WHEN MISSING DATA ARE NOT MISSING: A NEW APPROACH TO EVALUATING SUPPLEMENTAL HOMICIDE REPORT IMPUTATION STRATEGIES*

The Supplemental Homicide Reports (SHR) are widely used in criminological research and inform a broad range of research topics and subsequent policy applications. A serious issue with the SHR is missing information about the offender and incident in many recorded homicides. Although it is convenient to discard cases with missing data before analysis, such discarding is not theoretically justified and can lead to incorrect substantive conclusions. Recently, several techniques for imputing missing SHR data have been proposed, but it is difficult to evaluate their effectiveness. This research presents a new approach to testing and evaluating SHR imputation techniques. Offender data that are missing in the SHR are often found in police records available for individual cities. We examine similarities and differences among cases with known offender characteristics in the SHR, cases with such information missing in the SHR but available in police records, and cases with such information missing in both sources. We then use these data sets to evaluate four different imputation techniques suggested in the literature (Fox, 2004; Messner, Deane, and Beaulieu, 2002; Pampel and Williams, 2000; Regoeczi and Riedel, 2003). We apply each imputation technique to the SHR, and for cases with information missing in the SHR but known in the police records, we see how well the imputed values correspond both with the individual known values and with the overall distributions in the police records. We discuss the outcome of our assessment of these strategies, and we outline important implications this assessment has for research using SHR data.     

Distinguishing Between Influences on Brazilian Legislative Behavior

Ideal point estimators hold the promise of identifying multiple dimensions of political disagreement as they are manifested in legislative voting. However, standard ideal point estimates do not distinguish between ideological motivations and voting inducements from parties, coalitions, or the executive. In this article we describe a general approach for hierarchically identifying an ideological dimension using an auxiliary source of data. In the case we consider, we use an anonymous survey of Brazilian legislators to identify party positions on a left‐right ideology dimension. We then use this data to distinguish ideological motivations from other determinants of roll‐call behavior for eight presidential‐legislative periods covering more than 20 years of Brazilian politics. We find that there exists an important nonideological government‐opposition dimension, with the entrance and exit of political parties from the governing coalition appearing as distinct shifts in ideal point on this second dimension. We conjecture that the Brazilian president's control over politically important resources is the source of this dimension of conflict, which has recently become far more important in explaining roll‐call voting than the ideological dimension.     

“I’ll stop procrastinating now!” Fostering specific processes of self-regulated learning to reduce academic procrastination

ABSTRACT

Academic procrastination is considered to be a result of self-regulation failure having detrimental effects on students’ well-being and academic performance. In the present study, we developed and evaluated a group training that aimed to reduce academic procrastination. We based the training on a cyclical process model of self-regulated learning, thus, focusing on improving deficient processes of self-regulated learning among academic procrastinators (e.g., time management, dealing with distractions). The training comprised five sessions and took place once a week for 90?min in groups of no more than 10 students. Overall, 106 students completed the training. We evaluated the training using a comprehensive control group design with repeated measures (three points of measurement); the control group was trained after the intervention group’s training. The results showed that our training was successful. The trained intervention group significantly reduced academic procrastination and improved specific processes of self-regulated learning (e.g., time management, concentration), whereas the untrained control group showed no change regarding these variables. After the control group had also been trained, the control group also showed the expected favorable changes. The students rated the training overall as good and found it recommendable for procrastinating friends. Hence, fostering self-regulatory processes in our intervention was a successful attempt to support students in reducing academic procrastination. The evaluation of the training encourages us to adapt the training for different groups of procrastinators.