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Causality Analysis of Climate and Ecosystem Time Series
Published in Vyacheslav Lyubchich, Yulia R. Gel, K. Halimeda Kilbourne, Thomas J. Miller, Nathaniel K. Newlands, Adam B. Smith, Evaluating Climate Change Impacts, 2020
Mohammad Gorji Sefidmazgi, Ali Gorji Sefidmazgi
To study the causality of X1 → X2, the shadow manifolds, and , are reconstructed. Then, a vector on is selected, and its E + 1 nearby points on are found. The time indices of these points on are used to identify the corresponding points in (Figure 7.3). Then, a locally weighted mean is calculated to find the . The weights are found based on the distance between selected point in and its E + 1 neighbors. If the causality X1 → X2, exists, the should converge to X1(t) as value of L increases. The predictability is measured by error metrics such as mean absolute error and root mean square error (MAE and RMSE), or the correlation between observed and predicted values (ρ). This procedure is repeated over many random subsamples of the time series and the final result is the aggregation of these values over different L values (Sugihara et al, 2012).
Designing Phase II Dose-Finding Studies: Sample Size, Doses, and Dose Allocation Weights
Published in John O’Quigley, Alexia Iasonos, Björn Bornkamp, Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials, 2017
Note that when an approach like MCP-Mod is used, the model selection should be simulated as well, as it is part of the procedure. Although this was only examined on the metric in this chapter, it should be taken into account for any other performance metric for sample size calculation. Still, similar to the case for power calculations, different sample sizes will be associated with the different true candidate models and a summary function will be needed to combine the individual n’s into a single sample size recommendation. A conservative, but often not feasible, approach is to take the maximum sample size. Alternatives would be the median or some weighted mean of the individual values.
Managing the training load of overreached athletes
Published in Michael Kellmann, Jürgen Beckmann, Sport, Recovery, and Performance, 2017
Laurent Bosquet, Nicolas Berryman, Iñigo Mujika
As we have seen in previous sections, maximal gains are obtained with a tapering intervention of two-week duration, where the training volume is exponentially decreased by 41–60%, without any modification of either training intensity or frequency. What is the magnitude of the gains we are talking about? When using the scale of Cohen (1988) for the interpretation of standardised mean differences, expected performance improvements are most often small, and occasionally moderate. When expressed as a percent difference, the weighted mean improvement is 1.96%, which is of the same order of magnitude as the mathematical prediction by Thomas and Busso (2005). This difference could be considered as meaningless if the population of interest was not competitive athletes. As highlighted by Hopkins, Hawley, and Burke (1999), the smallest enhancement of performance that has a substantial effect on a top athlete’s chance of a medal is about one third of the typical variation of performance in competition. This has been shown to be approximately 0.5–1% in both swimming and running (Hopkins & Hewson, 2001; Stewart & Hopkins, 2000). In this context, the gains that can be expected after a taper intervention, as little as they are, may have a major impact on an athlete’s success in major competitions. An illustration was provided by Mujika et al. (2002), who reported that the magnitude of taper-induced improvements in performance in the Olympic swimming events (2.2%) were of similar order to the differences between the gold medallist and the fourth place (1.62%) or between third and eighth place (2.02%) at the 2000 Sydney Olympics.
Extended high-frequency bone conduction audiometry Calibration of bone conductor transducers in the conventional and extended high-frequency range
Published in International Journal of Audiology, 2023
Table 2 shows the average BC threshold levels in force levels (dB 1 µN/V) between 8 and 16 kHz reported by Richter and Brinkmann 1981; Richter and Frank 1985; Frank and Ragland 1987; McDermott et al. 1991 and Hallmo, Sundby, and Mair 1994 observed in young normal-hearing listeners measured with the KH70 bone conductor. In the same table, the weighted mean values are shown to account for the different number of ears per study. The differences between the mean and weighted mean are very small and are likely not clinically significant. There was no peer-reviewed paper found with BC threshold measured with the KLH96 bone conductor. The manufacturer Westra Electronics GmbH provided us with a technical calibration report by Physikalisch-Technische Bundesanstalt (PTB Report 1997) with EHF thresholds between 8 and 16 kHz in 17 ears obtained with a KLH96. This PTB report does not mention the RETVFL values below 8 kHz nor the repeatability of the thresholds.
Concordance between creatinine- and cystatin C-based eGFR in clinical practice
Published in Scandinavian Journal of Clinical and Laboratory Investigation, 2021
Emil den Bakker, Marin Musters, Isabelle Hubeek, Joanna A. E. van Wijk, Reinoud J. B. J. Gemke, Arend Bokenkamp
In the group with |ΔeGFR|>40% known explanations for low agreement were sought. Due to the structure of the eGFR equations used, any difference in eGFR is mathematically equivalent to a difference in rescaled biomarker. Explanations for low agreement were defined as known factors interfering with the accuracy of either of the two markers, such as low muscle mass as known in patients with neural tube defects [4] or low BMI for creatinine or use of glucocorticosteroids, which are known to influence cystatin C [9]. Additionally, we assessed patient groups in whom a weighted mean has been shown to increase accuracy. [4] In patients with multiple measurements we also sought for outliers indicating an analytical error. Outliers were defined as a single measurement with |ΔeGFR|>40% while in at least three other measurements |ΔeGFR| was below 30%.
Daunorubicin and cytarabine for certain types of poor-prognosis acute myeloid leukemia: a systematic literature review
Published in Expert Review of Clinical Pharmacology, 2019
Juan Eduardo Megías-Vericat, David Martínez-Cuadrón, Miguel Ángel Sanz, José Luis Poveda, Pau Montesinos
From the selected studies we extracted the following data: study design, chemotherapy scheme, AML status (poor-prognosis subgroups of patients analyzed), median age, the median of CR, OS and, other survival rates, including event-free survival (EFS), disease-free survival (DFS), and relapse-free survival (RFS). For the purposes of this study, the CR rate was reported including the CR, CR with incomplete blood count recovery (CRi) and CR without platelet recovery (CRp). The median CR durations (mCRD) and the rate of allogeneic or autologous hematopoietic stem cell transplant (HSCT) were reported when data was available. The median OS (mOS) and survival rates were reported in months. In order to describe the overall effectiveness of each schedule, we calculated the weighted mean and the ranges of CR (wmCR) and OS (wmOS) of different studies adjusted by the sample size. The weighted mean was calculated by summing the product of each variable by its sample size of the different studies and dividing the result by the sum of all the sample sizes. In addition, we have represented using box-plot diagrams the CR rates and mOS reported in the different subgroups of AML with poor prognosis, as well as in the different age groups (<60 and ≥60 years) and with the dosages of DNR and Ara-C, when we have data from at least two cohorts (IBM SPSS Statistics version 22, IBM Corp., Chicago, IL, USA).