22 papers · ranked by Valyu relevance
Dinis Gökaydin, Peter Brugger, Tobias Loetscher
Small and large numbers are typically associated with the left and right side of space, respectively. We conducted an online version of the classical Spatial-Numerical Association of Response Codes (SNARC) paradigm in 604 subjects in order to analyse how previous trials and responses affect SNARC. Our results point to…
Arthur Prat-Carrabin, Florent Meyniel, Rava Azeredo da Silveira
An abundant literature reports on ‘sequential effects’ observed when humans make predictions on the basis of stochastic sequences of stimuli. Such sequential effects represent departures from an optimal, Bayesian process. A prominent explanation posits that humans are adapted to changing environments, and erroneously…
Arthur Prat-Carrabin, Florent Meyniel, Rava Azeredo da Silveira, Hang Zhang + 1 more
An abundant literature reports on ‘sequential effects’ observed when humans make predictions on the basis of stochastic sequences of stimuli. Such sequential effects represent departures from an optimal, Bayesian process. A prominent explanation posits that humans are adapted to changing environments, and erroneously…
Jianrui Huang, Xianyou He, Xiaojin Ma, Yian Ren + 5 more
'Xin Zeng' 'Han Li' 'Yiheng Chen' 'Cosimo Urgesi'] When people make decisions about sequentially presented items in psychophysical experiments, their decisions are always biased by their preceding decisions and the preceding items, either by assimilation (shift towards the decision or item) or contrast (shift away from…
Seah Chang, Chai-Youn Kim, Yang Seok Cho, Linda Chao
An important factor affecting preference formation is the context in which that preference decision takes place. The current research examined whether one’s preference formed for a previously presented stimulus influences the processing of a subsequent preference decision, henceforth referred to as the preference…
Haiyan Zhao, Björn Andersson, Boliang Guo, Tao Xin
Writing assessments are an indispensable part of most language competency tests. In our research, we used cross-classified models to study rater effects in the real essay rating process of a large-scale, high-stakes educational examination administered in China in 2011. Generally, four cross-classified models are…
Noam Tal-Perry, Shlomit Yuval-Greenberg
When faced with unfamiliar circumstances, we often turn to our past experiences with similar situations to shape our expectations. This results in the well-established sequential effect, in which previous trials influence the expectations of the current trial. Studies have revealed that, in addition to the classical…
Jiao Wu, Halid Oğuz Serçe, Zhuanghua Shi
Serial dependence - the bias from recent experience on present response - is often linked to shared memory representations. Yet, it remains unclear whether this bias across tasks when stimulus features are shared but response modes differ. To test this, we interleaved temporal reproduction and bisection tasks using a…
Li Yin, Xiaoqin Wang
Suppose that a sequence of treatments are assigned to influence an outcome of interest that occurs after the last treatment. Between treatments there exist timedependent covariates that may be posttreatment variables of the earlier treatments and confounders of the subsequent treatments. In this article, we develop a…
Rina Friedberg, R. G. Mudd, Patrick R. Johnstone, Melissa Pothen + 3 more
Sequential treatment assignments in online experiments lead to complex dependency structures, often rendering identification, estimation and inference over treatments a challenge [[Kohavi et al., 2012]]. Treatments in one session (e.g., a user logging on) can have an effect that persists into subsequent sessions…
Donald Laming
Jesteadt et al. discovered a remarkable pattern of autocorrelation in log estimates of loudness. Responses to repeated stimuli correlated to about +0.7, but that correlation was much reduced (0.1) following large differences between successive stimuli. The experiment reported here demonstrates the same pattern in…
Nils Myszkowski, Martin Storme
Measurement models traditionally make the assumption that item responses are independent from one another, conditional upon the common factor. They typically explore for violations of this assumption using various methods, but rarely do they account for the possibility that an item predicts the next. Extending the…
Yingrong Wang, Anpeng Wu, Baohong Li, Ziyang Xiao + 3 more
'Qing Han' 'Kun Kuang'] This paper studies the cumulative causal effects of sequential treatments in the presence of unmeasured confounders. It is a critical issue in sequential decision-making scenarios where treatment decisions and outcomes dynamically evolve over time. Advanced causal methods apply transformer as a…
Shuai Chen, Tianhe Wang, Yan Bao
Recent experiences bias the perception of following stimuli, as has been verified in various kinds of experiments in visual perception. This phenomenon, known as serial dependence, may reflect mechanisms to maintain perceptual stability. In the current study, we examined several key properties of serial dependence in…
Iavor Bojinov, Neil Shephard
We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of a broad class of these estimands and exact randomization based p-values for testing causal effects, without imposing stringent assumptions. We…
Justin Ho, Jonathan Min
Experimental designs are fundamental for estimating causal effects. In some fields, within-subjects designs, which expose participants to both control and treatment at different time periods, are used to address practical and logistical concerns. Counterbalancing, a common technique in within-subjects designs, aims to…
Philip Marx, Elie Tamer, Xun Tang
Models Authors: ['Philip Marx' 'Elie Tamer' 'Xun Tang'] We study the identification and estimation of heterogeneous, intertemporal treatment effects (TE) when potential outcomes depend on past treatments. First, applying a dynamic panel data model to observed outcomes, we show that instrumentbased GMM estimators, such…
Konrad Neumann, Ulrike Grittner, Sophie K. Piper, Andre Rex + 8 more
'Oscar Florez-Vargas' 'George Karystianis' 'Alice Schneider' 'Ian Wellwood' 'Bob Siegerink' 'John P. A. Ioannidis' 'Jonathan Kimmelman' 'Ulrich Dirnagl'] Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost…
John P. Veillette, Letitia Ho, Howard C. Nusbaum
Cognitive neuroscientists have been grappling with two related experimental design problems. First, the complexity of neuroimaging data (e.g. often hundreds of thousands of correlated measurements) and analysis pipelines demands bespoke, non-parametric statistical tests for valid inference, and these tests often lack…
William Hedley Thompson, Jessey Wright, Patrick G Bissett, Russell A Poldrack
Open data has two principal uses: (i) to reproduce original findings and (ii) to allow researchers to ask new questions with existing data. The latter enables discoveries by allowing a more diverse set of viewpoints and hypotheses to approach the data, which is self-evidently advantageous for the progress of science.…
Authors not listed
Sequence is the critical determinant of macromolecular function, yet current polymer design approaches often optimize monomer composition and ratios while ignoring sequence. This creates poorly defined design spaces for active learning that miss the vast combinatorial landscape of sequence possibilities. We introduce…
Authors not listed
Metal–organic frameworks (MOFs) represent a versatile class of porous materials, yet efficiently exploring their vast chemical space for target gas adsorption properties remains a major challenge. MOFid, a text-based encoding of MOF structures, has enabled large-scale data mining using natural language processing (NLP)…