We contribute to debate about causal inferences in educational research in two ways. First, we quantify how much bias there must be in an estimate to invalidate an inference. Second, we utilize Rubin's causal model to interpret the bias necessary to invalidate an inference in terms of sample replacement. We apply our analysis to an inference of a positive effect of Open Court Curriculum on reading achievement from a randomized experiment, and an inference of a negative effect of kindergarten retention on reading achievement from an observational study. We consider details of our framework, and then discuss how our approach informs judgment of inference relative to study design. We conclude with implications for scientific discourse.
As noted by Fremer and Olson, analysis of answer changes is often used to investigate testing irregularities because the analysis is readily performed and has proven its value in practice. Researchers such as Belov, Sinharay and Johnson, van der Linden and Jeon, van der Linden and Lewis, and Wollack, Cohen, and Eckerly have suggested several statistics for detection of aberrant answer changes. This article suggests a new statistic that is based on the likelihood ratio test. An advantage of the new statistic is that it follows the standard normal distribution under the null hypothesis of no aberrant answer changes. It is demonstrated in a detailed simulation study that the Type I error rate of the new statistic is very close to the nominal level and the power of the new statistic is satisfactory in comparison to those of several existing statistics for detecting aberrant answer changes. The new statistic and several existing statistics were shown to provide useful information for a real data set. Given the increasing interest in analysis of answer changes, the new statistic promises to be useful to measurement practitioners.
Overexpression of Bcl-2 proteins such as Bcl2L10, also referred to as Nrh, is associated with resistance to therapy and poor survival in various cancers, including breast cancer, lung cancer, and leukemia. The single nucleotide polymorphism (SNP) of BCL2L10 in its BH4 domain at position 11 (BCL2L10 Leu11Arg, rs2231292), corresponding to position 11 in the Nrh open reading frame, is reported to lower resistance towards chemotherapy, with patients showing better survival in the context of acute leukemia and colorectal cancer. Using cellular models and clinical data, we aimed to extend this knowledge to breast cancer. We report that the homozygous status of the Nrh Leu11Arg isoform (Nrh-R) is found in 9.7–11% percent of the clinical datasets studied. Furthermore, Nrh-R confers higher sensitivity towards Thapsigargin-induced cell death compared to the Nrh-L isoform, due to altered interactions with IP3R1 Ca2+ channels in the former case. Collectively, our data show that cells expressing the Nrh-R isoform are more prone to death triggered by Ca2+ stress inducers, compared to Nrh-L expressing cells. Analysis of breast cancer cohorts revealed that patients genotyped as Nrh-R/Nrh-R may have a better outcome. Overall, this study supports the notion that the rs2231292 Nrh SNP could be used as a predictive tool regarding chemoresistance, improving therapeutic decision-making processes. Moreover, it sheds new light on the contribution of the BH4 domain to the anti-apoptotic function of Nrh and identifies the IP3R1/Nrh complex as a potential therapeutic target in the context of breast cancer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.