An assessment of the autism neuroimaging literature for the prospects of re-executability

Background: The degree of reproducibility of the neuroimaging literature in psychiatric application areas has been called into question and the issues that relate to this reproducibility are extremely complex. Some of these complexities have to do with the underlying biology of the disorders that we study and others arise due to the technology we apply to the analysis of the data we collect. Ultimately, the observations we make get communicated to the rest of the community through publications in the scientific literature. Methods: We sought to perform a ‘re-executability survey’ to evaluate the recent neuroimaging literature with an eye toward seeing if the technical aspects of our publication practices are helping or hindering the overall quest for a more reproducible understanding of brain development and aging. The topic areas examined include availability of the data, the precision of the imaging method description and the reporting of the statistical analytic approach, and the availability of the complete results. We applied the survey to 50 publications in the autism neuroimaging literature that were published between September 16, 2017 to October 1, 2018. Results: The results of the survey indicate that for the literature examined, data that is not already part of a public repository is rarely available, software tools are usually named but versions and operating system are not, it is expected that reasonably skilled analysts could approximately perform the analyses described, and the complete results of the studies are rarely available. Conclusions: We have identified that there is ample room for improvement in research publication practices. We hope exposing these issues in the retrospective literature can provide guidance and motivation for improving this aspect of our reporting practices in the future

Engineering Students' Perceptions of and Attitudes Towards Cheating

Academic dishonesty has become a serious problem at institutions of higher learning. This is particularly true in engineering where, according to previous research, engineering undergraduates are among the most likely to cheat in college. To investigate this concern, the authors embarked on a research project whose goal was to develop a better understanding of what students and faculty perceive as cheating and to use this knowledge to help instructors and institutions increase the level of academic integrity among students. The primary instrument for this project was a seven‐page survey that was administered to 643 engineering and pre‐engineering undergraduates at eleven institutions, ranging from community colleges to large research universities. This manuscript provides an overview of the descriptive data from the PACES‐1 Survey organized around the following questions: what is student cheating and how often does it occur; why do students cheat; and what methods can be used to reduce or stop cheating?Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94862/1/j.2168-9830.2006.tb00891.x.pd

Rethinking Social Media

https://larc.cardozo.yu.edu/event-invitations-2019/1001/thumbnail.jp

Estimation of a Transformation Model with Truncation, Interval Observation and Time-Varying Covariates

Abrevaya (1999b) considered estimation of a transformation model in the presence of left-truncation. This paper observes that a cross-sectional version of the statistical model considered in Frederiksen, Honoré, and Hu (2007) is a generalization of the model considered by Abrevaya (1999b) and the generalized model can be estimated by a pairwise comparison version of one of the estimators in Frederiksen, Honoré, and Hu (2007). Specifically, our generalization will allow for discretized observations of the dependent variable and for piecewise constant time{varying explanatory variables