Tim Ricker
@timricker.bsky.social
Associate Professor of Psychology at the University of South Dakota | PI of the Memory & Attention Laboratory | Fan of chess, cards, video games, & hiking.
Saturday (Nov.22) 6:00-7:30 PM
(V-136) When are Reward-Based Cues Most Effective
in Prioritizing Working Memories?
SRIYA RAVULA, University of South Dakota
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
(V-136) When are Reward-Based Cues Most Effective
in Prioritizing Working Memories?
SRIYA RAVULA, University of South Dakota
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
November 17, 2025 at 10:16 PM
Saturday (Nov.22) 6:00-7:30 PM
(V-136) When are Reward-Based Cues Most Effective
in Prioritizing Working Memories?
SRIYA RAVULA, University of South Dakota
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
(V-136) When are Reward-Based Cues Most Effective
in Prioritizing Working Memories?
SRIYA RAVULA, University of South Dakota
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
Saturday (Nov.22), 6:00-7:30 PM
(V-131) Stimulus Positioning and Local/Global Effects
on Working Memory Creation
DILLON A. QUINONES, University of South Dakota
ALLISON N. MARINO, Montclair State University
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
(V-131) Stimulus Positioning and Local/Global Effects
on Working Memory Creation
DILLON A. QUINONES, University of South Dakota
ALLISON N. MARINO, Montclair State University
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
November 17, 2025 at 10:15 PM
Saturday (Nov.22), 6:00-7:30 PM
(V-131) Stimulus Positioning and Local/Global Effects
on Working Memory Creation
DILLON A. QUINONES, University of South Dakota
ALLISON N. MARINO, Montclair State University
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
(V-131) Stimulus Positioning and Local/Global Effects
on Working Memory Creation
DILLON A. QUINONES, University of South Dakota
ALLISON N. MARINO, Montclair State University
JOSHUA SANDRY, Montclair State University
TIMOTHY J. RICKER, University of South Dakota
Reposted by Tim Ricker
I’m also on the job market! If you’re working on predictive processing, event cognition, or computational modeling — or know of exciting postdoc opportunities —please DM!
📄 Paper: psycnet.apa.org/record/2026-...
🙏 With: Matt Bezdek, Tan Nguyen, Chris Hall and @jzacks.bsky.social
📄 Paper: psycnet.apa.org/record/2026-...
🙏 With: Matt Bezdek, Tan Nguyen, Chris Hall and @jzacks.bsky.social
APA PsycNet
psycnet.apa.org
November 12, 2025 at 9:31 PM
I’m also on the job market! If you’re working on predictive processing, event cognition, or computational modeling — or know of exciting postdoc opportunities —please DM!
📄 Paper: psycnet.apa.org/record/2026-...
🙏 With: Matt Bezdek, Tan Nguyen, Chris Hall and @jzacks.bsky.social
📄 Paper: psycnet.apa.org/record/2026-...
🙏 With: Matt Bezdek, Tan Nguyen, Chris Hall and @jzacks.bsky.social
Reposted by Tim Ricker
Last year a bunch of us wrote about the issue of incentives and possible alternatives. I’m not in love with any of the options we reviewed but I *am* happy we were able to highlight major aspects of the problem in a highly visible space www.pnas.org/doi/10.1073/...
The misalignment of incentives in academic publishing and implications for journal reform | PNAS
For most researchers, academic publishing serves two goals that are often misaligned—knowledge
dissemination and establishing scientific credential...
www.pnas.org
November 12, 2025 at 9:32 AM
Last year a bunch of us wrote about the issue of incentives and possible alternatives. I’m not in love with any of the options we reviewed but I *am* happy we were able to highlight major aspects of the problem in a highly visible space www.pnas.org/doi/10.1073/...
Reposted by Tim Ricker
5% is quite a lot if you think about it. Huge N gives you the luxury to reduce alpha by a lot and still keep very high power. E.g., alpha = 0.5% (0.005) would give you 98.8% power for the same effect (in a t-test). The best balance depends on the cost of each error type, see tinyurl.com/yut35b3u >
Justify Your Alpha by Minimizing or Balancing Error Rates
A preprint ("Justify Your Alpha: A Primer on Two Practical Approaches") that extends the ideas in this blog post is available at: https://ps...
tinyurl.com
October 31, 2025 at 8:13 AM
5% is quite a lot if you think about it. Huge N gives you the luxury to reduce alpha by a lot and still keep very high power. E.g., alpha = 0.5% (0.005) would give you 98.8% power for the same effect (in a t-test). The best balance depends on the cost of each error type, see tinyurl.com/yut35b3u >