The purpose of this study was to investigate on a national scale the baseline level of p-value fluency of future researchers (i.e., doctoral students). To that end, two research questions were investigated. The first research question, Can a sufficiently reliable and valid measure of p-value misinterpretations (in a research context) be constructed?, was addressed via the development and validation of the Keller P-value Misinterpretation Inventory instrument (KPVMI). An iterative process of expert review, pilot testing, and field testing resulted in an adequately reliable measure (Alpha = .8030) of p-value fluency as assessed across 18 misinterpretations and 2 process levels as well as an independently validated sub-measure of p-value fluency in context as assessed across 18 misinterpretations (Alpha = .8298). The second research question, What do the results of the KPVMI administration tell us about the current level of p-value fluency among doctoral students nationally?, was addressed via analysis of a subset of the field test data (n = 147) with respect to performance on the subset of items considered sufficiently validated as developed in Phases I-III (KPVMI-1). The median score was 10/18 items answered correctly indicating that future researchers on the aggregate struggle to properly interpret and report p-values in context; furthermore, there was insufficient evidence to indicate training and experience are positively correlated with performance. These results aligned with the extant literature regarding the p-value misinterpretations of practicing researchers. / Doctor of Philosophy / The purpose of this study was to investigate on a national scale the baseline level of p-value fluency of future researchers (i.e., doctoral students). To that end, two research questions were investigated. The first research question, Can a sufficiently reliable and valid measure of p-value misinterpretations (in a research context) be constructed?, was addressed via the development and validation of the Keller P-value Misinterpretation Inventory instrument (KPVMI). The second research question, What do the results of the KPVMI administration tell us about the current level of p-value fluency among doctoral students nationally?, was addressed via analysis of a subset of the field test data (n = 147) with respect to performance on the subset of items considered sufficiently validated as developed in Phases I-III (KPVMI-1). Results indicate that future researchers on the aggregate struggle to properly interpret and report p-values in context; furthermore, there was insufficient evidence to indicate training and experience are positively correlated with performance. These results aligned with the extant literature regarding the p-value misinterpretations of practicing researchers.

In this paper we consider the problem of constructing confidence intervals and lower bounds forthe intraclass correlation coefficient in an interrater reliability study where the raters are randomly selected from a population of raters.The likelihood function of the interrater reliability is derived and simplified, and the profile likelihood based approach is readily available for computing the confidence intervals of the interrater reliability. Unfortunately, the confidence intervals computed by using the profile likelihood function are in general too narrow to have the desired coverage probabilities. From the point view of practice, a conservative approach, if is at least as precise as any existing method, is preferred sinceit gives the correct results with a probability higher than claimed. Under this rationale, we propose the so-called modified likelihood approach in this paper. Simulation study shows that, the proposed method in general has better performance than currently used methods.

No / Medical statistics is a vast and ever-growing field of academic endeavour, with direct application to developing the robustness of the evidence base in all areas of medicine. Although the complexity of available statistical techniques has continued to increase, fuelled by the rapid data processing capabilities of even desktop/laptop computers, medical practitioners can go a long way towards creating, critically evaluating and assimilating this evidence with an understanding of just a few key statistical concepts. While the concepts of statistics and ethics are not common bedfellows, it should be emphasised that a statistically flawed study is also an unethical study.[1] This review will outline some of these key concepts and explain how to interpret the output of some commonly used statistical analyses. Examples will be confined to two-group tests on independent samples, using both a continuous and a dichotomous/binary outcome measure.

Composite endpoints are widely used in clinical trials. The outcome of a clinical trial can affect many individuals and it is therefore of importance that the methods used are as effective and correct as possible. Improvements of the standard method of testing composite endpoints have been proposed and in this thesis, the alternative method using nonparametric combination methodology is compared to the standard method. Performing a simulation study, the power of three combining functions (Fisher, Tippett and the Logistic) are compared to the power of the standard method. The performances of the four methods are evaluated for different compositions of treatment effects, as well as for independent and dependent components. The results show that using the nonparametric combination methodology leads to higher power in both dependent and independent cases. The combining functions are suitable for different compositions of treatment effects, the Fisher combining function being the most versatile. The thesis is written with support from Statisticon AB.

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The focus of this thesis is on facial biometrics; specifically in the problems of face detection and face recognition. Despite intensive research over the last 20 years, the technology is not foolproof, which is why we do not see use of face recognition systems in critical sectors such as banking. In this thesis, we focus on three sub-problems in these two areas of research. Firstly, we propose methods to improve the speed-accuracy trade-off of the state-of-the-art face detector. Secondly, we consider a problem that is often ignored in the literature: to decrease the training time of the detectors. We propose two techniques to this end. Thirdly, we present a detailed large-scale study on self-updating face recognition systems in an attempt to answer if continuously changing facial appearance can be learnt automatically. / L'objectiu d'aquesta tesi és sobre biometria facial, específicament en els problemes de detecció de rostres i reconeixement facial. Malgrat la intensa recerca durant els últims 20 anys, la tecnologia no és infalible, de manera que no veiem l'ús dels sistemes de reconeixement de rostres en sectors crítics com la banca. En aquesta tesi, ens centrem en tres sub-problemes en aquestes dues àrees de recerca. En primer lloc, es proposa mètodes per millorar l'equilibri entre la precisió i la velocitat del detector de cares d'última generació. En segon lloc, considerem un problema que sovint s'ignora en la literatura: disminuir el temps de formació dels detectors. Es proposen dues tècniques per a aquest fi. En tercer lloc, es presenta un estudi detallat a gran escala sobre l'auto-actualització dels sistemes de reconeixement facial en un intent de respondre si el canvi constant de l'aparença facial es pot aprendre de forma automàtica.