Ett diagrams syfte är att förenkla och förmedla en datamängd och dess innebörd. Hur kan man på bästa sätt presentera en datamängd och vilka faktorer spelar roll vid val av diagramtyp? Studien kommer undersöka dessa frågor, samt att utreda för Marknads- information ABs räkning hur deras arbetssätt med att generera diagram med Microsoft Excel kan förbättras och förenklas för deras specifika önskemål genom att skapa en applikation för det ändamålet.  För att utreda studiens frågeställningar har en litteraturstudie genomförts, vi har även genomfört en empirisk studie om vad som är viktigt vid skapandet av diagram för kunden bland dess anställda, information som sedan står till grund för den tekniska implementation som skapats. Efter färdigställandet av den tekniska implementationen har en användarundersökning utförts för att examinera dess funktionalitet.  Det finns delade meningar om vilka diagram som bör användas till olika datamängder. Diagram visas vara bra för att visa trender överskådligt men saknar detaljrikedomen hos en tabell. Den applikation som skapats för att generera diagram efter kundens önskemål uppskattas av företaget och fyller de behov som eftersöktes.  Det finns skilda teorier om vilket diagram som lämpar sig bäst för att presentera en datamängd, och det finns olika vägar att gå beroende på föredraget utfall. För vår kund är färgsättning och överskådlighet av största vikt vid skapandet av diagram. Tillhörande text är mindre viktigt, diagrammet i sig ska kunna tala sitt tydliga språk. Då studiens omfattning är begränsat inom en organisation kan inga generella slutsatser dras av studiens resultat då testgruppen inte representerar en hel population. / The purpose of a diagram is to simplify and convey a dataset and its meaning. How does one best present a dataset, and which factors play a role when choosing a type of diagram? This study will investigate these questions. We will examine how Marknads- information AB’s work procedures in generating diagrams with Microsoft Excel can be improved and simplified for their specific needs by creating an application for its purpose.  To examine the questions of the report a literary study has been conducted. We have examined amongst the customer's employees what is important for them when creating diagrams. This information was subsequently the basis for the technical implemen- tation. Following the completion of the technical implementation, a user survey has been performed to examine its functionality.  There are conflicting opinions on what diagrams should be used for different types of datasets. Diagrams have proven to be superior when it comes to clarity but lack the richness of detail that a table possesses. The application created to generate diagrams according to the customer's requests is appreciated by the company and meets the required targets.  For the customer of this thesis, the color scheme and clarity of a diagram are of most importance, with formatting and text fields being of less importance. As the extent of the thesis is limited within the customer's organization, the answers of the thesis can not be generalized.

Neonatal abstinence syndrome (NAS) is a syndrome of withdrawal symptoms in newborn infants that have a history of prenatal exposure to certain substances. Affected infants may have gastrointestinal (GI) issues, such as gassiness and diarrhea. Although infants with known exposures may be monitored in the first few days of life, it is unclear how long these symptoms persist. This poster will examine GI issues in the first six months of life across four groups of infants: those with prenatal opioid exposure, those with prenatal substance exposure that does not include opioids, those with polysubstance exposure, and those without substance exposure in a pediatric clinic in northeast TN. A retrospective chart review of 600 charts of infants born from 2017—2020 was conducted with IRB approval in a pediatric clinic in rural middle Appalachia. Of these, 300 charts were selected based on known prenatal substance exposure, and the other 300 charts were randomly selected. A REDCap extraction manual was created, research assistants were trained, and % agreement was determined. Data was collected about type of prenatal substance exposure, growth, and medical conditions in the first three years of life. Infants were divided into groups by type of prenatal substance exposure for analysis. The opioid-only group included exposure to buprenorphine, methadone, or other opiates. The other (non-opioid) exposure group included exposure to marijuana, cocaine, benzodiazepines, methamphetamines, and prescription ADHD medications. The polysubstance exposure group included exposure to both opiate and non-opiate substances. The control group had no prenatal substance exposure. Analyses were performed using SAS version 9.4. Descriptive statistics showed the demographics of the sample were representative of the population in rural middle Appalachia, with a predominantly Caucasian sample of 121 females and 123 males, mostly receiving TennCare. Chi-square results showed there was only a statistically significant difference between the prenatal substance exposure groups at 2 months, X2 (3, N = 176) = 8.03, p = 0.045, but not at hospital discharge, within the first few days of life, at 1 month, 4 months, or 6 months. Infants in the opioid-only exposure group were most likely to have GI issues. These findings suggest that GI issues are more likely to occur in infants with certain prenatal substance exposures. This poster also shows a longitudinal perspective of these issues, indicating that the symptoms may persist in the first few months of life. Thus, caregivers of infants at risk for NAS may benefit with information about the long-term effects. Because the retrospective chart review is still in progress, this poster only analyzes a preliminary number of charts. Future research should also take into consideration other factors that may be associated with GI issues in this population, such as nutrition.

Our objective is to monitor the changes in a proportion with correlated binary observations. All of the published work on this subject used the first-order Markov chain model for the data. Increasing the order of dependence above one by extending a standard Markov chain model entails an exponential increase of both the number of parameters and the dimension of the transition probability matrix. In this dissertation, we develop a particular Markov chain structure, the Multilevel Model (MLM), to model the correlation between binary data. The basic idea is to assign a lower probability to observing a 1 when all previous correlated observations are 0's, and a higher probability to observing a 1 as the last observed 1 gets closer to the current observation. We refer to each of the distinct situations of observing a 1 as a "level". For a given order of dependence, , at most different values of conditional probabilities of observing a 1 can be assigned. So the number of levels is always less than or equal to . Compared to a direct extension of the first-order Markov model to higher orders, our model is considerably parsimonious. The number of parameters for the MLM is only one plus the number of levels, and the transition probability matrix is . We construct a CUSUM control chart for monitoring a proportion with correlated binary observations. First, we use the probability structure of a first-order Markov chain to derive a log-likelihood ratio based CUSUM control statistic. Then, we model this CUSUM statistic itself as a Markov chain, which in turn allows for designing a control chart with specified statistical properties: the Markov Binary CUSUM (MBCUSUM) chart. We generalize the MBCUSUM to account for any order of dependence between binary observations through implying MLM to the data and to our CUSUM control statistic. We verify that the MBCUSUM has a better performance than a curtailed Shewhart chart. Also, we show that except for extremely large changes in the proportion (of interest) the MBCUSUM control chart detects the changes faster than the Bernoulli CUSUM control chart, which is designed for independent observations. / Ph. D.

We consider two applications of control charts in health care. The first involves the comparison of four methods designed to detect an increase in the incidence rate of a rare health event, such as a congenital malformation. A number of methods have been proposed: among these are the Sets method, two modifications of the Sets method, and the CUSUM method based on the Poisson distribution. Many of the previously published comparisons of these methods used unrealistic assumptions or ignored implicit assumptions which led to misleading conclusions. We consider the situation where data are observed as a sequence of Bernoulli trials and propose the Bernoulli CUSUM chart as a desirable method for the surveillance of rare health events. We compare the steady-state average run length performance of the Sets methods and its modifications to the Bernoulli CUSUM chart under a wide variety of circumstances. Except in a very few instances we find that the Bernoulli CUSUM chart performs better than the Sets method and its modifications for the extensive number of cases considered. The second application area involves monitoring clinical outcomes, which requires accounting for the fact that each patient has a different risk of death prior to undergoing a health care procedure. We propose a risk-adjusted survival time CUSUM chart (RAST CUSUM) for monitoring clinical outcomes where the primary endpoint is a continuous, time-to-event variable that is right censored. Risk adjustment is accomplished using accelerated failure time regression models. We compare the average run length performance of the RAST CUSUM chart to the risk-adjusted Bernoulli CUSUM chart, using data from cardiac surgeries to motivate the details of the comparison. The comparisons show that the RAST CUSUM chart is more efficient at detecting deterioration in the quality of a clinical procedure than the risk-adjusted Bernoulli CUSUM chart, especially when the fraction of censored observations is not too high. We address details regarding the implementation of a prospective monitoring scheme using the RAST CUSUM chart. / Ph. D.

Patients with myelodysplastic syndromes (MDS) frequently receive red blood cell (RBC) transfusions to alleviate symptoms of anemia and improve health-related quality of life (HR-QoL). Patients can sometimes continue to feel unwell after transfusion and the age of the transfused RBCs could contribute to this observation. Three pilot studies were conducted to inform the design of a randomized crossover trial to determine if fresh blood to MDS patients could improve HR-QoL post-transfusion. A systematic review was performed to inform the background and rationale for the trial. The results showed a dearth of literature addressing the research question. Only two clinical trials have been conducted to date where fatigue and HR-QoL were the primary outcomes of interest. Although results of the trials were negative, several limitations and generalizability issues warrant additional research in this area. Crossover designs necessitate patients have a stable prognosis while being observed; hence, a chart review of adult MDS patients was conducted to assess clinical stability using the following criteria: interval of days between transfusions; pre-transfusion Hb; number of hospital admissions; and severe infections. Results indicated that the majority of patients who had received greater than 3 transfusions within the 6-month observation period had stable disease and were appropriate for a crossover trial. The criteria defining stability will be useful for identifying eligible patients. Finally, an applied qualitative study in adult MDS patients in Hamilton was conducted to inform the selection of an appropriate outcome measure (i.e. HR- QoL tool). Short semi-structured interviews were conducted with participants to elicit information about anemia related symptoms and changes in well-being in response to transfusion. The results of the study support clinical observations that suggest patients do not immediately recover post-transfusion. Findings indicate that an appropriate HR-QoL tool should be short, be disease specific, and have a short recall period. Currently, the Quality of Life-E tool, validated in patients with MDS, fits most of these criteria. In conclusion, data from the systematic review and the two pilot studies suggest that it may be feasible to conduct an age of blood crossover trial in MDS patients where the primary outcome of interest is HR-QoL. / Thesis / Master of Science (MSc)

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No description available.

Simply by reading data and statistics of the charting positions of popular songs on global and national music charts, it is hard to understand how the popularity of songs, albums, or artists within pop music truly behave over time. However, analyzing the data using visualizations as means of communication might provide us with new points of view and new insights into how the popularity of contemporary popular music behaves over a longer period. This is the hypothesis that we intend to investigate in this thesis. An interactive visualization application (presented as a website) has been developed based on data from “Daily Top 200” lists provided by Spotify. A survey was then used to evaluate the application, with the results suggesting that new and interesting insights into the trends in the popularity of music can be gained from the proposed prototype.

Anxiety has become one of the common problems in society in recent years. As an emerging interactive medium, games can create a first-hand experience for players. Therefore, it is possible to guide the player through behavioral experiments implemented with the game. But in order to reduce the direct damage to the player and make the problem more obvious, metaphorical game is one of the good choices.   In order to design and make such a metaphorical game, I firstly need to collect anxiety triggers and game design related theories into an initial design framework. These theories mainly include metaphorical game, experiential game model and reflection game design. After two iterations of game design core development, I'll be doing demos and interviews with several players. After that, I will summarize these data into several themes. These themes will extend the original design framework, which will also serve as an outcome of this paper. The two most prominent points in the expansion are beat chart and reward.

We examine some of the methodologies implemented by the Centers for Disease Control and Prevention's (CDC) BioSense program. The program uses data from hospitals and public health departments to detect outbreaks using the Early Aberration Reporting System (EARS). The EARS method W2 allows one to monitor syndrome counts (W2count) from each source and the proportion of counts of a particular syndrome relative to the total number of visits (W2rate). We investigate the performance of the W2r method designed using an empiric recurrence interval (RI) in this dissertation research. An adaptive threshold monitoring method is introduced based on fitting sample data to the underlying distributions, then converting the current value to a Z-score through a p-value. We compare the upper thresholds on the Z-scores required to obtain given values of the recurrence interval for different sets of parameter values. We then simulate one-week outbreaks in our data and calculate the proportion of times these methods correctly signal an outbreak using Shewhart and exponentially weighted moving average (EWMA) charts. Our results indicate the adaptive threshold method gives more consistent statistical performance across different parameter sets and amounts of baseline historical data used for computing the statistics. For the power analysis, the EWMA chart is superior to its Shewhart counterpart in nearly all cases, and the adaptive threshold method tends to outperform the W2 rate method. Two modified W2r methods proposed in the dissertation also tend to outperform the W2r method in terms of the RI threshold functions and in the power analysis. / Ph. D.