The Effects of Two Association Measures on L2 Collocation Processing

[PORTUGUESE ABSTRACT] Neste estudo, demonstramos como significância estatística pode variar a partir da comparação de quatro métodos distintos: teste t, ANOVA (seguida de Tukey HSD), modelo linear simples, e modelo linear de efeitos mistos. Em nossa demonstração, modelamos tempos de reação em função de diferentes afixos em dinamarquês, e mostramos como nossas conclusões a respeito do efeito de certos afixos podem mudar categoricamente dependendo de qual dos métodos mencionados acima decidimos utilizar. Por fim, reiteramos o que dizem estudos recentes, e sugerimos que modelos de efeitos mistos devam ser a norma sempre que dados agrupados forem analisados. Esperamos, com este estudo, alertar pesquisadores da área para a importância de decisões analíticas bem informadas e éticas em estudos linguísticos.[ENGLISH ABSTRACT] In this study, we illustrate the potential variability of statistical significance by comparing four different methods, namely, t-test, ANOVA (followed by Tukey HSD), simple linear regression, and mixed effects linear regression. In our demonstration, we model reaction times as a function of different affixes in Danish, and show how our conclusions regarding the effect of certain affixes can change categorically depending on which of the aforementioned methods we choose to use. Finally, we echo recent studies and suggest that mixed effects models be the norm whenever grouped data is analyzed. With our comparison, we hope to raise researchers’ awareness to the need for well-informed and ethical analytical decisions in linguistic studies.

Abstract Background Tofogliflozin, an SGLT2 inhibitor, is associated with favorable metabolic effects, including improved glycemic control and serum lipid profile and decreased body weight, visceral adipose tissue, and blood pressure (BP). This study evaluated the effects of tofogliflozin on the brachial-ankle pulse wave velocity (baPWV) in patients with type 2 diabetes (T2DM) without a history of apparent cardiovascular disease. Methods The using tofogliflozin for possible better intervention against atherosclerosis for type 2 diabetes patients (UTOPIA) trial is a prospective, randomized, open-label, multicenter, parallel-group, comparative study. As one of the prespecified secondary outcomes, changes in baPWV over 104 weeks were evaluated in 154 individuals (80 in the tofogliflozin group and 74 in the conventional treatment group) who completed baPWV measurement at baseline. Results In a mixed-effects model, the progression in the right, left, and mean baPWV over 104 weeks was significantly attenuated with tofogliflozin compared to that with conventional treatment (– 109.3 [– 184.3, – 34.3] (mean change [95% CI] cm/s, p = 0.005; – 98.3 [– 172.6, – 24.1] cm/s, p = 0.010; – 104.7 [– 177.0, – 32.4] cm/s, p = 0.005, respectively). Similar findings were obtained even after adjusting the mixed-effects models for traditional cardiovascular risk factors, including body mass index (BMI), glycated hemoglobin (HbA1c), total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglyceride, systolic blood pressure (SBP), hypertension, smoking, and/or administration of drugs, including hypoglycemic agents, antihypertensive agents, statins, and anti-platelets, at baseline. The findings of the analysis of covariance (ANCOVA) models, which included the treatment group, baseline baPWV, and traditional cardiovascular risk factors, resembled those generated by the mixed-effects models. Conclusions Tofogliflozin significantly inhibited the increased baPWV in patients with T2DM without a history of apparent cardiovascular disease, suggesting that tofogliflozin suppressed the progression of arterial stiffness. Trial Registration UMIN000017607. Registered 18 May 2015. (https://www.umin.ac.jp/icdr/index.html)

Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of Wollack and Eckerly (2017) and Sinharay (2018) and suggests a new aggregate-level EDI by incorporating the empirical best linear unbiased predictor from the literature of linear mixed-effects models (e.g., McCulloch et al., 2008). A simulation study shows that the new EDI has larger power than the indices of Wollack and Eckerly (2017) and Sinharay (2018). In addition, the new index has satisfactory Type I error rates. A real data example is also included.

The global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic leading to coronavirus disease 2019 (COVID-19) is straining hospitals. Judicious resource allocation is paramount but difficult due to the unpredictable disease course. Once hospitalized, discerning which patients may progress to critical disease would be valuable for resource planning. Medical records were reviewed for consecutive hospitalized patients with COVID-19 in a large healthcare system in Texas. The main outcome was progression to critical disease within 10 days from admission. Albumin trends from admission to 7 days were analyzed using mixed-effects models, and progression to critical disease was modeled by multivariable logistic regression of laboratory results. Risk models were evaluated in an independent group. Of 153 non-critical patients, 28 (18%) progressed to critical disease. The rate of decrease in mean baseline-corrected (Δ) albumin was −0.08 g/dL/day (95% CI −0.11 to −0.04; p<0.001) or four times faster, in those who progressed compared with those who did not progress. A model of Δ albumin combined with lymphocyte percentage predicting progression to critical disease was validated in 60 separate patients (sensitivity, 0.70; specificity, 0.74). ALLY (delta albumin and lymphocyte percentage) is a simple tool to identify patients with COVID-19 at higher risk of disease progression when: (1) a 0.9 g/dL or greater albumin drop from baseline within 5 days of admission or (2) baseline lymphocyte of ≤10% is observed. The ALLY tool identified >70% of hospitalized cases that progressed to critical COVID-19 disease. We recommend prospectively tracking albumin. This is a globally applicable tool for all healthcare systems.