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Dissertations / Theses on the topic 'Medical statistics'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Wong, Sik-kwan Francis. "Outcome of a web-based statistic laboratory for teaching and learning of medical statistics." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43251687.

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2

Raner, Max. "On logistic regression and a medical application." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-420680.

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3

Hua, Hairui. "Survival modelling in mathematical and medical statistics." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5808/.

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An essential aspect of survival analysis is the estimation and prediction of survival probabilities for individuals. For this purpose, mathematical modelling of the hazard rate function is a fundamental issue. This thesis focuses on the novel estimation and application of hazard rate functions in mathematical and medical research. In mathematical research we focus on the development of a semiparametric kernel-based estimate of hazard rate function and a L\(_1\) error optimal kernel hazard rate estimate. In medical research we concentrate on the development and validation of survival models using individual participant data from multiple studies. We also consider how to fit survival models that predict individual response to treatment effectiveness, given IPD from multiple trials.

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4

Buchan, Iain Edward. "The development of a statistical computer software resource for medical research." Thesis, University of Liverpool, 2000. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:71360.

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Medical research is often weakened by poor statistical practice, and inappropriate use of statistical computer software is part of this problem. The statistical knowledge that medical researchers require has traditionally been gained in both dedicated and ad hoc learning time, often separate from the research processes in which the statistical methods are applied. Computer software, however, can be written to flexibly support statistical practice. The work of this thesis was to explore the possibility of, and if possible, to create, a resource supporting medical researchers in statistical knowledge and calculation at the point of need. The work was carried out over eleven years, and was directed towards the medical research community in general. Statistical and Software Engineering methods were used to produce a unified statistical computational and knowledge support resource. Mathematically and computationally robust approaches to statistical methods were continually sought from current literature. The type of evaluation undertaken was formative; this included monitoring uptake of the software and feedback from its users, comparisons with other software, reviews in peer reviewed publications, and testing of results against classical and reference data. Large-scale opportunistic feedback from users of this resource was employed in its continuous improvement. The software resulting from the work of this thesis is provided herein as supportive evidence. Results of applying the software to classical reference data are shown in the written thesis. The scope and presentation of statistical methods are considered in a comparison of the software with common statistical software resources. This comparison showed that the software written for this thesis more closely matched statistical methods commonly used in medical research, and contained more statistical knowledge support materials. Up to October 31st 2000, uptake of the software was recorded for 5621 separate instances by individuals or institutions. The development has been self-sustaining. Medical researchers need to have sufficient statistical understanding, just as statistical researchers need to sufficiently understand the nature of data. Statistical software tools may damage statistical practice if they distract attention from statistical goals and tasks, onto the tools themselves. The work of this thesis provides a practical computing framework supporting statistical knowledge and calculation in medical research. This work has shown that sustainable software can be engineered to improve statistical appreciation and practice in ways that are beyond the reach of traditional medical statistical education.

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5

黃式鈞 and Sik-kwan Francis Wong. "Outcome of a web-based statistic laboratory for teaching and learning of medical statistics." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43251687.

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6

Sonesson, Christian. "On statistical surveillance issues of optimality and medical applications /." Göteborg, Sweden : Stockholm : Statistical Research Unit, Göteborg University ; Almqvist & Wiksell International, 2003. http://catalog.hathitrust.org/api/volumes/oclc/53500706.html.

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7

Coupal, Louis. "The EM algorithm : an overview with applications to medical data." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=56644.

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Owing to their complex design and use of live subjects as experimental units, missing or incomplete data is common place in medical experiments. The great increase in difficulty of maximum likelihood based analysis of incomplete data experiments compared to a similar complete data analysis encourages many medical researchers to ignore cases with missing data in favour of performing a "complete" cases analysis.
The expectation maximization algorithm (EM for short) is often an easily implemented algorithm that provides estimates of parameters in models with missing data. The EM algorithm unifies the theory of maximum likelihood estimation in the context of "missing" data. The general problem of missing data also includes structurally unobservable quantities such as parameters, hyperparameters and latent variables. The nature of its defining steps, the expectation or E-step and the maximization or M-step, gives the user intuitive understanding of the maximization process.
In this Thesis, the EM algorithm is first illustrated through an example borrowed from the field of genetics. The theory of the EM algorithm is formally developed and the special case of exponential families is considered. Issues concerning convergence and inference are discussed. Many examples taken from the medical literature serve to highlight the method's broad spectrum of application in both missing data and unobservable parameter problems.

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8

Walker, Stephen Graham. "Bayesian parametric and nonparametric methods with applications in medical statistics." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307519.

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9

Tom, Brian Dermot Ming. "Modelling event-history data in the context of medical statistics." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624771.

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10

Joubert, Georgina. "Variable selection in logistic regression, with special application to medical data." Master's thesis, University of Cape Town, 1994. http://hdl.handle.net/11427/17006.

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Bibliography: pages 121-126.
In this thesis, the various methods of variable selection which have been proposed in the statistical, epidemiological and medical literature for prediction and estimation problems in logistic regression will be described. The procedures will be applied to medical data sets. On the basis of the literature review as well as the applications to examples, strengths and weaknesses of the approaches will be identified. The procedures will be compared on the basis of the results obtained, their appropriateness for the specific aim of the analysis, and demands they place on the analyst and researcher, intellectually and computationally. In particular, certain selection procedures using bootstrap samples, which have not been used before, will be investigated, and the partial Gauss discrepancy will be extended to the case of logistic regression. Recommendations will be made as to which approaches are the most suitable or most practical in different situations. Most statistical texts deal with issues regarding prediction, whereas the epidemiological literature focuses on estimation. It is therefore hoped that the thesis will be a useful reference for those, statistically or epidemiologically trained, who have to deal with issues regarding variable selection in logistic regression. When fitting models in general, and logistic regression models in particular, it is standard practice to determine the goodness of fit of models, and to ascertain whether outliers or influential observations are present in a data set. These aspects will not be discussed in this thesis, although they were considered when fitting the models.

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11

Yang, Li. "A comparison of unsupervised learning techniques for detection of medical abuse in automobile claims." California State University, Long Beach, 2013.

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12

Partlett, Christopher. "Asymmetry and other distributional properties in medical research data." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/6348/.

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The central theme of this thesis is to investigate the use of non-parametric methods for making inferences about a random sample with an unknown distribution function. The overarching aim is the development of new methods to make inferences regarding the nature of the unknown distribution to enhance medical research. Initially,the focus is exclusively on the asymmetry of a random variable. In particular, a recently proposed measure of asymmetry provides the foundation for the proposal and development of a new test for symmetry. The potential applications of the test and measure are applied to a number of medical research settings including randomised trials. Moreover, guidance is provided on its implementation, with particular emphasis on the problem of small sample estimation. This investigation is then generalised to examine asymmetry across multiple studies. In particular, meta-analysis methods are used to synthesise information about the amount of asymmetry in several studies. Further, a detailed simulation study is carried out to investigate the impact of asymmetry on linear models and meta-analyses of randomised trials, in terms of the accuracy of the treatment effect estimate and the coverage of confidence and prediction intervals. Finally, the scope of the investigation is widened to encompass the problem of comparing and synthesising information about the probability density function and cumulative distribution function, based on samples from multiple studies. The meta-analysis of the smooth distribution function estimate is then applied to propose new methods for conducting meta-analyses of diagnostic test accuracy, which have a number of merits compared to the existing methodology.

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13

Machin, David. "Statistical aspects of clinical trials." Thesis, University of Southampton, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.257667.

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14

Reeves, John A. F. "Longitudinal regression models for a study of age-related macular degeneration." Thesis, Keele University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267456.

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15

Morris, Andrew Paul. "Transmission tests of linkage and association using samples of nuclear families with at least one affected child." Thesis, University of Reading, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267416.

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16

Ekangaki, Abie. "An assessment of vaginal bleeding disturbances in women from different cultural groups using different contraceptive methods." Thesis, University of Southampton, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259504.

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17

Hsieh, Jui-Ying. "The Split Analysis for Multiple-Reader Multiple-Case Split-Plot Studies." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10813369.

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One pathway for a new device to gain access to the marketplace requires demonstration that it is equivalent to, or substantially better than, a legally marketed device. To evaluate the equivalence of a medical imaging device, we propose measuring the intra- or inter-reader agreement in a reader study, where the clinicians (readers) make diagnoses on the medical images (cases) using both the new and old imaging devices. Such an endpoint, as well as its variance estimate, enable us to make a statistical inference on the equivalence of two devices. A method for multiple-reader multiple-case agreement analysis was presented in Gallas et al. (2016) for fully-crossed study designs, where every reader reads every case. In practice, having every reader read every case may be impossible when readers have a limited amount of time to participate in the study. One alternative study design is the split-plot study design, where both the readers and the cases are partitioned into a fixed number of groups, and each group of readers reads its own group of cases. In this thesis, we adapt the multiple-reader multiple-case agreement analysis method in Gallas et al. (2016) to analyze split-plot study designs, and propose a new variance estimator based on splitting the analysis across the groups. In each split sub-study, we compute an estimate, and then combine these estimates to obtain the final estimate for the full study. Our numerical studies show that the "split-analysis" variance estimator provides more accurate estimation of the variance of concordance measurements than the full-study-based method for unbalanced split-plot study designs.

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18

嚴嘉文. "中藥製劑處方與藥效的統計分析研究 : 婦科." HKBU Institutional Repository, 2011. http://repository.hkbu.edu.hk/etd_ra/1325.

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19

Smith, Nicole Thomas. "Validation of criteria used to predict warfarin dosing decisions /." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd427.pdf.

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20

Chiu, Jing-Er. "Applications of bayesian methods to arthritis research /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3036813.

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21

Kettermann, Anna. "Estimation of Standardized Mortality Ratio in Geographic Epidemiology." Fogler Library, University of Maine, 2004. http://www.library.umaine.edu/theses/pdf/KettermanA2004.pdf.

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22

Gordon, Kerry. "Modelling and monitoring of medical time series." Thesis, University of Nottingham, 1986. http://eprints.nottingham.ac.uk/12369/.

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In this thesis we examine several extensions to the dynamic linear model framework, outlined by Harrison and Stevens (1976), in order to adapt these models for use in the on-line analysis of medical time series that arise from routine clinical settings. The situation with which we are most concerned is that where we are monitoring individual patients and wish to detect abrupt changes in the patient's condition as soon as possible. A detailed background to the study and application of dynamic linear models is given, and other techniques for time series monitoring are also discussed when appropriate. We present a selection of specific models that we feel may prove to be of practical use in the modelling and monitoring of medical time series, and we illustrate how these models may be utilized in order to distinguish between a variety of alternative changepoint-types. The sensitivity of these models to the specification of prior information is examined in detail. The medical background to the time series examined requires the development of models and techniques enabling us to analyze generally unequally-spaced time series. We test the performance of the resulting models and techniques using simulated data. We then attempt to build a framework for bivariate time series modelling, allowing, once more, for the possibility of unequally spaced data. In particular, we suggest mechanisms whereby causality and feedback may be introduced into such models. Finally, we report on several applications of this methodology to actual medical time series arising in various contexts including kidney and bone-marrow transplantation and foetal heart monitoring.

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23

Dragset, Ingrid Garli. "Analysis of Longitudinal Data with Missing Values. : Methods and Applications in Medical Statistics." Thesis, Norwegian University of Science and Technology, Department of Mathematical Sciences, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9945.

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Missing data is a concept used to describe the values that are, for some reason, not observed in datasets. Most standard analysis methods are not feasible for datasets with missing values. The methods handling missing data may result in biased and/or imprecise estimates if methods are not appropriate. It is therefore important to employ suitable methods when analyzing such data. Cardiac surgery is a procedure suitable for patients suffering from different types of heart diseases. It is a physical and psychical demanding surgical operation for the patients, although the mortality rate is low. Health-related quality of life (HRQOL) is a popular and widespread measurement tool to monitor the overall situation of patients undergoing cardiac surgery, especially in elderly patients with naturally limited life expectancies [Gjeilo, 2009]. There has been a growing attention to possible differences between men and women with respect to HRQOL after cardiac surgery. The literature is not consistent regarding this topic. Gjeilo et al. [2008] studied HRQOL in patients before and after cardiac surgery with emphasis on differences between men and women. In the period from September 2004 to September 2005, 534 patients undergoing cardiac surgery at St Olavs Hospital were included in the study. HRQOL were measured by the self-reported questionnaires Short-Form 36 (SF-36) and the Brief Pain Inventory (BPI) before surgery and at six and twelve months follow-up. The SF-36 reflects health-related quality of life measuring eight conceptual domains of health [Loge and Kaasa, 1998]. Some of the patients have not responded to all questions, and there are missing values in the records for about 41% of the patients. Women have more missing values than men at all time points. The statistical analyses performed in Gjeilo et al. [2008] employ the complete-case method, which is the most common method to handle missing data until recent years. The complete-case method discards all subjects with unobserved data prior to the analyses. It makes standard statistical analyses accessible and is the default method to handle missing data in several statistical software packages. The complete-case method gives correct estimates only if data are missing completely at random without any relation to other observed or unobserved measurements. This assumption is seldom met, and violations can result in incorrect estimates and decreased efficiency. The focus of this paper is on improved methods to handle missing values in longitudinal data, that is observations of the same subjects at multiple occasions. Multiple imputation and imputation by expectation maximization are general methods that can be applied with many standard analysis methods and several missing data situations. Regression models can also give correct estimates and are available for longitudinal data. In this paper we present the theory of these approaches and application to the dataset introduced above. The results are compared to the complete-case analyses published in Gjeilo et al. [2008], and the methods are discussed with respect to their properties of handling missing values in this setting. The data of patients undergoing cardiac surgery are analyzed in Gjeilo et al. [2008] with respect to gender differences at each of the measurement occasions; Presurgery, six months, and twelve months after the operation. This is done by a two-sample Student's t-test assuming unequal variances. All patients observed at the relevant occasion is included in the analyses. Repeated measures ANOVA are used to determine gender differences in the evolution of the HRQOL-variables. Only patients with fully observed measurements at all three occasions are included in the ANOVA. The methods of expectation maximization (EM) and multiple imputation (MI) are used to obtain plausible complete datasets including all patients. EM gives a single imputed dataset that can be analyzed similar to the complete-case analysis. MI gives multiple imputed datasets where all dataset must be analyzed sepearately and their estimates combined according to a technique called Rubin's rules. Results of both Student's t-tests and repeated measures ANOVA can be performed by these imputation methods. The repeated measures ANOVA can be expressed as a regression equation that describes the HRQOL-score improvement in time and the variation between subjects. The mixed regression models (MRM) are known to model longitudinal data with non-responses, and can further be extended from the repeated measures ANOVA to fit data more sufficiently. Several MRM are fitted to the data of cardiac surgery patients to display their properties and advantages over ANOVA. These models are alternatives to the imputation analyses when the aim is to determine gender differences in improvement of HRQOL after surgery. The imputation methods and mixed regression models are assumed to handle missing data in an adequate way, and gives similar analysis results for all methods. These results differ from the complete-case method results for some of the HRQOL-variables when examining the gender differences in improvement of HRQOL after surgery.

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24

Jannetta, Adrian. "Advanced deconvolution techniques and medical radiography." Thesis, Northumbria University, 2005. http://nrl.northumbria.ac.uk/164/.

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Medical radiography is a process by which the internal structures of the human body are imaged using a source of x-rays. The images formed are essentially shadowgrams whose size and intensity is dependent on the geometry of the imaging system and the degree to which the structures attenuate x-ray radiation. The images are blurred because the x-ray source has a finite size, and noisy because the x-ray exposure must be kept as low as possible for the safety of the patient but which also limits the number of photons available for image formation. In such noisy environments traditional methods of Fourier deconvolution have limited appeal. In this research we apply maximum entropy methods (MEM) to some radiological images. We justify the choice of MEM over other deconvolution schemes by processing a selection of artificial images in which the blur and noise mimic the real situation but whose levels are known a priori. A hybrid MEM scheme is developed to address the shortcomings of so-called historic MEM in these situations. We initially consider images from situations in which the model point- spread function is assumed to be three-dimensionally spatially invariant, and which approximates the real situation reasonably well. One technique lends itself well to this investigation: magnification mammography. MEM is offered as a way of breaking some of the conflicting performance requirements of this technique and we explore several new system possibilities with a working MEM system in place. A more complicated blurring function is encountered in linear tomography, which uses opposing movements of the image receptor and x-ray source to generate planar images through an object. Features outside a particular focal plane are smeared to such an extent that detail within the focal plane can be very difficult to detect. With appropriate modification of our MEM technique, processed images show a significant reduction to the blurring outside the focal plane.

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25

Sithole, Jabulani S. "Longitudinal data models for evaluating change in prescribing patterns." Thesis, Keele University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327702.

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26

Woods, Tonya M. "Extracting meaningful statistics for the characterization and classification of biological, medical, and financial data." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53857.

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This thesis is focused on extracting meaningful statistics for the characterization and classification of biological, medical, and financial data and contains four chapters. The first chapter contains theoretical background on scaling and wavelets, which supports the work in chapters two and three. In the second chapter, we outline a methodology for representing sequences of DNA nucleotides as numeric matrices in order to analytically investigate important structural characteristics of DNA. This methodology involves assigning unit vectors to nucleotides, placing the vectors into columns of a matrix, and accumulating across the rows of this matrix. Transcribing the DNA in this way allows us to compute the 2-D wavelet transformation and assess regularity characteristics of the sequence via the slope of the wavelet spectra. In addition to computing a global slope measure for a sequence, we can apply our methodology for overlapping sections of nucleotides to obtain an evolutionary slope. In the third chapter, we describe various ways wavelet-based scaling may be used for cancer diagnostics. There were nearly half of a million new cases of ovarian, breast, and lung cancer in the United States last year. Breast and lung cancer have highest prevalence, while ovarian cancer has the lowest survival rate of the three. Early detection is critical for all of these diseases, but substantial obstacles to early detection exist in each case. In this work, we use wavelet-based scaling on metabolic data and radiography images in order to produce meaningful features to be used in classifying cases and controls. Computer-aided detection (CAD) algorithms for detecting lung and breast cancer often focus on select features in an image and make a priori assumptions about the nature of a nodule or a mass. In contrast, our approach to analyzing breast and lung images captures information contained in the background tissue of images as well as information about specific features and makes no such a priori assumptions. In the fourth chapter, we investigate the value of social media data in building commercial default and activity credit models. We use random forest modeling, which has been shown in many instances to achieve better predictive accuracy than logistic regression in modeling credit data. This result is of interest, as some entities are beginning to build credit scores based on this type of publicly available online data alone. Our work has shown that the addition of social media data does not provide any improvement in model accuracy over the bureau only models. However, the social media data on its own does have some limited predictive power.

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27

Eklund, Anders. "Computational Medical Image Analysis : With a Focus on Real-Time fMRI and Non-Parametric Statistics." Doctoral thesis, Linköpings universitet, Medicinsk informatik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-76120.

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Functional magnetic resonance imaging (fMRI) is a prime example of multi-disciplinary research. Without the beautiful physics of MRI, there wouldnot be any images to look at in the first place. To obtain images of goodquality, it is necessary to fully understand the concepts of the frequencydomain. The analysis of fMRI data requires understanding of signal pro-cessing, statistics and knowledge about the anatomy and function of thehuman brain. The resulting brain activity maps are used by physicians,neurologists, psychologists and behaviourists, in order to plan surgery andto increase their understanding of how the brain works. This thesis presents methods for real-time fMRI and non-parametric fMRIanalysis. Real-time fMRI places high demands on the signal processing,as all the calculations have to be made in real-time in complex situations.Real-time fMRI can, for example, be used for interactive brain mapping.Another possibility is to change the stimulus that is given to the subject, inreal-time, such that the brain and the computer can work together to solvea given task, yielding a brain computer interface (BCI). Non-parametricfMRI analysis, for example, concerns the problem of calculating signifi-cance thresholds and p-values for test statistics without a parametric nulldistribution. Two BCIs are presented in this thesis. In the first BCI, the subject wasable to balance a virtual inverted pendulum by thinking of activating theleft or right hand or resting. In the second BCI, the subject in the MRscanner was able to communicate with a person outside the MR scanner,through a virtual keyboard. A graphics processing unit (GPU) implementation of a random permuta-tion test for single subject fMRI analysis is also presented. The randompermutation test is used to calculate significance thresholds and p-values forfMRI analysis by canonical correlation analysis (CCA), and to investigatethe correctness of standard parametric approaches. The random permuta-tion test was verified by using 10 000 noise datasets and 1484 resting statefMRI datasets. The random permutation test is also used for a non-localCCA approach to fMRI analysis.

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28

Zhang, Lin Tubbs Jack Dale. "Semiparametric AUC regression for testing treatment effect in clinical trial." Waco, Tex. : Baylor University, 2008. http://hdl.handle.net/2104/5237.

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29

Southey, Richard. "Bayesian hierarchical modelling with application in spatial epidemiology." Thesis, Rhodes University, 2018. http://hdl.handle.net/10962/59489.

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Disease mapping and spatial statistics have become an important part of modern day statistics and have increased in popularity as the methods and techniques have evolved. The application of disease mapping is not only confined to the analysis of diseases as other applications of disease mapping can be found in Econometric and financial disciplines. This thesis will consider two data sets. These are the Georgia oral cancer 2004 data set and the South African acute pericarditis 2014 data set. The Georgia data set will be used to assess the hyperprior sensitivity of the precision for the uncorrelated heterogeneity and correlated heterogeneity components in a convolution model. The correlated heterogeneity will be modelled by a conditional autoregressive prior distribution and the uncorrelated heterogeneity will be modelled with a zero mean Gaussian prior distribution. The sensitivity analysis will be performed using three models with conjugate, Jeffreys' and a fixed parameter prior for the hyperprior distribution of the precision for the uncorrelated heterogeneity component. A simulation study will be done to compare four prior distributions which will be the conjugate, Jeffreys', probability matching and divergence priors. The three models will be fitted in WinBUGS® using a Bayesian approach. The results of the three models will be in the form of disease maps, figures and tables. The results show that the hyperprior of the precision for the uncorrelated heterogeneity and correlated heterogeneity components are sensitive to changes and will result in different results depending on the specification of the hyperprior distribution of the precision for the two components in the model. The South African data set will be used to examine whether there is a difference between the proper conditional autoregressive prior and intrinsic conditional autoregressive prior for the correlated heterogeneity component in a convolution model. Two models will be fitted in WinBUGS® for this comparison. Both the hyperpriors of the precision for the uncorrelated heterogeneity and correlated heterogeneity components will be modelled using a Jeffreys' prior distribution. The results show that there is no significant difference between the results of the model with a proper conditional autoregressive prior and intrinsic conditional autoregressive prior for the South African data, although there are a few disadvantages of using a proper conditional autoregressive prior for the correlated heterogeneity which will be stated in the conclusion.

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Huitfeldt, Anders. "Emulation of Target Trials to Study the Effectiveness and Safety of Medical Interventions." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:23205172.

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Ideally, clinical guidelines would be informed by well-designed randomized experiments. However, it is generally not possible to conduct a randomized trial for every clinically relevant decision. Decision makers therefore often have to rely on observational data. Guidelines that rely on observational data due to the absence of randomized trials benefit when the analysis mimics the analysis of a hypothetical target trial. This can be achieved by explicitly formulating the protocol of the target trial, and thoroughly discussing the feasibility of the conditions that must be met in order to validly emulate the target trial using observational data. In chapter one, we discuss the emulation of trials that compare the effects of different timing strategies, that is, strategies that vary the frequency of delivery of a medical intervention or procedures, and provide an application to surveillance for colorectal cancer. In chapter two, we discuss a study design that attempts to avoid bias by comparing initiators of the treatment of interest with initiators of an “active comparator” that is believed to be inactive for the outcome, in order to emulate a randomized trial that compares the treatment of interest with an inactive comparator. In chapter three, we describe a new method that combines randomized trial data and external information to emulate a different target trial. We apply this method to a randomized trial of postmenopausal hormone therapy in order to emulate a trial of a joint intervention on hormone therapy and statin therapy.

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31

Bai, Yan. "A Bayesian approach to detect the onset of activity limitation among adults in NHIS." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050605-155002/.

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32

Xu, Peiheng 1965. "The effect of utilizing spatial information for brain image segmentation /." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81458.

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This thesis addresses several brain MRI segmentation methods including three methods of using normal distributions, similar methods using t-distributions and a new method using MCLUST software packages. The main purpose of this thesis is to try to improve current brain image segmentation methods and reduce the long computing time with satisfactory results. The methodology consists in applying histogram analysis for the initialization of parameters, using Simpson's rule for the approximation of numerical integration and describing methods of skull stripping and neighborhood information encoding. The two most significant contributions are suggestions for speeding up current methods and a newly proposed method that ignores spatial information for parameter estimation. Potential future work is proposed at the end.

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33

Chapman, Joanne Shirley. "Statistical methods for gamma mixtures of proportional hazards survival models." Thesis, Lancaster University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340567.

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Gouda, Hebe Naomi. "Events and their consequences : choosing metrics in population health assessments." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609370.

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35

Prieto, Bernal Juan Carlos. "Multiparametric organ modeling for shape statistics and simulation procedures." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0010/document.

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La modélisation géométrique a été l'un des sujets les plus étudiés pour la représentation des structures anatomiques dans le domaine médical. Aujourd'hui, il n'y a toujours pas de méthode bien établie pour modéliser la forme d'un organe. Cependant, il y a plusieurs types d'approches disponibles et chaque approche a ses forces et ses faiblesses. La plupart des méthodes de pointe utilisent uniquement l'information surfacique mais un besoin croissant de modéliser l'information volumique des objets apparaît. En plus de la description géométrique, il faut pouvoir différencier les objets d'une population selon leur forme. Cela nécessite de disposer des statistiques sur la forme dans organe dans une population donné. Dans ce travail de thèse, on utilise une représentation capable de modéliser les caractéristiques surfaciques et internes d'un objet. La représentation choisie (s-rep) a en plus l'avantage de permettre de déterminer les statistiques de forme pour une population d'objets. En s'appuyant sur cette représentation, une procédure pour modéliser le cortex cérébral humain est proposée. Cette nouvelle modélisation offre de nouvelles possibilités pour analyser les lésions corticales et calculer des statistiques de forme sur le cortex. La deuxième partie de ce travail propose une méthodologie pour décrire de manière paramétrique l'intérieur d'un objet. La méthode est flexible et peut améliorer l'aspect visuel ou la description des propriétés physiques d'un objet. La modélisation géométrique enrichie avec des paramètres physiques volumiques est utilisée pour la simulation d'image par résonance magnétique pour produire des simulations plus réalistes. Cette approche de simulation d'images est validée en analysant le comportement et les performances des méthodes de segmentations classiquement utilisées pour traiter des images réelles du cerveau
Geometric modeling has been one of the most researched areas in the medical domain. Today, there is not a well established methodology to model the shape of an organ. There are many approaches available and each one of them have different strengths and weaknesses. Most state of the art methods to model shape use surface information only. There is an increasing need for techniques to support volumetric information. Besides shape characterization, a technique to differentiate objects by shape is needed. This requires computing statistics on shape. The current challenge of research in life sciences is to create models to represent the surface, the interior of an object, and give statistical differences based on shape. In this work, we use a technique for shape modeling that is able to model surface and internal features, and is suited to compute shape statistics. Using this technique (s-rep), a procedure to model the human cerebral cortex is proposed. This novel representation offers new possibilities to analyze cortical lesions and compute shape statistics on the cortex. The second part of this work proposes a methodology to parameterize the interior of an object. The method is flexible and can enhance the visual aspect or the description of physical properties of an object. The geometric modeling enhanced with physical parameters is used to produce simulated magnetic resonance images. This image simulation approach is validated by analyzing the behavior and performance of classic segmentation algorithms for real images

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Грабовий, С. Л. "Інструментарій медичної статистики для ефективного публічного управління у сфері протидії ВІЛ-інфекції." Master's thesis, Сумський державний університет, 2021. https://essuir.sumdu.edu.ua/handle/123456789/86955.

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У роботі наведено огляд основних існуючих на сьогодні у сфері протидії ВІЛ-інфекції методів епідеміологічного аналізу. Охарактеризовано сучасний стан системи епідеміологічного нагляду за ВІЛ-інфекцією в Україні за компонентами сероепідеміологічного моніторингу (діагностичний компонент), реєстрації випадків ВІЛ-інфекції/СНІДу та смерті ВІЛ-позитивних осіб від усіх причин. Синхронізовані з загальноприйнятою світовою практикою визначення основних статистичних понять. Оновлено перелік статистичних показників для здійснення аналізу епідситуації з ВІЛ-інфекції в Україні. Запропоновані для застосування на практиці показники тягаря хвороб, наведена покрокова методологія їх розрахунку для використання в діяльності лікарів закладів, що надають медичну допомогу ВІЛ-позитивним особам. Адаптовані для використання в Україні показники епідеміологічного переходу.

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Bashet, AbuZafar. "Effects of Student-Created Question Process on Learning Biomedical Statistics in a Specialized Master's in Medical Sciences." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984186/.

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This study explored the effectiveness of a student question creation process engaging students actively in self, peer, and instructor interaction in development of affective, cognitive, and meta-cognitive skills. Employing a mixed-methods sequential explanatory design assigning both treatment and control activities sequentially in an alternating pattern over a six week period, students' performance on exams as well as their perceptions of various aspects of the student question creation process were used to evaluate the effectiveness of student-created questions (SCQs) activities as a cognitive strategy and to identify factors contributing to the effectiveness of question creation activities on students' learning. Subjects of this study were high performing and highly motivated graduate students in an 8-week online biomedical statistics course, part of a specialized master's program designed for medical school preparation. Survey findings and focus groups strongly supported the student question creation process as a facilitator of higher order thinking. However, the relatively short study duration, comparison of student question creation with another competing method for facilitating learning (discussion board) and not a pure control group, and availability of a common study guide course with student-created questions on all course topics may have muted assessment of the full impact of the strategy on learning. Although practically difficult in an education environment, further research to assess fully the impact of the student question creation strategy is desirable especially if these confounding factors can be greatly minimized, if not eliminated.

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Henderson, Neil James Kerr. "Extending the clinical and economic evaluations of a randomised controlled trial the IONA study /." Connect to e-thesis, 2008. http://theses.gla.ac.uk/418/.

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Thesis (Ph.D.) - University of Glasgow, 2008.
Ph.D. thesis submitted to the Department of Statistics, Faculty of Information and Mathematical Sciences, University of Glasgow, 2008. Includes bibliographical references. Print version also available.

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Kiri, V. A. "Studies of survival data using variable metric optimisation methods : Applications of survivor models in the area of industrial medical and social sciences, using software designed to exploit the practical merits of recent optimisation alogrithms." Thesis, University of Bradford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380629.

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Moldovan, Andreea-Loredana. "Socio-economic disparities in science knowledge, biomedical self-efficacy, and public participation in medical decision-making." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/21632/.

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The thesis consists of three self-contained articles that empirically investigate socio-economic differences in, and interrelationships amongst, science knowledge, biomedical self-efficacy, and participation in medical decision-making. Chapter 2 investigates age-related bias in the science knowledge questions in the Wellcome Trust Monitor Survey Waves I and II. It also examines what evidence there is for three dimensions of knowledge. Chapter 3 studies the influence of Internet use and paying attention to medical stories online in reducing science knowledge and biomedical self-efficacy gaps between low and high educational groups. Wave II of the Wellcome Trust Monitor Surveys is employed in this chapter. Chapter 4 scrutinises the influence of various socio-economic factors, biomedical self-efficacy, and trust in physicians and other medical practitioners on public willingness and confidence to take part in the medical decision-making process. Chapter 4 uses Wave III of the Wellcome Trust Monitor Survey. Chapter 2 finds evidence for age-related bias in the science knowledge battery of questions; no evidence of a misinformed group of respondents was found; a group who consistently said they didn’t know instead of providing an answer that was wrong was found; a sensitivity analysis showed that using the summed score approach leads to the same substantive conclusions as a model taking into account age-related non-invariance. Chapter 3 finds evidence of education-based knowledge and efficacy gaps. It also finds some evidence that the Internet can help reduce that democratic deficit in information. Chapter 4 finds evidence that people are generally confident to participate. Those who are more self-efficacious are also more confident to participate in medical decisions. The opposite held true for those who place high trust in doctors. Women were found to be more confident than men.

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Lee, Sally Hung-Hsin. "Use of the two-stage procedure for analysis of cross-over trials in four aspects of medical statistics." Thesis, University College London (University of London), 2006. http://discovery.ucl.ac.uk/1444951/.

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The two-stage procedure had been used as a standard method to analyse cross-over trials for many years before its major deficiency was found. The inflated type I error rate of the two-stage procedure indicates that there have been more trials which have produced false positive results than originally believed. Because of the 24 years gap between the introduction of the method and the publishing of its deficiency, it is conceivable that the impact of the change in the perception about the validity of the two-stage procedure might not have taken effect overnight. The objective of this thesis is to examine the impact of the change in the perception about the validity of the two-stage procedure on four different aspects of medical statistics. The areas of medical statistics include both applications of, and references to, the analysis of cross-over trials to give a full picture of the use of the two-stage procedure. Methods used are citation analysis for all scientific journals, systematic review for medical journals, comprehensive review for general medical statistics books and questionnaire survey for the pharmaceutical industry. The results have been inconclusive in terms of the estimation of how prevalently the two-stage procedure has been used. However, the four studies demonstrated that the analysis of cross-over trials is often associated with the two-stage procedure while the deficiency of the two-stage procedure has not been generally acknowledged. It can be concluded that further understanding of Use of the two-stage procedure for analysis of cross-over trials in four aspects of medical statistics the two-stage procedure and better references in the analysis of cross-over trials are needed in all four areas of medical statistics.

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Holm, Hansen Christian. "Analysis of routinely collected repeated patient outcomes." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9556.

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Clinical practice should be based on the best available evidence. Ideally such evidence is obtained through rigorously conducted, purpose-designed clinical studies such as randomised controlled trials and prospective cohort studies. However gathering information in this way requires a massive effort, can be prohibitively expensive, is time consuming, and may not always be ethical or practicable. When answers are needed urgently and purpose-designed prospective studies are not feasible, retrospective healthcare data may offer the best evidence there is. But can we rely on analysis with such data to give us meaningful answers? The current thesis studies this question through analysis with repeated psychological symptom screening data that were routinely collected from over 20,000 outpatients who attended selected oncology clinics in Scotland. Linked to patients’ oncology records these data offer a unique opportunity to study the progress of distress symptoms on an unprecedented scale in this population. However, the limitations to such routinely collected observational healthcare data are many. We approach the analysis within a missing data context and develop a Bayesian model in WinBUGS to estimate the posterior predictive distribution for the incomplete longitudinal response and covariate data under both Missing At Random and Missing Not At Random mechanisms and use this model to generate multiply imputed datasets for further frequentist analysis. Additional to the routinely collected screening data we also present a purpose-designed, prospective cohort study of distress symptoms in the same cancer outpatient population. This study collected distress outcome scores from enrolled patients at regular intervals and with very little missing data. Consequently it contained many of the features that were lacking in the routinely collected screening data and provided a useful contrast, offering an insight into how the screening data might have been were it not for the limitations. We evaluate the extent to which it was possible to reproduce the clinical study results with the analysis of the observational screening data. Lastly, using the modelling strategy previously developed we analyse the abundant screening data to estimate the prevalence of depression in a cancer outpatient population and the associations with demographic and clinical characteristics, thereby addressing important clinical research questions that have not been adequately studied elsewhere. The thesis concludes that analysis with observational healthcare data can potentially be advanced considerably with the use of flexible and innovative modelling techniques now made practicable with modern computing power.

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Sangaramoorthy, Thurka. "We all have AIDS: Circulations of risk, race, and statistics in HIV/AIDS prevention." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3311350.

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Thesis (Ph.D.)--University of California, San Francisco with the University of California, Berkeley, 2008.
Source: Dissertation Abstracts International, Volume: 69-06, Section: A, page: 2336. Adviser: Charles L. Briggs.

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Wang, Xiaofeng. "New Procedures for Data Mining and Measurement Error Models with Medical Imaging Applications." Case Western Reserve University School of Graduate Studies / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=case1121447716.

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Majeke, Lunga. "Preliminary investigation into estimating eye disease incidence rate from age specific prevalence data." Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/464.

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This study presents the methodology for estimating the incidence rate from the age specific prevalence data of three different eye diseases. We consider both situations where the mortality may differ from one person to another, with and without the disease. The method used was developed by Marvin J. Podgor for estimating incidence rate from prevalence data. It delves into the application of logistic regression to obtain the smoothed prevalence rates that helps in obtaining incidence rate. The study concluded that the use of logistic regression can produce a meaningful model, and the incidence rates of these diseases were not affected by the assumption of differential mortality.

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Yang, Kaolee. "A Statistical Analysis of Medical Data for Breast Cancer and Chronic Kidney Disease." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1587052897029939.

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Drymoussis, Michael. "Globalisation and commercialisation of healthcare services : with reference to the United States and United Kingdom." Thesis, University of Sussex, 2014. http://sro.sussex.ac.uk/id/eprint/61483/.

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The thesis seeks to interrogate historically the relationship between multinational healthcare service companies and states in the pursuit of market-oriented reforms for healthcare. It constitutes a critical reading of the idea of globalisation as a concept with substantive explanatory value to analyse the causal role of multinational service firms in a commercial transformation in national healthcare service sectors. It analyses the development and expansion of commercial (for-profit) healthcare service provision and financing in the healthcare systems of OECD countries. The hospital and health insurance sectors in the US and UK are analysed as case studies towards developing this critical reading from a more specific national setting. The thesis contributes to developing a framework for analysing the emergence of an international market for trade in healthcare services, which is a recently emerging area of research in the social sciences. As such, it uses an interdisciplinary approach, utilising insights from health policy and international political economy. The research entails a longitudinal study of secondary and primary sources of qualitative data broadly covering the period 1975-2005. I have also made extensive use of quantitative data to illustrate key economic trends that are relevant to the changes in the particular healthcare services sectors analysed. The research finds a substantive shift in the mixed economy of healthcare in which commercial healthcare service provision and financing are increasing. However, while the internationalisation of healthcare service firms is a key element in helping to drive some of this change, the changes are ultimately highly dependent on state-level decision making and regulation. In this context, the thesis argues that globalisation presents an inadequate and potentially misleading conceptual framework for analysing these changes without a historical grounding in the particular developments of national and international markets for healthcare services.

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Barker, Jolene. "APPLICATIONS OF THE BIVARIATE GAMMA DISTRIBUTION IN NUTRITIONAL EPIDEMIOLOGY AND MEDICAL PHYSICS." VCU Scholars Compass, 2008. http://scholarscompass.vcu.edu/etd/1623.

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In this thesis the utility of a bivariate gamma distribution is explored. In the field of nutritional epidemiology a nutrition density transformation is used to reduce collinearity. This phenomenon will be shown to result due to the independent variables following a bivariate gamma model. In the field of radiation oncology paired comparison of variances is often performed. The bivariate gamma model is also appropriate for fitting correlated variances. A method for simulating bivariate gamma random variables is presented. This method is used to generate data from several bivariate gamma models and the asymptotic properties of a test statistic, suggested for the radiation oncology application, is studied.

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Rivas, Cruz Manuel A. "Medical relevance and functional consequences of protein truncating variants." Thesis, University of Oxford, 2015. http://ora.ox.ac.uk/objects/uuid:a042ca18-7b35-4a62-aef0-e3ba2e8795f7.

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Genome-wide association studies have greatly improved our understanding of the contribution of common variants to the genetic architecture of complex traits. However, two major limitations have been highlighted. First, common variant associations typically do not identify the causal variant and/or the gene that it is exerting its effect on to influence a trait. Second, common variant associations usually consist of variants with small effects. As a consequence, it is more challenging to harness their translational impact. Association studies of rare variants and complex traits may be able to help address these limitations. Empirical population genetic data shows that deleterious variants are rare. More specifically, there is a very strong depletion of common protein truncating variants (PTVs, commonly referred to as loss-of-function variants) in the genome, a group of variants that have been shown to have large effect on gene function, are enriched for severe disease-causing mutations, but in other instances may actually be protective against disease. This thesis is divided into three parts dedicated to the study of protein truncating variants, their medical relevance, and their functional consequences. First, I present statistical, bioinformatic, and computational methods developed for the study of protein truncating variants and their association to complex traits, and their functional consequences. Second, I present application of the methods to a number of case-control and quantitative trait studies discovering new variants and genes associated to breast and ovarian cancer, type 1 diabetes, lipids, and metabolic traits measured with NMR spectroscopy. Third, I present work on improving annotation of protein truncating variants by studying their functional consequences. Taken together, these results highlight the utility of interrogating protein truncating variants in medical and functional genomic studies.

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Hernandez, Andres M. "Spatial Modeling of the Social Health Determinants Impact on the Epidemiology of Diseases in Low-, Middle-, and High-income Settings." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613686108382205.

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