1,721,412 research outputs found
Can machine learning support survival model selection to inform economic evaluations? Exploring K-Fold cross validation based model selection in seven datasets
No full textfrom the intent-to-treat population. Estimated HRs and 95% CIs of ivosidenib versus placebo were calculated. Results: The previously published RPSFTM-adjusted results showed that ivosidenib was associated with mortality risk reduction (MRR) versus placebo (HR=0.49 [95% CI: 0.34; 0.70]). The external analysis reported here, showed that ivosidenib was associated with MRR, using the RPSFTM 'treatment group' (not re-censored HR=0.52 [95% CI: 0.37; 0.75]), and 'on-treatment' approaches (re-censored HR=0.49 [95% CI: 0.28; 0.87]; not re-censored HR=0.52 [95% CI: 0.36; 0.74]). The IPCW-adjusted Cox proportional hazards regression analysis also showed that ivosidenib was associated with MRR (HR=0.74 [95% CI: 0.35; 1.56]). Conclusions: All three crossover adjustment methods applied in this external re-analysis of ClarIDHy data showed that ivosidenib was associated with MRR, consistent with previously published RPSFTM-adjusted results. Objectives: The selection of survival models for informing economic evaluations of innovative therapies with limited long-term data traditionally relies on metrics of statistical goodness of fit in the full trial data. However, models selected based on full trial data might underperform in the target population due to overfitting. K-fold cross validation (CV), commonly used in machine learning, splits the data allowing better estimation of fit in unseen data. We explore whether k-fold CV improves model selection. Methods: We used seven publicly available long-term survival datasets covering a range of diseases. We simulated 100 artificial data locks by sampling 250 patients without replacement, and right-censoring once median survival was reached. We fitted standard parametric and flexible survival models to each simulated dataset and selected models with lowest AIC/BIC as estimated using 10-fold CV and traditional methods. We then estimated the restricted mean survival time (RMST) error of best-fitting models relative to the RMST calculated from the full dataset's Kaplan-Meier. Results: K-fold CV led to lower mean RMST errors compared to traditional model selection methods in six (all seven) datasets when selecting models based on AIC (and BIC). On average, the RMST error was 27% higher (when based on AIC) and 40% (BIC) higher using traditional model selection compared to CV-based model selection. CV never selected complex models (3+ parameters) whilst the traditional method resulted in complex models being selected in 51% (AIC) and 12% (BIC) of simulations. Conclusions: In the first study exploring k-fold CV for survival model selection, we show that it can regularly outperform traditional methods. Notably, k-fold CV favors less complex models compared to traditional methods, which may hint at their better generalizability. We conclude that k-fold CV may be an important addition to the modeler's toolbox when performing survival analysis. Further research should explore whether these findings hold in additional settings. Objectives: The purpose of the present study was to assess how the eight dimensions of the SF-36 HRQoL profile instrument impact the utility scores derived from the major multiattribute utility instruments (MAUIs). Methods: We employed the ordinary least squares (OLS) estimator to estimate models that analyze the relationship between SF-36 dimensions and various MAUIs using data from the multi-instrument comparison (MIC) study (Richardson et al., 2015). We focused on the sensitivity of six major MAUIs-AQoL-4D, AQoL-8D, 15D, EQ-5D, SF-6D, and HUI3-to changes in the eight SF-36 dimensions. Results: Our analysis show that the AQoL-8D demonstrates greater sensitivity to mental health (MH) compared to AQoL-4D, 15D, EQ-5D, and HUI3. The EQ-5D showed higher sensitivity to bodily pain (BP) than all other MAUIs. Additionally, the 15D was more sensitive to physical functioning (PF) compared to AQoL-4D and AQoL-8D. Finally, the SF-6D exhibited greater sensitivity to the role emotional (RE) dimension than 15D, AQoL-4D, and AQoL-8D. Conclusions: Our study highlights that HRQoL utility scores are affected differently by the eight dimensions measured by the SF-36 survey, depending on the MAUI used. These findings allow to deduce which dimensions of the SF-36 have the greatest influence on the utility scores generated by a specific MAUI. Thus, the selection of a MAUI for research may be informed by its sensitivity to the health dimensions of particular interest
Can machine learning support survival model selection to inform economic evaluations? Exploring K-Fold cross validation based model selection in seven datasets
No full textfrom the intent-to-treat population. Estimated HRs and 95% CIs of ivosidenib versus placebo were calculated. Results: The previously published RPSFTM-adjusted results showed that ivosidenib was associated with mortality risk reduction (MRR) versus placebo (HR=0.49 [95% CI: 0.34; 0.70]). The external analysis reported here, showed that ivosidenib was associated with MRR, using the RPSFTM 'treatment group' (not re-censored HR=0.52 [95% CI: 0.37; 0.75]), and 'on-treatment' approaches (re-censored HR=0.49 [95% CI: 0.28; 0.87]; not re-censored HR=0.52 [95% CI: 0.36; 0.74]). The IPCW-adjusted Cox proportional hazards regression analysis also showed that ivosidenib was associated with MRR (HR=0.74 [95% CI: 0.35; 1.56]). Conclusions: All three crossover adjustment methods applied in this external re-analysis of ClarIDHy data showed that ivosidenib was associated with MRR, consistent with previously published RPSFTM-adjusted results. Objectives: The selection of survival models for informing economic evaluations of innovative therapies with limited long-term data traditionally relies on metrics of statistical goodness of fit in the full trial data. However, models selected based on full trial data might underperform in the target population due to overfitting. K-fold cross validation (CV), commonly used in machine learning, splits the data allowing better estimation of fit in unseen data. We explore whether k-fold CV improves model selection. Methods: We used seven publicly available long-term survival datasets covering a range of diseases. We simulated 100 artificial data locks by sampling 250 patients without replacement, and right-censoring once median survival was reached. We fitted standard parametric and flexible survival models to each simulated dataset and selected models with lowest AIC/BIC as estimated using 10-fold CV and traditional methods. We then estimated the restricted mean survival time (RMST) error of best-fitting models relative to the RMST calculated from the full dataset's Kaplan-Meier. Results: K-fold CV led to lower mean RMST errors compared to traditional model selection methods in six (all seven) datasets when selecting models based on AIC (and BIC). On average, the RMST error was 27% higher (when based on AIC) and 40% (BIC) higher using traditional model selection compared to CV-based model selection. CV never selected complex models (3+ parameters) whilst the traditional method resulted in complex models being selected in 51% (AIC) and 12% (BIC) of simulations. Conclusions: In the first study exploring k-fold CV for survival model selection, we show that it can regularly outperform traditional methods. Notably, k-fold CV favors less complex models compared to traditional methods, which may hint at their better generalizability. We conclude that k-fold CV may be an important addition to the modeler's toolbox when performing survival analysis. Further research should explore whether these findings hold in additional settings. Objectives: The purpose of the present study was to assess how the eight dimensions of the SF-36 HRQoL profile instrument impact the utility scores derived from the major multiattribute utility instruments (MAUIs). Methods: We employed the ordinary least squares (OLS) estimator to estimate models that analyze the relationship between SF-36 dimensions and various MAUIs using data from the multi-instrument comparison (MIC) study (Richardson et al., 2015). We focused on the sensitivity of six major MAUIs-AQoL-4D, AQoL-8D, 15D, EQ-5D, SF-6D, and HUI3-to changes in the eight SF-36 dimensions. Results: Our analysis show that the AQoL-8D demonstrates greater sensitivity to mental health (MH) compared to AQoL-4D, 15D, EQ-5D, and HUI3. The EQ-5D showed higher sensitivity to bodily pain (BP) than all other MAUIs. Additionally, the 15D was more sensitive to physical functioning (PF) compared to AQoL-4D and AQoL-8D. Finally, the SF-6D exhibited greater sensitivity to the role emotional (RE) dimension than 15D, AQoL-4D, and AQoL-8D. Conclusions: Our study highlights that HRQoL utility scores are affected differently by the eight dimensions measured by the SF-36 survey, depending on the MAUI used. These findings allow to deduce which dimensions of the SF-36 have the greatest influence on the utility scores generated by a specific MAUI. Thus, the selection of a MAUI for research may be informed by its sensitivity to the health dimensions of particular interest
Comparison fairytales of B. Němcová, K. J. Erben and Grimm´s brothers
No full textThis bachelor thesis deals with comparison fairy tales of B. Němcová, K. J. Erben and Grimm´s brothers. It is divided into three parts. The theoretical part contains genre characteristics of fairy tales, theories of its origin and its classification, the classification of fairy tales as a special genre and the last chapter is about Frank Wollman. The practical part is about Božena Němcová, Karel Jaromír Erben and Grimm´s brothers. The interpretative part deals with an analysis of fairy tale Tři zlaté vlasy děda Vševěda
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
THOR-ICO: a general circulation model for exoplanets on an icosahedral grid
No full textThe study of extrasolar planets has become important since the discovery of a large number of these astronomical objects. The diversity of planetary characteristics observed raises questions about the variety of climates. The influence of the astronomical and planetary bulk parameters in driving the atmospheric circulations continues to be poorly understood. In the solar system the results from planetary spacecraft missions have demonstrated how different the planetary climate and atmospheric circulations can be. The study of exoplanets is going to require a study of a far greater range of physical and orbital parameters than the ones that characterise our neighbour planets (in the solar system). For this reason the study of exoplanets will involve an even greater diversity of circulation and climate regimes. We are developing a dedicated General Circulation Model (GCM) for extrasolar planets called "Exoclimes Simulation Platform". This model will solve the complex physical and dynamical equations that include fundamental principles of atmospheric fluid dynamics and various idealisations of, for example, radiative transfer [1] and dry or moist convection. The interpretation and analysis of the results from this complex model will help us to have a better understanding on the diversity of climates and atmospheric circulations. Here we present the first results of our recent scheme which represents the fluid dynamical phenomena in the atmosphere. This new code solves the atmospheric fluid equations in a rotating sphere (fully compressible - elastic - nonhydrostatic system) using an icosahedral grid. The grid is also modified to improve the uniformity of the grid point distribution applying a method called spring dynamics [2]. The results shown include 3D experiments of gravity and acustic waves, Held-Suarez test case [3] and an idealized hot-Jupiter case. ..
THOR-ISO: a global circulation model for exoplanets on an icosahedral grid
No full textIn this presentation I will describe the details and first results of our new dynamical code for exoplanet atmospheres. This model is part of the Exoclimes Simulation Platform (ESP), and is a project of the Exoplanet and Exoclimes Group (see www.exoclime.org). The model I will present solves the complex physical and dynamical equations that include fundamental principles of atmospheric fluid dynamics and various idealisations of radiative transfer and dry convection, among others. I will also show the results of the first successful benchmark tests for this model, where we explore the results of the model for Earth-like and Hot-Jupiter like conditions. The analysis of the results from this complex and detailed model, will help us to have a better understanding of the diversity of climates and atmospheric circulations that we expect to find in the multitude of exoplanets already discovered. ..
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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