<p>It has been claimed that there are considerable differences between pri-vate and non-private patients with regard to the outcome of back surgery.This can be found in the yearly report from the register concerning backsurgery in Sweden. However, the results seem doubtful and the referencescould not be found. Therefore, we analyze the data about nearly 1200patients from the clinic of back surgery in Str¨angn¨as (CSS). It includesthree time periods with somewhat different questionnaires from 1986 to2007 with both private and non-private patients. In the third period,the patients have been evaluated using the SF-36 questionnaire. The re-sults show that most of the differences between private and non-privatepatients are minor and not statistically significant.</p>

It has been claimed that there are considerable differences between pri-vate and non-private patients with regard to the outcome of back surgery.This can be found in the yearly report from the register concerning backsurgery in Sweden. However, the results seem doubtful and the referencescould not be found. Therefore, we analyze the data about nearly 1200patients from the clinic of back surgery in Str¨angn¨as (CSS). It includesthree time periods with somewhat different questionnaires from 1986 to2007 with both private and non-private patients. In the third period,the patients have been evaluated using the SF-36 questionnaire. The re-sults show that most of the differences between private and non-privatepatients are minor and not statistically significant.

Biclustering is a technique for clustering rows and columns of a data matrix simultaneously. Over the past few years, we have seen its applications in biology-related fields, as well as in many data mining projects. As opposed to classical clustering methods, biclustering groups objects that are similar only on a subset of variables. Many biclustering algorithms on continuous data have emerged over the last decade. In this dissertation, we will focus on two Bayesian biclustering algorithms we developed for discrete data, more specifically categorical data and ordinal data. / Statistics

In the Groundwork for the Metaphysics of Morals, Kant gives several formulations of the categorical imperative, one being the universal law of nature formulation. One question that can be raised is why Kant formulates the categorical imperative in terms of universal laws of nature at all. In this paper, I will argue that it is necessary for Kant to formulate the categorical imperative in terms of universal laws of nature in order to demonstrate the applicability of the moral law to our maxims and hence the possibility of the moral law as a functional practical principle.

Many people in widely varied fields are exposed to categorical data describing myriad observations. The breadth of applications in which categorical data are used means that many of the people tasked to apply these data have not been trained in data analysis. Visualization of data is often used to alleviate this problem since visualization can convey relevant information in a non-mathematical manner. However, visualizations are frequently static and the tools to create them are largely geared towards quantitative data. It is the purpose of this thesis to demonstrate a method which expands on the parallel coordinates method of visualization and uses a 'Google Maps' style of interaction and view dependent data presentation for visualizing and exploring categorical data that is accessible by non-experts and promotes the use of domain specific knowledge. The parallel coordinates method has enjoyed increasing popularity in recent times, but has several shortcomings. This thesis seeks to address some of these problems in a manner which involves not just addressing the final static image which is generated, but the paradigm of interaction as well.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第22980号 / 理博第4657号 / 新制||理||1669(附属図書館) / 京都大学大学院理学研究科数学・数理解析専攻 / (主査)教授 長谷川 真人, 准教授 照井 一成, 准教授 河村 彰星 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

We compare different multiple imputation methods for categorical variables using the MICE package in R. We take a complete data set and remove different levels of missingness and evaluate the imputation methods for each level of missingness. Logistic regression imputation and linear discriminant analysis (LDA) are used for binary variables. Multinomial logit imputation and LDA are used for nominal variables while ordered logit imputation and LDA are used for ordinal variables. After imputation, the regression coefficients, percent deviation index (PDI) values, and relative frequency tables were found for each imputed data set for each level of missingness and compared to the complete corresponding data set. It was found that logistic regression outperformed LDA for binary variables, and LDA outperformed both multinomial logit imputation and ordered logit imputation for nominal and ordered variables. Simulations were ran to confirm the validity of the results.

No description available.

abstract: Statistical inference from mediation analysis applies to populations, however, researchers and clinicians may be interested in making inference to individual clients or small, localized groups of people. Person-oriented approaches focus on the differences between people, or latent groups of people, to ask how individuals differ across variables, and can help researchers avoid ecological fallacies when making inferences about individuals. Traditional variable-oriented mediation assumes the population undergoes a homogenous reaction to the mediating process. However, mediation is also described as an intra-individual process where each person passes from a predictor, through a mediator, to an outcome (Collins, Graham, & Flaherty, 1998). Configural frequency mediation is a person-oriented analysis of contingency tables that has not been well-studied or implemented since its introduction in the literature (von Eye, Mair, & Mun, 2010; von Eye, Mun, & Mair, 2009). The purpose of this study is to describe CFM and investigate its statistical properties while comparing it to traditional and casual inference mediation methods. The results of this study show that joint significance mediation tests results in better Type I error rates but limit the person-oriented interpretations of CFM. Although the estimator for logistic regression and causal mediation are different, they both perform well in terms of Type I error and power, although the causal estimator had higher bias than expected, which is discussed in the limitations section. / Dissertation/Thesis / Masters Thesis Psychology 2019

Individuals perceive emotional facial expressions in categories. Specifically, for basic emotional expressions, discrimination performance is better for pairs of stimuli that fall in either side of a perceptual category boundary than for those within a perceptual category. In this thesis I have examined categorical perception of emotional facial expressions from a number of different perspectives. In Chapter 2, I found in two experiments that categorical perception of emotional facial expressions of a robust phenomenon with a few consistent individual differences. There findings highlight some of the important caveats that categorical perception researchers face, not only in the area of emotional facial expressions, but across domains as well. In Chapter 3 I show that context has an effect on the visual perception of emotional facial expressions. A surprise-fear continuum was perceived categorically only in the case in which a context story was provided for the surprise face. In Chapter 4 I demonstrate categorical perception of a happy-sad continuum in 3.5-year-olds. This is an important study in development because the current literature is limited by studies that do not compare identification and discrimination performance in these age groups. The experiment in this chapter uses both identification and discrimination tasks and compares the results of 3.5-year-olds to adults who do the exact same task. The results suggest that 3.5-year-olds perceive happy and sad expressions as adults do, categorically. In Chapter 5 I develop a powerful new methodology for the study of the category boundary using non-verbal methods. This investigation with emotional facial expressions shows it can be reliably used to identify category boundary information in adults. Perception of emotional facial expressions is an essential part of successful social cognition, and the phenomenon of categorical perception specifically allows individuals to quickly and accurately respond to expressions. The research in this thesis is a further step in understanding the processes that allows individuals to be successful in a social environment. / Thesis / Doctor of Philosophy (PhD)