Project description:We discuss the results on improving the generalizability of individualized treatment rule following the work in Kallus [1] and Mo et al. [5]. We note that the advocated weights in Kallus [1] are connected to the efficient score of the contrast function. We further propose a likelihood-ratio-based method (LR-ITR) to accommodate covariate shifts, and compare it to the CTE-DR-ITR method proposed in Mo et al. [5]. We provide the upper-bound on the risk function of the target population when both the covariate shift and the contrast function shift are present. Numerical studies show that LR-ITR can outperform CTE-DR-ITR when there is only covariate shift.
Project description:In a simulation study, Stafford et al. (Behavior Research Methods, 52, 2142-2155, 2020) explored the effect of sample size on detecting group differences in ability in the presence of speed-accuracy trade-offs using the Drift Diffusion Model (DDM) and introduced an online tool to perform a power analysis. They found that the DDM approach was superior to analyzing the observed response times and response accuracies alone. In their simulation, they applied the EZ method to estimate the model parameters. In this article, we demonstrate that the EZ method, which cannot estimate the response bias parameter of the DDM, causes severe estimation bias for all parameters if the true response bias is not 0.5. Moreover, the bias patterns differ between EZ and the equivalent maximum likelihood estimation with z fixed at 0.5. This should be taken into consideration when using the otherwise excellent power analysis tool for experimental designs, in which z≠ 0.5 cannot be ruled out or even stipulate it.
Project description:Root-secreted coumarins and the microbiota interact to improve iron nutrition in Arabidopsis. Harbort and Hashimoto et al. Cell Host & Microbe 2020
Project description:Reviews by Devoe et al. (2022), Linardon et al. (2022), and Schneider et al. (2022) illustrate the profound impact the COVID-19 pandemic has had on people with eating disorders (EDs) or disordered eating (DE) and their families. However, there is a dearth of research on how the pandemic has affected individuals with marginalized identities, who have been historically underrepresented in ED/DE research. The few studies conducted to date suggest that people with marginalized identities, including people of color, LGBTQ + people, women, and people experiencing socioeconomic disadvantage, may have had even greater increases in EDs/DE than people without marginalized identities. In this Commentary, I discuss who is missing from research on EDs/DE during the COVID-19 pandemic, strategies for breaking down barriers to participation in research for diverse groups, and the implications of existing research findings for people with marginalized identities. Improved measurement of salient aspects of participants' identities and increased recruitment and retention of participants from diverse backgrounds is necessary to more fully understand the impact of the COVID-19 pandemic on all people affected by EDs and DE. Concurrently, increased access to affordable and culturally sensitive care is urgently required to meet the extensive treatment needs already documented.
Project description:In this commentary, I discuss some critical issues in the study by Greiff, S.; Stadler, M.; Sonnleitner, P.; Wolff, C.; Martin, R., "Sometimes less is more: Comparing the validity of complex problem solving measures", Intelligence 2015, 50, 100-113. I conclude that-counter to the claims made in the original study-the specific study design was not suitable for deriving conclusions about the validity of different complex problem-solving (CPS) measurement approaches. Furthermore, a more elaborate consideration of previous CPS research was found to challenge Greiff et al.'s conclusions even further. Therefore, I argue that researchers should be aware of the differences between several kinds of CPS assessment tools and conceptualizations when the validity of CPS assessment tools is examined in future research.