This project analyzed the giving data of Worcester Polytechnic Institute's alumni and other constituents (parents, friends, neighbors, etc.) from fiscal year 1983 to 2007 using a two-stage modeling approach. Logistic regression analysis was conducted in the first stage to predict the likelihood of giving for each constituent, followed by linear regression method in the second stage which was used to predict the amount of contribution to be expected from each contributor. Box-Cox transformation was performed in the linear regression phase to ensure the assumption underlying the model holds. Due to the nature of the data, multiple imputation was performed on the missing information to validate generalization of the models to a broader population. Concepts from the field of direct and database marketing, like "score" and "lift", were also introduced in this report.

This project uses multiple linear regression to predict the value of Major League Baseball free agent contracts, inspired by the low volume of published research on this topic. I found one published paper that shared my research goal but its predictive power needed improvement. An in depth comparison of our models is carried out with k-fold cross validation mean square prediction error being used as the main standard. The predictor variables considered in my models were related to performance evaluation and position, and the response variable was inflation-adjusted average annual value of the contract. The result of the project is two linear regression models, one for hitters and one for pitchers.

<p>Regression testing plays an important role during the software development life-cycle,especially during maintenance, it provides confidence that the modified parts of softwarebehave as intended and the unchanged parts have no affect by the modification. Regressiontest selection is used to select test cases from the test suites which have been used to test theprevious version of the software. In this thesis, we extend the traditional definition of a testcase with a log file, containing information of which events that occurred when the test casewas last executed. Based on the contents of this log file, we propose a method of regressiontest selection for multi-tasking real-time systems, able to determine which parts of softwarethat have not been affected by the modification. Therefore, the test cases designed for theunchanged parts do not need to be re-tested.</p>

<p><strong>Målsättning</strong><strong></strong></p><p>Att utreda skillnader i tillgänglighet till insulinpump mellan olika patientgrupper samt vad som orsakar ett byte till insulinpump.</p><p><strong>Metod</strong><strong></strong></p><p>Data från 7224 individer med typ 1 diabetes vid tio olika vårdenheter analyserades för att utreda effekterna av njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration samt ålder. Jämförelsen mellan patientgrupper utfördes med logistisk regression som en tvärsnittsstudie och Cox-regression för att utreda vad som föregått ett byte till pump.</p><p><strong>Resultat</strong><strong></strong></p><p>Genom logistisk regression erhölls en bild av hur skillnader mellan patienter som använder insulinpump och patienter som inte gör det ser ut i dagsläget. Cox-regressionen tar med ett tidsperspektiv och ger på så sätt svar på vad som föregått ett byte till insulinpump. Dessa analyser gav liknande resultat gällande variabler konstanta över tiden. Kvinnor använder pump i större utsträckning än män och andelen pumpanvändare skiljer sig åt vid olika vårdenheter. I dagsläget visar sig hög ålder sänka sannolikheten att använda insulinpump, vilket bekräftas vid den tidsberoende studien som visade hur sannolikheten att byta till pump är avsevärt lägre vid hög ålder. Långtidsblodsockret har också tydlig effekt på sannolikheten att gå över till pump där ett högt långtidsblodsocker medför hög sannolikhet att byta till insulinpump.</p><p><strong>Slutsatser</strong><strong></strong></p><p>I dagsläget finns det skillnader i andelen insulinpumpanvändare mellan olika patientgrupper och skillnader finns även i de olika gruppernas benägenhet att byta från andra insulinbehandlingar till insulinpump. Beroende av patienters njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration och ålder har dessa olika sannolikheter att byta till insulinpump.<strong></strong></p>

The LSH-study started in 2003 at the department of Health and Society at the University of Linköping. The purpose of the study was to examine the relationship between life condition, stress and health. A total of 1007 people from ten different health centres in Östergötlands län participated. At the follow up, a couple of years later, 795 of the 1007 participated. 127 of the 212 in the attrition turned down the follow up, twelve people were not invited (for example in case of death) and the rest did not respond at all. The purpose of this paper is to find out in what degree the attrition in the follow up can be predicted using the information from the first survey and which variables are important. The differences between different types of attrition have also been examined. Simple and multiple bi- and multinomial logistic regression have been used in the analysis. In total 34 variables were examined and in the final model six variables remained with a significant relation to the attrition. High BMI, regular smoking, high pulse and lack of daily exercise at the first survey were connected to a higher risk for an individual to not participate at the follow up. It is interesting that these factors are considered as risk factors for unhealthy living. Other factors related to a higher attrition were unemployment in the last year before the first survey and if the individual had parents born in another country than Sweden. The risk for attrition increased gradually when more risk factors were shown by the individual. The factors contributing an individual to turn down the follow up instead of not responding at all was if he or she were in the older age segments in the survey or if they were not active in any type of association.

Målsättning Att utreda skillnader i tillgänglighet till insulinpump mellan olika patientgrupper samt vad som orsakar ett byte till insulinpump. Metod Data från 7224 individer med typ 1 diabetes vid tio olika vårdenheter analyserades för att utreda effekterna av njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration samt ålder. Jämförelsen mellan patientgrupper utfördes med logistisk regression som en tvärsnittsstudie och Cox-regression för att utreda vad som föregått ett byte till pump. Resultat Genom logistisk regression erhölls en bild av hur skillnader mellan patienter som använder insulinpump och patienter som inte gör det ser ut i dagsläget. Cox-regressionen tar med ett tidsperspektiv och ger på så sätt svar på vad som föregått ett byte till insulinpump. Dessa analyser gav liknande resultat gällande variabler konstanta över tiden. Kvinnor använder pump i större utsträckning än män och andelen pumpanvändare skiljer sig åt vid olika vårdenheter. I dagsläget visar sig hög ålder sänka sannolikheten att använda insulinpump, vilket bekräftas vid den tidsberoende studien som visade hur sannolikheten att byta till pump är avsevärt lägre vid hög ålder. Långtidsblodsockret har också tydlig effekt på sannolikheten att gå över till pump där ett högt långtidsblodsocker medför hög sannolikhet att byta till insulinpump. Slutsatser I dagsläget finns det skillnader i andelen insulinpumpanvändare mellan olika patientgrupper och skillnader finns även i de olika gruppernas benägenhet att byta från andra insulinbehandlingar till insulinpump. Beroende av patienters njurfunktion, kön, långtidsblodsocker, insulindos, diabetesduration och ålder har dessa olika sannolikheter att byta till insulinpump.

This study discusses main risk factors of ovarian tumor to determine a tumor type. Since symptoms of ovarian tumor are not obvious as the tumors are located in pelvic, the ovarian tumor is difficult to detect. The symptoms are mostly stomach or lower abdomen swellings, which are often ignored. The probability of ovarian cancer is lower than cervical cancer, but the mortality rate is the highest of all gynecologic diseases. The study uses statistical methods to analyze risk factors of patients to determine the tumor type and an early treatment in order to reduce the death rate. The sources of the studies are from Kaohsiung Veterans General Hospital and are classified according to different cases of tumors based on ultrasound checks and other relevant risk factors, such as ages and tumor marks so as to provide a determined method to distinguish among benign, borderline and malignant ovarian tumors in order to create appropriate classification criteria for followups, surgeries, and references for tracking. To differentiate between malignant and nonmalignant (benign and borderline) cases, we use risk factors to construct classification and regression trees so as to help physicians to determine the tumor type. In the situation in which the non-malignant tumor may be determined, we use logistic regression model according to the degree of influence of risk factors to further classify between benign and borderline tumors. The aforementioned process can determine tumor types precisely and can also determine surgery types so as to help determining whether patients would need a follow-up.

Several reports research the best prediction power of the credit risk models for different industries. The structural models use firm¡¦s information for firms¡¦ structural variables, such as asset value and asset volatility, to determine the time of default, but it suffer from some drawbacks, which represent the main reasons behind their relatively poor empirical performance. It require estimates for the parameters of the firm¡¦s asset value, which is nonobservable. Moody's KMV model is well known and useful among them, but it ignores recovery rate and difference in financial structure and industry. The reduced-form models fundamentally differ from typical structural models in the degree of predictability of the default. Reduced-form models use market data and assume the probability of default is exogenously generated. However, the basel committee for banking supervision proposed that risk is endogenous. The purpose of this paper is using quantile and threshold regression to introduce a new approach which is based on the Moody¡¦s KMV model, the Lu and Kuo ( 2005) and the Altman, Brooks Brady, Resti and Sironi (2005) to the evaluation of the endogenous probability of default and the endogenous recovery rate.

<p>The LSH-study started in 2003 at the department of Health and Society at the University of Linköping. The purpose of the study was to examine the relationship between life condition, stress and health. A total of 1007 people from ten different health centres in Östergötlands län participated. At the follow up, a couple of years later, 795 of the 1007 participated. 127 of the 212 in the attrition turned down the follow up, twelve people were not invited (for example in case of death) and the rest did not respond at all. The purpose of this paper is to find out in what degree the attrition in the follow up can be predicted using the information from the first survey and which variables are important. The differences between different types of attrition have also been examined. Simple and multiple bi- and multinomial logistic regression have been used in the analysis.</p><p>In total 34 variables were examined and in the final model six variables remained with a significant relation to the attrition. High BMI, regular smoking, high pulse and lack of daily exercise at the first survey were connected to a higher risk for an individual to not participate at the follow up. It is interesting that these factors are considered as risk factors for unhealthy living. Other factors related to a higher attrition were unemployment in the last year before the first survey and if the individual had parents born in another country than Sweden. The risk for attrition increased gradually when more risk factors were shown by the individual. The factors contributing an individual to turn down the follow up instead of not responding at all was if he or she were in the older age segments in the survey or if they were not active in any type of association.</p>

Estimation procedures and optimal designs for estimation of the individual parameters and of the global parameters are discussed under various conditions of prior knowledge. The extension to nonlinear parametrization of the response function ís based on the asymptotical validity of the results for the linear parametrization. For the case where the error variance and the dispersion matrix are unknown, an iterative estimation procedure is suggested. An example based on dental plaque pH profiles demonstrates the improvement that is achieved (a) through using the optimal design or a design that ís close to the optimal, and (b) through taking into account prior information. (author's abstract) / Series: Forschungsberichte / Institut für Statistik