TSHS Portal Submission - DEI datasets - $500 Stipend Application

JavaScript isn't enabled in your browser, so this file can't be opened. Enable and reload.

The American Statistical Association (ASA) Section on Teaching of Statistics in the Health Sciences (TSHS) Resources Portal (Portal) Editorial Board is pleased to announce two (2) $500 stipend opportunities in 2023-2024 for the submission of teaching datasets with a clear focus on diversity, equity and inclusion (DEI).

This is an opportunity for teachers and researchers interested in DEI to become actively engaged. In addition, since all Portal datasets undergo peer review, dataset posts to the TSHS Resources Portal can be listed a publication on the submitters’ CVs.

The successful elimination of racial and cultural inequities in public health practice and research on human health will require recognizing and addressing the myriad and complex factors supporting those inequities. These include, but are not limited to: historical and present-day structural racism (including in social determinants of health), algorithmic unfairness, biases in common tests (e.g, the eGFR), racial bias on our parts (known or unknown), implicit bias in our legal and professional infrastructures, and failure to appreciate that race is a social construct that is distinct from ancestry. As teachers of statistics in the health sciences, and as public health professionals ourselves, we are well positioned to introduce our students to DEI through the lens of scientific inquiry and statistical literacy. The availability of teaching datasets with a focus on DEI would be an invaluable resource, as they offer students “hands on” training in exploring the effects of racism on health using real data, and in ensuring DEI in study design, data analysis, and reporting.

All datasets posted to the TSHS Resources Portal (https://www.causeweb.org/tshs/) have an associated published citation in the health sciences. In addition, all are peer reviewed and include essential companion materials needed for teaching: abstract, introduction, and data dictionary. Downloads are available in any of six formats: Excel, R, SAS, Stata, SPSS and Minitab.

Applicants must provide the associated published citation and have obtained permission to share the corresponding dataset, after deidentification, on the Portal. Rich datasets, those for which multiple types of analyses can be done, will be given priority. For more information about the process of contributing a dataset, please see https://www.causeweb.org/tshs/contributors/.

To apply, please complete the form below. Students are welcome to apply but must have identified a faculty mentor who has access to an appropriate dataset and is willing to commit to working with the student on this. Applications will be considered on a rolling basis by The TSHS Resources Portal Executive Committee.

Email *

Submitter Name *

Submitter Role *

Faculty

Student

Other:

If submitter is not faculty, please submit the faculty mentor's name and email below

Link to journal publication or DOI *

Data sharing permission *

I have obtained permission to share the described dataset (after de-identification) on the TSHS Portal

I have not yet, but will obtain permission (before receiving funding) to share the described dataset (after de-identification) on the TSHS Portal

Please give a brief description of the intended dataset. Include sample size and types of variables included. If the data covers only a subset of that presented in the matching publication, please explain what would be included. *

Please describe how this dataset focuses on Diversity, Equity, and Inclusion (DEI) *

Please list the primary statistical techniques that could be used when analyzing these data (e.g., survival analysis, linear regression, etc.) *

Please indicate which of the following components would be necessary for the dataset submission (i.e., the scope of work for the student). For further instructions on what is required for dataset submission, please see https://www.causeweb.org/tshs/contributors/. *

data cleaning

data de-identification

data dictionary generation

creation of different data file types (SAS, R, Stata, *.csv, etc.)

writing dataset introduction

Other:

Required

Who will be responsible for making any necessary revisions after the peer-review process *

Faculty member/advisor

Student

What is your target date for completing a version of the submission materials for review (e.g., September 2023)? *

Send me a copy of my responses.