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1. On the Phase Transition of Wilk’s Phenomenon

   https://doi.org/10.1093/biomet/asaa078  

   He, Yinqiu; Meng, Bo; Zeng, Zhenghao; Xu, Gongjun (September 2020, Biometrika)

   null (Ed.)

   Abstract Wilk’s theorem, which offers universal chi-squared approximations for likelihood ratio tests, is widely used in many scientific hypothesis testing problems. For modern datasets with increasing dimension, researchers have found that the conventional Wilk’s phenomenon of the likelihood ratio test statistic often fails. Although new approximations have been proposed in high dimensional settings, there still lacks a clear statistical guideline regarding how to choose between the conventional and newly proposed approximations, especially for moderate-dimensional data. To address this issue, we develop the necessary and sufficient phase transition conditions for Wilk’s phenomenon under popular tests on multivariate mean and covariance structures. Moreover, we provide an in-depth analysis of the accuracy of chi-squared approximations by deriving their asymptotic biases. These results may provide helpful insights into the use of chi-squared approximations in scientific practices. 

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2. Breaking Barriers with Bread: Using the Sourdough Starter Microbiome to Teach High-Throughput Sequencing Techniques

   https://doi.org/10.1128/jmbe.00306-21  

   Holt, Benjamin H.; Buchan, Alison; DeBruyn, Jennifer M.; Goodrich-Blair, Heidi; McPherson, Elizabeth; Brown, Veronica A. (August 2022, Journal of Microbiology & Biology Education)

   Westenberg, Dave J. (Ed.)

   ABSTRACT Widespread usage of high-throughput sequencing (HTS) in the LIFE SCIENCES has produced a demand for undergraduate and graduate institutions to offer classes exposing students to all aspects of HTS (sample acquisition, laboratory work, sequencing technologies, bioinformatics, and statistical analyses). Despite the increase in demand, many challenges exist for these types of classes. We advocate for the usage of the sourdough starter microbiome for implementing meta-amplicon sequencing. The relatively small community, dominated by a few taxa, enables potential contaminants to be easily identified, while between-sample differences can be quickly statistically assessed. Finally, bioinformatic pipelines and statistical analyses can be carried out on personal student laptops or in a teaching computer lab. In two semesters adopting this system, 12 of 14 students were able to effectively capture the sourdough starter microbiome, using the instructor’s paired sample as reference. 

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3. The Price Does Not Appear the Same for Everyone: Racial Differences in Students' Perceptions of the Mathematics Graduate School Application Process

   McEldowney, T.; Townsend, E.; Maldonado, D.; Michaluk, L.; Deshler, J. (February 2024, Proceedings of the Annual Conference on Research in Undergraduate Mathematics Education)

   Lack of racial diversity has been an ongoing issue in higher education. Recently, the Theory of Racialized Organizations has been used to help explain why, despite many calls for diversity, the demographics of higher education have not changed. Considering this framework, we seek to understand what aspects of the graduate school application process are viewed as barriers by minoritized students for applying. As part of a larger study of undergraduate student knowledge of the graduate school application process, we analyze 515 responses from undergraduate math majors using Mann-Whitney U tests to identify differences in what participants view as a barrier to apply to graduate school by race/ethnicity. We discuss two main results and recommend changes to graduate programs wishing to recruit more minoritized students. 

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4. Centering Diversity, Equity, and Inclusion in Graduate Admissions

   https://doi.org/10.59390/OETW7461  

   Tan, Taralyn; Tomaszycki, Michelle; Martinez_Acosta, Veronica; Juavinett, Ashley (August 2024, Journal of Undergraduate Neuroscience Education)

   Many undergraduate neuroscience trainees aspire to earn a PhD. In recent years the number, demographics, and previous experiences of PhD applicants in neuroscience has changed. This has necessitated both a reconsideration of admissions processes to ensure equity for an increasingly diverse applicant pool as well as renewed efforts to expand access to the training and research experiences required for admission to graduate programs. Here, we describe both facets of graduate school admissions by demystifying the process and providing faculty with tools and resources to help undergraduate students successfully navigate it. We discuss admissions requirements and processes at two graduate institutions, highlighting holistic approaches to evaluating students, the ever-increasing research experience expectations, and the decreasing reliance on the GRE. With a particular focus on improving equity, diversity, inclusion and belonging, we discuss resources for applying to graduate school that are available for students from underrepresented populations, including summer institutes and fellowship programs and intentional relationships with minority serving institutions (MSIs) to foster bi-directional engagement between undergraduate programs at MSIs and graduate institutions. With diverse perspectives as faculty involved in undergraduate education, graduate programs, and post-baccalaureate training programs, we provide recommendations and resources for how to help all trainees — especially those from populations underrepresented in the STEM workforce — succeed in the current graduate education admissions landscape. 

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5. A latent class analysis approach to the identification of doctoral students at risk of attrition

   https://doi.org/10.1371/journal.pone.0280325  

   Stevens, Samantha M.; Ruberton, Peter M.; Smyth, Joshua M.; Cohen, Geoffrey L.; Purdie Greenaway, Valerie; Cook, Jonathan E. (January 2023, PLOS ONE)

   Benetreau, Yann (Ed.)

   To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat , Nonchalant , Engaged/Worried , and Highest Threat . These classes were associated with characteristics measured at the beginning of students’ first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes. 

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