# International Seminar on Selective Inference

A weekly online seminar on selective inference, multiple testing, and post-selection inference.

Gratefully inspired by the Online Causal Inference Seminar

## Mailing List

For announcements and Zoom invitations please subscribe to our mailing list.

## Upcoming Seminar Presentations

All seminars take place Thursdays at 8:30 am PT / 11:30 am ET / 4:30 pm London / 6:30 pm Tel Aviv. Past seminar presentations are posted here.

• Thursday, August 12, 2021 [Link to join]

• Speaker: Sanat K. Sarkar (Temple University)

• Title: Adjusting the Benjamini-Hochberg method for controlling the false discovery rate in knockoff-assisted variable selection

• Abstract: The knockoff-based multiple testing setup of Barber & Candès (2015) for variable selection in multiple regression where sample size is as large as the number of explanatory variables is considered. The Benjamini-Hochberg method based on ordinary least squares estimates of the regression coefficients is adjusted to the setup, transforming it to a valid p-value based FDR controlling method not relying on any specific correlation structure of the explanatory variables. Simulations and real data applications show that our proposed method that is agnostic to $\pi_0$, the proportion of unimportant explanatory variables, and a data-adaptive version of it that uses an estimate of $\pi_0$ are powerful competitors of the FDR controlling methods in Barber & Candès (2015).

• Discussant: Lucas Janson (Harvard University)

• Links: [Relevant papers: paper #1]

## Format

The seminars are held on Zoom and last 60 minutes:

• 45 minutes of presentation

• 15 minutes of discussion, led by an invited discussant

Moderators collect questions using the Q&A feature during the seminar.

## How to join

You can attend by clicking the link to join (there is no need to register in advance).

More instructions for attendees can be found here.

## Organizers

If you have feedback or suggestions or want to propose a speaker, please e-mail us at selectiveinferenceseminar@gmail.com.

## What is selective inference?

Broadly construed, selective inference means searching for interesting patterns in data, usually with inferential guarantees that account for the search process. It encompasses:

• Multiple testing: testing many hypotheses at once (and paying disproportionate attention to rejections)

• Post-selection inference: examining the data to decide what question to ask, or what model to use, then carrying out one or more appropriate inferences

• Adaptive / interactive inference: sequentially asking one question after another of the same data set, where each question is informed by the answers to preceding questions

• Cheating: cherry-picking, double dipping, data snooping, data dredging, p-hacking, HARKing, and other low-down dirty rotten tricks; basically any of the above, but done wrong!