Este estudo apresenta uma análise sobre a aplicação do geoprocessamento integrado à técnica de Análise Envoltória de Dados (Data Envelopment Analysis - DEA), relacionada a distribuição espacial de empresas em unidades produtivas representadas por áreas de zoneamento do solo urbano, utilizando dados socioeconômicos multitemporais. O trabalho tem como área de estudo o Município de Osasco, localizado na Região Metropolitana de São Paulo, que faz parte do trecho Oeste do Sistema Viário Rodoanel Mário Covas. Desta forma, a análise de instalação de empresas nos períodos anterior e posterior a implantação do sistema viário Rodoanel, poderá servir de apoio na avaliação de mudanças ou transformações empresariais (indústria, comércio e serviços) no uso e ocupação do solo no Município de Osasco. De uma forma mais específica, o estudo buscou avaliar a influência dos fatores espaciais no processo de localização e migração de empresas, focando em alterações no uso do solo com ênfase no zoneamento do município e em função da melhoria de infra-estrutura relacionada à construção de uma grande obra viária e tomando como base períodos de tempo e situações urbanas distintas. Para traçar este panorama foram utilizadas informações sócioeconômicas, dados cadastrais de empresas e o zoneamento municipal associadas a dados geográficos, os quais permitiram compor cenários multitemporais de cada momento urbano. Estes cenários foram representados e analisados no capítulo de resultados utilizando o índice de instalação de empresas em conjunto com as analises espaciais do SIG, que proporcionou uma análise temporal quantitativa da distribuição de empresas no Município de Osasco. / This study presents an analysis on GIS application integrated to Data Envelopment Analysis - DEA, related to spatial distribution of companies in productive units represented by zoning areas of the urban land and using socioeconomic data of different time periods. The work has Osasco\'s Municipal district as the area of study, located in São Paulo\'s Metropolitan Region, it makes part of the west section of the Mário Covas Rodoanel road system. Thus, the analysis will support in the changes evaluation or managerial transformations (industries, commerce and services) in the Osasco\'s Municipal district land use, current of the Rodoanel road system implantation. In a more specific way, the study sought to evaluate the influence of the space factors in the companies location and migration process, focusing on alterations in the land use with emphasis in the municipal district zoning and in infrastructure improvement function related to construction of a big road and taking as time\'s base periods and distinct urban situations. To trace this panorama were used socioeconomic information, cadastral data of companies and the municipal zoning associated to geographical data, to compose urban scenarios in different time periods. These scenarios were represented and analyzed in the results chapter using the companies installation index together with Spatial GIS Analysis, who provided a quantitative temporal analysis of distribution of companies in Osasco\'s Municipal distritct.

Análise de expressão gênica em larga escala é de fundamental importância para a biologia molecular atual pois possibilita a medida dos níveis de expressão de milhares de genes simultaneamente, o que torna viável a realização de trabalhos voltados para biologia de sistemas (systems biology). Dentre as principais técnicas experimentais disponíveis para esta finalidade, a tecnologia de microarray tem sido amplamente utilizada. Este procedimento para medida de expressão gênica é bastante complexo e os dados obtidos são freqüentemente observacionais, o que dificulta a modelagem estatística. Não existe um protocolo padrão para a geração e avaliação desses dados, sendo portanto necessário buscar procedimentos de análise que sejam adequados para cada caso. Assim, os principais métodos matemáticos e estatísticos aplicados para a análise desses dados deveriam estar disponíveis de uma forma organizada, coerente e simples em um ambiente computacional que confira robustez, confiabilidade e reprodutibilidade às análises realizadas. Uma forma de garantir estas características é através da representação (e documentação) de todos os algoritmos utilizados na forma de um grafo direcionado e acíclico que descreva todo o conjunto de transformações, ou operações, aplicadas seqüencialmente ao conjunto de dados. De acordo com esta filosofia, um ambiente foi implementado neste trabalho incorporando diversos procedimentos disponíveis na literatura atual, além de outros que foram aprimorados ou propostos nesta tese. Dentre os métodos de análise já disponíveis que foram incorporados destacam-se aqueles para a construção de agrupamentos, busca de genes diferencialmente expressos e classificadores, construção de redes de relevância e classificação funcional de grupos gênicos. Além disso, o método de construção de redes de relevância foi revisto e aprimorado e um modelo estatístico para a classificação funcional de redes de regulação gênica foi proposto e implementado. Esses dois últimos métodos surgiram a partir de problemas biológicos para os quais não existiam procedimentos de análise adequados na literatura. Finalmente, são apresentados dois conjuntos de dados que foram analisados utilizando diversas ferramentas disponíveis neste ambiente computacional. / High throughput gene expression analysis has a great importance to molecular biology nowadays because it can measure expression profiles for hundreds of genes, and this turn possible studies focused in systems biology. Between the main experimental techniques available in this direction, the microarray technology has been widely used. This experimental procedure to quantify gene expression profiles is very complex and the data obtained is frequently observational, what difficult the statistical modelling. There is not a standard protocol for the generation and evaluation of microarray data, therefore it is necessary to search by adequate analysis methods for each case. Thus, the main mathematical and statistical methods applied to microarray data analysis would have to be available in an organized, coherent and simple way in a computational environment that confer robustness, reliability and reproducibility to the data analysis. One way to guarantee these characteristics is through the representation (and documentation) of all used algorithms as a directed and acyclic graph that describes the set of transformations, or operations, applied sequentially to the dataset. According to this philosophy, an environment was implemented in this work aggregating several data analysis procedures already available in the literature, beyond other methods that were improved or proposed in this thesis. Between the procedures already available that were incorporated we can distinguish that ones for cluster analysis, differentially expressed genes and classifiers search, construction of relevance networks and functional classification of gene groups. Moreover, the method for construction of relevance networks was revised and improved and an statistical model was proposed and implemented for the functional classification of gene regulation networks. The last two procedures was born from biological problems for which adequate data analysis methods didn?t exist in the literature. Finally, we presented two datasets that were evaluated using several data analysis procedures available in this computational environment.

A presente proposta correlaciona como o investimento direto estrangeiro pode, e deve, promover o desenvolvimento sustentável no país que o acolhe. O investimento direto estrangeiro é capaz de promover uma série de vantagens competitivas quando aplicado de forma coerente como: ganhos de tecnologia, geração de empregos, capacitação de mão de obra e outros benefícios que vão além do econômico. No entanto, há a necessidade de uma mensuração para que a promoção do desenvolvimento gerado se dê de forma sustentável, para que os benefícios obtidos para a nação sejam maiores do que a degradação ambiental, emissão de poluentes e os impactos sociais causados. Utilizando um referencial sobre o investimento direto estrangeiro e desenvolvimento sustentável, o trabalho consiste em verificar se o investimento direto estrangeiro promove o desenvolvimento sustentável. Para isso, uma construção foi feita a partir de dados secundários que pudessem verificar a latência dos constructos de sustentabilidade e assim relacioná-los com o investimento direto estrangeiro com a divisão em setor primário, secundário e terciário. Com essas correlações foi possível verificar como o investimento tem impactado não apenas na economia nacional mas também qual impacto ambiental e social ele trouxe. Posteriormente, uma análise de cluster e discriminante foram feitas com o intuito de agrupar e classificar os impactos do investimento direto estrangeiro utilizando a poupança líquida ajustada, que é um indicador de sustentabilidade promovido pelo Banco Mundial. Essa construção foi possível através das técnicas de análise multivariada de dados que permitiram a relação de variáveis de diferentes categorias e se mostrou adequada para pesquisas de carácter exploratório. As evidências provenientes da discussão desse trabalho contribuem com a recente literatura que busca por estudos que relacionem o investimento direto estrangeiro e o desenvolvimento que eles promovem, melhorando assim a tomada de decisão na captura desses recursos. O trabalho contribui em verificar a possível falta de políticas públicas que integrem as dimensões de desenvolvimento sustentável. Também são apresentadas algumas variáveis que podem auxiliar na busca pelo desenvolvimento sustentável. / The present work aims to highlight the need to correlate how foreign direct investment can, and should, promote sustainable development in the country that hosts it. Foreign direct investment is able to promote a number of competitive advantages when applied consistently such as gains in technology, job creation, training of manpower and other benefits that go beyond the economic level. However, a measurement is necessary so that the promotion of development generated can be satisfactory and thus fulfill the purpose of everyone involved with this financial, environmental and social capital which was invested, so environmental degradation, emissions, incentives offered and social impacts are no greater than the benefits for the nation. By using a reference framework on foreign direct investment and sustainable development, this work aims to formulate hypotheses so this investment can be measured and be considered sustainable. In order to do this, a construction from secondary data to verify the latency of the constructs of sustainability will be made enabling to relate them to foreign direct investment in every sector nationwide. With these correlations will be possible to verify how the investment has impacted not only in the national economy but which environmental and social impact it has brought. Later, a cluster analysis and discriminant will be carried out enabling to group and classify the impacts of foreign direct investment using the adjusted net saving, which is an indicator of sustainability promoted by the World Bank. This construction will be possible through techniques of multivariate data analysis, allowing the relationship of variables of different categories, which is adequate for an exploratory research. The evidences arising from the discussion of this study contribute to the recent literature that searches for studies that relate foreign direct investment and development they promote, thereby improving decision making in the capture of these resources. The study aims to verify the possible lack of public policies that promote sustainable development dimensions. Some variables are also presented which may also contribute to the search for sustainable development.

Em muitos trabalhos científicos, é comum encontrar os dados estruturados de forma hierarquica, ou seja, os indivíduos em estudo estão agrupados em unidades de nível mais baixo, que por sua vez pertencem a unidades de um nível mais alto e assim sucessivamente. Na análise desse tipo de dados é importante levar em conta a estrutura hierarquica uma vez que, não faze-la, pode implicar na superestimação dos coecientes do modelo em estudo. Assim, para facilitar a análise de dados seguindo uma estrutura hierarquica, foram desenvolvidos os modelos multiníveis. Tais modelos levam em conta toda a variabilidade existente para os dados num mesmo nível como nos diferentes níveis da hierarquia. No caso da análise de dados de medidas repetidas no tempo, uma estrutura hierarquica em dois níveis pode ser considerada, organizando as ocasiões de medidas, no primeiro nível, para cada indivíduo no segundo nível. Neste trabalho, é feita uma abordagem dos modelos multiníveis para vários níveis da hierarquia bem como os métodos de estimação e teste dos parâmetros envolvidos no modelo. Como aplicação, foram analisados dados provenientes do Programa de Atenção ao Idoso (PAI), desenvolvido no ambulatório municipal Dr. Plinio do Prado Coutinho em Alfenas, M.G., em que foram observadas as variáveis Indice de Massa Corporea (imc) e Pressão Arterial dos idosos durante 22 meses. Também, foram analisados dados referentes ao teor de proteína no leite de 79 vacas australianas, coletados durante 19 semanas após o parto e submetidas a três dietas (Diggle et al., 1994). Para os dados do "PAI", foi possível verificar que as diferentes medidas de pressão arterial estão relacionadas positivamente com o imcao longo do tempo, independente de sexo, idade e estado civil. Já nos dados relativos ao teor de proteína no leite, notou-se uma redução do teor de proteína no leite ao longo do tempo, independente dos tratamentos aplicados. Foram utilizados os softwares MLwiN e SAS para a realização das análises. / It is common to and data structured in a hierarchical form in several scientific works, that is, the studied subjects are nested in the lowest level unites, that belong to the highest level unites, and so on. To analyze these sort of data it is important to take in account the hierarchical structure once, if does not do it, the coeficients can be overestimated in the studied model. Then, in order to become easier the data analysis according to the hierarchical structure, multilevel models were developed. Such models take into account all the existing variability for the data at the same level as well as in diferent levels of the hierarchy. In the case of repeated measure data, a two levels hierarchical structure can be considered, organizing the occasions at the first level for each subject at the second level. In this work, na approach of the multilevel models for several levels are made as well as the estimation methods and the tests for the involved parameters in the model. As an application, data from the Elderly Care Program (ECP), developed at outpatient clinic Dr. Plinio do Prado Coutinho at Alfenas, M.G., where the Body Mass Index and the Bloody Pressure were observed from elderly people for 22 months. Also, it was analyzed the milk protein content of 79 australian cows during 19 weeks after calving and subject to three diets (Diggle et al., 1994). For the data of the ECP it was possible to observe that the bloody pressure are positively related to the occasions, independently of sex, race and marital status. For the data form the milk protein content, a reduce in the content in the occasions even after the diets are included. MLwiN and SAS softwares were used to run the analysis.

Abstract This thesis explores the use of assistive in-situ technologies for formal caregivers in nursing homes. More specifically, focus is placed on improving context awareness and medication management. Although these topics have previously been researched for elderly care in general, few solutions targeting nursing homes have been generated. As the aging population further increases the burden on this care environment, it is important that solutions are found to help maintain care quality. The main findings in this thesis emphasise how technology can assist formal caregivers and facilitate increased patient wellbeing. The articles presented in this thesis describe our creation of a context-aware sensor system (named CARE) and a non-expert miniaturised near-infrared spectroscopy (MNIRS) solution. Both systems were designed iteratively with the help of nurses and were evaluated in a nursing home. CARE quantifies elderly residents’ behaviour, analyses the resulting data and produces valuable and actionable insights for nurses. Results from a two-month-long user study demonstrate that the system can facilitate increased awareness of patients’ needs and enhance care service. The custom MNIRS solution allows nurses to scan pharmaceuticals and obtain accurate identifications. This method significantly outperforms currently available tools in nursing homes and represents a promising solution that can reduce medication mismanagement. In the discussion section of the thesis, we revisit the research questions defined in the introduction and examine how each were answered. In addition, we discuss the augmentation of nursing home technology and various stakeholders’ perspectives. We then highlight how the work covered in this thesis was conducted in collaboration with industry and offer some conclusions, limitations and reflections. / Tiivistelmä Tämä väitöstyö tutkii paikkasidonnaisten teknologioiden käyttöä hoitajien työn helpottamiseksi vanhusten palvelukodeissa. Työn keskiössä on erityisesti kontekstitietoisuuden lisääminen ja lääkehoidon valvonta. Näitä aiheita on tutkittu laajalti aiemminkin, mutta aitoihin ympäristöihin keskittyviä ratkaisuja on vielä vain vähän. Väestön ikääntyminen aiheuttaa haasteita vanhustenhoidossa, ja siksi on tärkeää kehittää ratkaisuja hoidon laadun ylläpitoa varten. Väitöstyön löydökset painottavat teknologian roolia hoitajien avustajana sekä hoidettavien hyvinvoinnin ylläpitäjänä. Työn artikkelit kuvailevat kontekstitietoisen järjestelmän (CARE) koko kehitys- ja elinkaaren sekä lähi-infrapunaspektroskopiaan perustuvan ratkaisun lääkehoidon prosessien parantamiseksi. Molemmat järjestelmät kehitettiin iteratiivisesti hoitajien avulla ja koestettiin aidossa ympäristössä vanhainkodissa. CARE analysoi asiakkaiden liikkeitä ja toimintoja sekä visualisoi niistä korkeamman tason tietoa hoitajille. Kahden kuukauden kenttäkokeen tuloksena voidaan todeta, että järjestelmät yhdessä voivat auttaa hoitajia ymmärtämään asiakkaiden tarpeita sekä parantamaan hoidon laatua. Lähi-infrapunaspektroskopiaan perustuvalla kannettavalla ratkaisulla puolestaan hoitajat voivat varmistaa lääkehoidon oikeellisuuden. Tämä menetelmä on tarkempi ja parempi kuin tämänhetkiset käytössä olevat ratkaisut lääkkeiden oikeaksi toteamiseen. Väitöstyön keskusteluosuus palaa tutkimuskysymyksiin ja selventää, kuinka tehty työ ja saavutetut tulokset vastaavat niihin. Lisäksi keskustelu antaa yleiskuvan eri osapuolien näkemyksistä kehitetyn ratkaisun hyödyistä ja sen soveltuvuudesta käytännön työhön. Lopuksi väitöstyö luo katsauksen yhteistyön rooliin eri osa-alueiden toteuttamisessa ja esittää kriittisen näkökulman työn puutteisiin sekä yhteenvedon.

L'émergence du phénomène Big Data a créé un besoin grandissant en analyse de données, mais, bien souvent, cette analyse est conduite par des experts de différents domaines ayant peu d'expérience en science des données. On s'intéresse donc à ce besoin d'assistance à l'analyse de données, qui commence tout juste à recevoir une certaine attention des communautés scientifiques, donnant naissance au domaine de la méta-analyse. Les premières approches du sujet se révélant souvent similaires et peu abouties, on tente en particulier de permettre de nouvelles approches de méta-analyse pour adresser ce problème d'assistance à l'analyse de données. Pour ce faire, une première étape cruciale est de déterminer ce qu'est une méta-analyse performante, aucun standard n'ayant encore été établi dans ce domaine relativement neuf. On propose ainsi un cadre générique d'évaluation de méta-analyse, permettant de comparer et caractériser finement diverses techniques de méta- analyse. Ensuite, afin d'ouvrir de nouvelles voies, on s'intéresse à un verrou majeur de la méta-analyse : la caractérisation de jeu de données. On propose et évalue alors une caractérisation par dissimilarité faisant usage de toute l'information disponible pour autoriser de nouvelles approches de méta-analyse. L'utilisation de cette caractérisation par dissimilarité permettant de recommander facilement des processus d'analyse de données complets, on décrit enfin les nouvelles approches de méta-analyses rendues possibles, ainsi que les processus afférents d'assistance à l'analyse de données. / The emergence of the big data phenomenon has led to increasing demands in data analysis, which most often are conducted by other domains experts with little experience in data science. We then consider this important demand in intelligent assistance to data analysis, which receives an increasing attention from the scientific community. The first takes on the subject often possessing similar shortcomings, we propose to address it through new processes of meta-analysis. No evaluation standard having yet been set in this relatively new domain, we first propose a meta-analysis evaluation framework that will allow us to test and compare the developed methods. In order to open new approaches of meta-analysis, we then consider one of its recurring issue: dataset characterization. We then propose and evaluate such a characterization, consisting in a dissimilarity between datasets making use of a precise topological description to compare them. This dissimilarity allows a new meta-analysis approach producing recommendations of complete data analysis processes, which we then evaluate on a proof of concept. We thus detail the proposed methods of meta-analysis, and the associated process of assistance to data analysis.

Two dimensional (2D) materials with interesting fundamental physics and potential applications attract tremendous efforts to study. The versatile properties of 2D materials can be further tailored by tuning the electronic structure with the layer-stacking arrangement, of which the main adjustable parameters include the thickness and the in-plane twist angle between layers. The Angle-Resolved Photoemission Spectroscopy (ARPES) has become a canonical tool to study the electronic structure of crystalline materials. The recent development of ARPES with sub-micrometre spatial resolution (micro-ARPES) has made it possible to study the electronic structure of materials with mesoscopic domains. In this thesis, we use micro-ARPES to investigate the spatially-resolved electronic structure of a series of few-layer materials: 1. We explore the electronic structure of the domains with different number of layers in few-layer graphene on copper substrate. We observe a layer- dependent substrate doping effect in which the Fermi surface of graphene shifts with the increase of number of layers, which is then explained by a multilayer effective capacitor model. 2. We systematically study the twist angle evolution of the energy band of twisted few-layer graphene over a wide range of twist angles (from 5° to 31°). We directly observe van Hove Singularities (vHSs) in twisted bilayer graphene with wide tunable energy range over 2 eV. In addition, the formation of multiple vHSs (at different binding energies) is observed in trilayer graphene. The large tuning range of vHS binding energy in twisted few-layer graphene provides a promising material base for optoelectrical applications with broad-band wavelength selectivity. 3. To better extract the energy band features from ARPES data, we propose a new method with a convolutional neural network (CNN) that achieves comparable or better results than traditional derivative based methods. Besides ARPES study, this thesis also includes the study of surface reconstruction for the layered material Bi2O2Se with the analysis of Scanning Tunnelling Microscopy (STM) images. To explain the origin of the pattern, we propose a tile model that produces the identical statistics with the experiment.

Sustainable development (SD) is a pressing global issue that is becoming increasingly prominent on clients and governing bodies agendas. In order to survive, organisations are seeking ways to negate their detrimental environmental impacts. This is no easy feat: SD is both complex and dynamic. To be successful, organisations need to leverage and expand their most valuable asset – knowledge. Civil engineering plays a significant role in SD – it shapes our environment and governs our interaction with it. However, extant research asserts that civil engineering related disciplines have been slow to adopt SD oriented practices; a possible result of their complex and fragmented organisational environments. The literature suggests that effective knowledge sharing (KS) can overcome these barriers, thus driving enhanced SD performance. Consequently, this research aims to investigate how the civil engineering sector can improve its intra-organisational sharing of SD knowledge, using an international civil engineering consultancy as an exemplar. Whilst there has been much research surrounding KS and SD there has been limited research that has investigated KS for SD, thus this thesis contributes to this limited body of knowledge. Mixed-method research was used to address the abovementioned aim. An increasingly popular approach, it is widely believed to generate greater value through complementary integration of quantitative and qualitative research paradigms. This approach lends itself also to the ethnographic inclinations of the reported research: the author was embedded within the case organisation, and sought a rich and reliable understanding of the study phenomena. An initial set of semi-structured interviews suggested that the case organisation’s members exhibit positive attitudes towards KS and SD, yet are often constrained by a number of common KS barriers, namely: a lack of organisation slack (i.e. time); a silo mentality; and poor SD ICT systems. These socio-cultural and technical barriers were subsequently investigated and contested using social network analysis techniques and an intranet acceptance model. A number of observations are made on the relationships between the findings from the research activities. It is believed the organisation often exhibits a reactive approach to KS for SD, which is deemed undesirable. This signals the need for greater senior management support to cultivate a culture where KS for SD is the norm and is integrated with work practices. A series of recommendations are provided to help the case organisation understand how such change could be cultivated. Several implications follow from this work. The mixed-method approach revealed a number of contradictions between the findings of each research activity. It is therefore postulated that mixed-method designs can provide a richer understanding, thus reducing misconceptions of KS phenomena. Following from this, the research contends that it may be too easy for researchers to identify with ubiquitous KS barriers as the reported research suggests that these may be perceived rather than actual. The research also reinforces the need for senior management support. These individuals govern the systems in which organisational members operate and thus have the ability to enhance KS for SD. Finally, the research demonstrates that SD ICT systems have little impact unless they are embedded in receptive contexts. Thus, an action research approach to KS system development is advocated to ensure systems are shaped to meet user expectations and drive desired KS behaviours. This research is presented in five peer-reviewed articles.

P-values combination procedure for multiple statistical tests is a common data analysis method in many applications including bioinformatics. However, this procedure is nontrivial when input P-values are dependent. For the Fisher€™s combination procedure, a classic method is the Brown€™s Strategy [1, Brown,1975], which is based empirical moment-matching of gamma distribution. In this project, we address a more general family of weighting-andtruncation p-value combination procedures called TFisher. We first study how to extend Brown€™s Strategy to this problem. Then we make further development in two directions. First, instead of using the empirical polynomial model-fitting strategy to find moments, we developed an analytical calculation strategy based on asymptotic approximation. Second, instead of using the gamma distribution to approximate the null distribution of TFisher, we propose to use a mixed gamma distribution or a shifted-mixed gamma distribution. We focus on calculating the one-sided p-value for TFisher, especially the soft-thresholding version of TFisher. Simulations show that our methods much improve the accuracy than the traditional strategy.

This thesis presents a contribution to the active research area of functional data analysis (FDA) and is concerned with the analysis of data from complex experimental designs in which the responses are curves. High resolution, closely correlated data sets are encountered in many research fields, but current statistical methodologies often analyse simplistic summary measures and therefore limit the completeness and accuracy of conclusions drawn. Specifically the nature of the curves and experimental design are not taken into account. Mathematically, such curves can be modelled either as sample paths of a stochastic process or as random elements in a Hilbert space. Despite this more complex type of response, the structure of experiments which yield functional data is often the same as in classical experimentation. Thus, classical experimental design principles and results can be adapted to the FDA setting. More specifically, we are interested in the functional analysis of variance (ANOVA) of experiments which use orthogonal designs. Most of the existing functional ANOVA approaches consider only completely randomised designs. However, we are interested in more complex experimental arrangements such as, for example, split-plot and row-column designs. Similar to univariate responses, such complex designs imply that the response curves for different observational units are correlated. We use the design to derive a functional mixed-effects model and adapt the classical projection approach in order to derive the functional ANOVA. As a main result, we derive new functional F tests for hypotheses about treatment effects in the appropriate strata of the design. The approximate null distribution of these tests is derived by applying the Karhunen- Lo`eve expansion to the covariance functions in the relevant strata. These results extend existing work on functional F tests for completely randomised designs. The methodology developed in the thesis has wide applicability. In particular, we consider novel applications of functional F tests to gait analysis. Results are presented for two empirical studies. In the first study, gait data of patients with cerebral palsy were collected during barefoot walking and walking with ankle-foot orthoses. The effects of ankle-foot orthoses are assessed by functional F tests and compared with pointwise F tests and the traditional univariate repeated-measurements ANOVA. The second study is a designed experiment in which a split-plot design was used to collect gait data from healthy subjects. This is commonly done in gait research in order to better understand, for example, the effects of orthoses while avoiding confounded analysis from the high variability observed in abnormal gait. Moreover, from a technical point of view the study may be regarded as a real-world alternative to simulation studies. By using healthy individuals it is possible to collect data which are in better agreement with the underlying model assumptions. The penultimate chapter of the thesis presents a qualitative study with clinical experts to investigate the utility of gait analysis for the management of cerebral palsy. We explore potential pathways by which the statistical analyses in the thesis might influence patient outcomes. The thesis has six chapters. After describing motivation and introduction in Chapter 1, mathematical representations of functional data are presented in Chapter 2. Chapter 3 considers orthogonal designs in the context of functional data analysis. New functional F tests for complex designs are derived in Chapter 4 and applied in two gait studies. Chapter 5 is devoted to a qualitative study. The thesis concludes with a discussion which details the extent to which the research question has been addressed, the limitations of the work and the degree to which it has been answered.