Flexible Models for Competing Risks and Weighted Analyses of Composite Endpoints

In many clinical studies the occurrence of different types of disease events over time is of interest. For example, in cardiovascular studies, disease events such as death, stroke or myocardial infarction are of interest. As another example, in central nervous system infections such as cryptococcal meningitis, unfavourable events such as death or neurological events and favourable events such as coma or fungal clearance are relevant. In statistical terminology, competing risks refer to data where the time and type of the first disease event are analysed. Such data arise naturally if a nonfatal disease event is of interest but is precluded by death in a substantial proportion of subjects. Competing risks are the topic of the first four chapters of this thesis. An alternative approach used in many randomized controlled clinical trials is to combine different harmful events to a single composite endpoint. The analysis of trials with a composite endpoints is the topic of the fifth chapter. This thesis is organised as follows: Chapters 1 and 2 are introductory chapters and provide an overview of statistical approaches to competing risks and semi-nonparametric (SNP) density estimation. Two concepts that form the basis for the work in Chapters 3 and 4 are introduced here: the cumulative incidence function (CIF) and SNP densities. For competing risks data, the CIF describes the absolute risk of different event types depending on time and is the most important quantity for data description, prognostic modelling, and medical decision making. SNP densities are densities that can be expressed as the product of a squared polynomial (of variable degree) and a base density which is chosen as the standard normal or the exponential density in this work. Chapter 3 presents a novel approach to CIF-estimation. The underlying statistical model is specified via a mixture factorization of the joint distribution of the event type and time and the time to event distributions conditional on the event type are modelled using SNP densities. One key strength of the approach is that it can handle arbitrary censoring and truncation. A stepwise forward algorithm for model estimation and adaptive selection of SNP polynomial degrees is presented, implemented in the statistical software R, evaluated in a sequence of simulation studies, and applied to data sets from clinical trials in central nervous system infections. The simulations demonstrate that the SNP approach frequently outperforms both parametric and nonparametric alternatives. They also support the use of “ad hoc” asymptotic inference to derive confidence intervals despite a lack of a formal mathematical verification for the relevant asymptotic properties. Chapter 4 extends the work of Chapter 3 to regression modelling, i.e. the quantification of cov-ariate effects on the CIF. A careful discussion of interpretational and identifiability issues which are intrinsic to models based on the mixture factorization is provided and the usage of the model is only recommended in settings with sufficient follow-up relative to the timing of the events. A simulation study demonstrates that the proposed approach is competitive compared to common statistical models for competing risks in terms of accuracy of parameter estimates and predictions. However, it also shows that “ad hoc” asymptotic inference is only valid if sample size is large. The chapter also provides a suggestion for model diagnostics of the proposed model, an area that has been somewhat neglected for competing risks data. Chapter 5 discusses the analysis of composite endpoints. A common critique of traditional analyses of composite endpoints is that all disease events are equally weighted whereas their clinical relevance may differ substantially. This chapter addresses this by introducing a framework for the weighted analysis of composite endpoints that handles both binary and time-to-event data. To address the difficulty in selecting an exact set of weights, it proposes a method for constructing simultaneous confidence intervals and tests that protect the familywise type I error in the strong sense across families of weights which satisfy flexible inequality and order constraints based on the theory of χ-2-distributions. It is then demonstrated in several simulation scenarios as well as applications that the proposed method achieves the nominal simultaneous overall coverage rate with lower efficiency loss compared to the standard Scheffe’s procedure. Final remarks are given in Chapter 6 together with an outlook for potential future research directions

薬物の副作用を予測するための高度なディープラーニングモデルの構築

京都大学新制・課程博士博士(薬科学)甲第24559号薬科博第176号新制||薬科||19(附属図書館)京都大学大学院薬学研究科医薬創成情報科学専攻(主査)教授 馬見塚 拓, 教授 山下 富義, 教授 金子 周司学位規則第4条第1項該当Doctor of Pharmaceutical SciencesKyoto UniversityDFA

A Short Hike: Writing with a videogame

This master thesis focuses on implementing a videogame in an educational setting. By doing this, the study can focus on the pupils’ interactions with the videogame and how their texts are inspired by the videogame A Short Hike. The study was performed in two different classes in 5th and 7th grade. With this in mind, the research question is: How does an adventure videogame inspire the pupils’ writing? With this question, the study can analyse the pupils’ texts and what is expressed in their texts. On the side, there will be a focus on the popular culture the pupils interact with and references and intertextuality in their texts. The study carries out a lesson plan for the classes where the game A Short Hike is being played. After the gameplay, the pupils will write a continuation of where the class stopped playing. The introduced task invites the pupils to write a narrative text with no limitations to the content. There was only one condition, and it was to write a continuation of the gameplay. The texts’ content will be analysed, and the focus during the analysis is on the texts’ references and intertextualities with other videogames, popular culture, and stories. With the analysis of four texts and observation from the study, it was discovered that the pupils’ texts contained several references and intertextualities from their interests and other videogames. The structure and theme of the texts were also inspired by previous texts they might have encountered in the past. It was also important to facilitate the pupils’ joy of writing within the study. Without it, the pupils would struggle to write and find interest in writing a text. This study encourages the teachers to learn more about the pupils’ popular culture and implement videogames in their teaching schemes. By doing this, the pupils can be more engaged in the writing and in the class. Implementing videogames for educational purposes can also motivate them and facilitate their joy of writing.

The Impact of the Economic Stimulus on Domestic, Private Enterprises

In the year 2008 and the first half of 2009, the world witnessed the unfolding and heavy repercussions of the global financial crisis which affected Vietnam, among others, through the reduction of investments inflow, lower global commodity prices and trade. The government of Vietnam has acted quickly with its stimulus package, including a 4% interest rate subsidy for enterprises with the objective of preventing the economy from falling further. While there are some anecdotal evidences about the effectiveness of the stimulus package, there is no systematic evidence of the impact of the stimulus package. This paper makes use of the PCI 2008 enterprise survey data, a unique dataset which is only recently made by available to investigate the impact of the 4% interest rate subsidy component of the stimulus package. We find strong statistical evidence that the 4% interest rate subsidy has positive and important impacts on the enterprises, easing the severe effects of the global crisis.Freeware; Global financial crisis, fiscal stimulus, interest rate subsidy, Vietnam.

Some Background on Moral Hazard Management in Banks

The article focuses on researching the theoretical framework for moral hazard management in banks. With the desk research methodology, the content focuses on researching the overview of the concept and the causes of moral hazard, study of the theoretical literature related to moral hazard management and moral hazard management models in banks

A STUDY ON POWER OUTPUT OF HORIZONTAL-AXIS WIND TURBINES UNDER RAIN

The power of the wind turbine are significantly affected by the air conditions of the operating environment. Rain is a widespread phenomenon in many parts of the world especially in Vietnam, so exploring its effect on the power of wind turbines will provide valuable insights into the design of a new wind tower. In this paper, a method and a model is developed to estimate the effect of precipitation by simulating the actual physical processes of the rain drops forming on the surface of the blades of horizontal-axis wind turbines (HAWT), thereby determining optimal wetness, then power and performance respectively. Consequently, it makes a contribution to operation and control strategies for horizontal-axis wind turbines