normally distributed. These results, combined with theoretical guarantees and ease-of-use suggest that the approach examined provides an attractive alternative for applied researchers undertaking multiple imputations

Influence of racial stereotypes on investigative decision-making in criminal investigations: A qualitative comparative analysis

open access articleRecent research suggests that the police are aware of the general trends in street crime and, from such awareness, tend to form impressions of the likelihood that persons belonging to various racial groups will commit certain types of crimes (e.g. drugs-related crimes). Such perceptions may lead to the police undertaking racial profiling which has the effect of creating a cycle of profiling of suspected offenders, regardless of the accuracy of these perceptions. As such, these cycles of profiling are results of negative stereotypes. The present study involved semi-structured interviews with serving police officers in England, during which the same scenario was put to each of them in turn, only differing in the name of the suspect. We employed an innovative methodological technique, crisp-set qualitative comparative analysis (csQCA), which enabled us to identify the causal relationship between variables (i.e. racial stereotypes) and associated outcomes of investigations. As a result, we found two pathways to police officers’ investigative decision-making. Both pathways indicated that any negative stereotypes based on suspect’s group membership may well indeed influence the officers’ investigative decision-making, quite possibly affecting outcomes of criminal investigations. Implications for investigative practice are discussed

Amino acid composition predicts prion activity

Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained; we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136

Effects of Non-Driving Related Tasks During Self-Driving Mode

Perception reaction time and mental workload have proven to be crucial in manual driving. Moreover, in highly automated cars, where most of the research is focusing on Level 4 Autonomous driving, take-over performance is also a key factor when taking road safety into account. This study aims to investigate how the immersion in non-driving related tasks affects the take-over performance of drivers in given scenarios. The paper also highlights the use of virtual simulators to gather efficient data that can be crucial in easing the transition between manual and autonomous driving scenarios. The use of Computer Aided Simulations is of absolute importance in this day and age since the automotive industry is rapidly moving towards Autonomous technology. An experiment comprising of 40 subjects was performed to examine the reaction times of driver and the influence of other variables in the success of take-over performance in highly automated driving under different circumstances within a highway virtual environment. The results reflect the relationship between reaction times under different scenarios that the drivers might face under the circumstances stated above as well as the importance of variables such as velocity in the success on regaining car control after automated driving. The implications of the results acquired are important for understanding the criteria needed for designing Human Machine Interfaces specifically aimed towards automated driving conditions. Understanding the need to keep drivers in the loop during automation, whilst allowing drivers to safely engage in other non-driving related tasks is an important research area which can be aided by the proposed study

Amino acid composition predicts prion activity

Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained; we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136

The Challenges of Wastewater Irrigation in Developing Countries

The volume of wastewater generated by domestic, industrial, and commercial sources has increased with population, urbanization, improved living conditions, and economic development. The productive use of wastewater has also increased, as millions of small-scale farmers in urban and peri-urban areas of developing countries depend on wastewater or wastewater-polluted water sources to irrigate high-value edible crops for urban markets, often as they have no alternative sources of irrigation water. Undesirable constituents in wastewater can harm human health and the environment. Hence, wastewater irrigation is an issue of concern to public agencies responsible for maintaining public health and environmental quality. For diverse reasons, many developing countries are still unable to implement comprehensive wastewater treatment programs. Therefore in the near term, risk management and interim solutions are needed to prevent adverse impacts from wastewater irrigation. A combination of source control and farm-level and post-harvest measures can be used to protect farm workers and consumers. The WHO guidelines revised in 2006 for wastewater use suggest measures beyond the traditional recommendations of producing only industrial or nonedible crops, as in many situations it is impossible to enforce a change in the current cash crop pattern, or provide alternative vegetable supply to urban markets. There are several opportunities for improving wastewater management via improved policies, institutional dialogues, and financial mechanisms, which would reduce the risks in agriculture. Effluent standards combined with incentives or enforcement can motivate improvements in water management by household and industrial sectors discharging wastewater from point sources. Segregation of chemical pollutants from urban waste-water facilitates treatment and reduces risk. Strengthening institutional capacity and establishing links between water delivery and sanitation sectors through interinstitutional coordination leads to more efficient management of wastewater and risk reduction

The Challenges of Wastewater Irrigation in Developing Countries

The volume of wastewater generated by domestic, industrial, and commercial sources has increased with population, urbanization, improved living conditions, and economic development. The productive use of wastewater has also increased, as millions of small-scale farmers in urban and peri-urban areas of developing countries depend on wastewater or wastewater-polluted water sources to irrigate high-value edible crops for urban markets, often as they have no alternative sources of irrigation water. Undesirable constituents in wastewater can harm human health and the environment. Hence, wastewater irrigation is an issue of concern to public agencies responsible for maintaining public health and environmental quality. For diverse reasons, many developing countries are still unable to implement comprehensive wastewater treatment programs. Therefore in the near term, risk management and interim solutions are needed to prevent adverse impacts from wastewater irrigation. A combination of source control and farm-level and post-harvest measures can be used to protect farm workers and consumers. The WHO guidelines revised in 2006 for wastewater use suggest measures beyond the traditional recommendations of producing only industrial or nonedible crops, as in many situations it is impossible to enforce a change in the current cash crop pattern, or provide alternative vegetable supply to urban markets. There are several opportunities for improving wastewater management via improved policies, institutional dialogues, and financial mechanisms, which would reduce the risks in agriculture. Effluent standards combined with incentives or enforcement can motivate improvements in water management by household and industrial sectors discharging wastewater from point sources. Segregation of chemical pollutants from urban waste-water facilitates treatment and reduces risk. Strengthening institutional capacity and establishing links between water delivery and sanitation sectors through interinstitutional coordination leads to more efficient management of wastewater and risk reduction

The Challenges of Wastewater Irrigation in Developing Countries

The volume of wastewater generated by domestic, industrial, and commercial sources has increased with population, urbanization, improved living conditions, and economic development. The productive use of wastewater has also increased, as millions of small-scale farmers in urban and peri-urban areas of developing countries depend on wastewater or wastewater-polluted water sources to irrigate high-value edible crops for urban markets, often as they have no alternative sources of irrigation water. Undesirable constituents in wastewater can harm human health and the environment. Hence, wastewater irrigation is an issue of concern to public agencies responsible for maintaining public health and environmental quality. For diverse reasons, many developing countries are still unable to implement comprehensive wastewater treatment programs. Therefore in the near term, risk management and interim solutions are needed to prevent adverse impacts from wastewater irrigation. A combination of source control and farm-level and post-harvest measures can be used to protect farm workers and consumers. The WHO guidelines revised in 2006 for wastewater use suggest measures beyond the traditional recommendations of producing only industrial or nonedible crops, as in many situations it is impossible to enforce a change in the current cash crop pattern, or provide alternative vegetable supply to urban markets. There are several opportunities for improving wastewater management via improved policies, institutional dialogues, and financial mechanisms, which would reduce the risks in agriculture. Effluent standards combined with incentives or enforcement can motivate improvements in water management by household and industrial sectors discharging wastewater from point sources. Segregation of chemical pollutants from urban waste-water facilitates treatment and reduces risk. Strengthening institutional capacity and establishing links between water delivery and sanitation sectors through interinstitutional coordination leads to more efficient management of wastewater and risk reduction