Welcome to the Mental Health Statistics Section!

The Mental Health Statistics Section aims to provide a forum for communication among statisticians and mental health researchers, facilitate development and use of sound statistical methodologies in mental health research, and promote career opportunities for statisticians in mental health research


  • 2023 Student Paper Award Competition Winners

    Congratulations to the winners of the 2023 Mental Health Statistics Section Student Paper Award competition:

    Richard Watson, NC State University
    On Heterogeneous Treatment Effect Estimation in Causal Graphs

    Daiqi Gao, University of North Carolina at Chapel Hill
    Fusing Individualized Treatment Rules Using Auxiliary Outcomes

    Jizhou Kang, University of California, Santa Cruz
    Flexible Bayesian Modeling for Longitudinal Binary Responses

    Awards will be presented to the winner at the MHSS Mixer at JSM 2023.
  • 2023 Student Paper Award Competition

    The Mental Health Statistics Section (MHSS) of the American Statistical Association is inviting submissions to our student paper competition for the 2023 Joint Statistical Meetings (JSM). Papers entered in this student paper competition should involve a methodological innovation or a novel application of statistical methods to a mental health issue. Up to three cash prizes of $1,000 each will be awarded to the highest rated paper(s) to cover JSM 2023 expenses. 


    Current undergraduate or graduate students at any level, as well as those who graduated in 2022 and wish to submit research they conducted as students, are eligible to participate. There is no requirement for participants to be a member of ASA or the MHSS.

    The MHSS strongly encourages submissions from diverse applicants including those from underrepresented racial and ethnic groups, individuals with disabilities, individuals from disadvantaged backgrounds, and women in the biomedical workforce.

    Application Materials: 

    The deadline for application is 5 PM EST on December 15, 2022.

    Applications to the Mental Health Section student paper award competition should include:

    1. A cover letter including name, current affiliation and status including actual or intended date of graduation, and contact information (address, telephone, email) of the applicant.
    2. A letter from the adviser certifying student status (or completion of degree within the past year).
    3. The paper submitted for the competition, including an abstract of up to 1200 characters.

    Applications must be submitted by email as one combined document (PDF files preferred).  You should submit the single document with the three application parts in the following order: (1) cover letter, (2) adviser letter, and (3) paper.


    To apply, please send the application materials to Chong Wu (cwu18@mdanderson.org) with “MHSS student paper award application” as the title.

    Selection Process and Expectations for Award Winners:

    The award committee will review all papers, and winners will be notified by January 15, 2023. The winner(s) will be required to present their papers at JSM 2023. The winner(s) must submit an abstract on the topic of their winning paper and register for JSM 2023 before the deadline through the official JSM abstract submission system. The award(s) will be announced at the Mental Health Statistics Section Mixer at JSM 2023, and it is hoped that winners will be in attendance to connect with the Mental Health Statistics Section members.

    Please contact Chong Wu (cwu18@mdanderson.org) for more information.

MHSS Webinars

The MHSS is pleased to continually offer a number of webinars.

2022 Webinars

Date and Time: Sept. 29th at 12:00-2:00 PM EST
Speaker: Dr. Stephen Bates (UC Berkeley)
Title: Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

Date and Time: May 24th at 12:00-2:00 PM EST
Speaker: Dr. Bengt Muthen (UC Los Angeles)
Title: Recent Advances in Modeling Short and Long Longitudinal Data

Date and Time: March 15th at 12:00-2:00 PM EST
Speaker: Dr. Bin Yu (UC Berkeley)
Title: Interpreting Deep Neural Networks towards Trustworthiness

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