In the late 90s coconut farms in Mozambique were affected by a disease that made the coconut trees drop their leaves and die, the disease is called the coconut lethal yellowing disease (CLYD). It is known that planthoppers are spreading the disease. This thesis investigates if cultivation and farm related factors could have an impact on the risk of being infected by CLYD. With a sample of 534 farms from the two provinces Zambeze and Nampula a logistic regression model is estimated. The result shows that the only factor that has a significant effect of increasing the risk of getting infected by the disease is if farms had other palm species than coconut trees on the plantation. / I slutet av 90-talet drabbades många kokosnötsfarmer i Mocambique av en sjukdom som gjorde att träden började tappa sina löv och till slut dog. Denna sjukdom kallas för ”the coconut lethal yellowing disease” (CLYD). I dagsläget vet man att det är en specifik insekt som sprider denna sjukdom. Denna uppsats undersöker om det finns andra faktorer som kan påverka risken för koksnötsfarmer att drabbas av denna sjukdom, faktorer som är kopplade till farmerna och dess vegetation. Genom ett urval av 534 farmer från de två provinserna Zambezia och Nampula skattades en logistik regression. Resultatet visade att det enbart är en faktor, om plantagen innehåller andra palmsorter, som signifikant ökar risken för att en farm ska drabbas av CLYD.

The primary purpose of this study was to find out which variables lie behind the fact that patients who respond well to treatment of chronic pain differs from those who do not. We used logistic regression to predict group belonging based on the self-reported health surveys, i.e if different answers in the surveys can predict whether a patient is “responsive” or “unresponsive”. By bootstrapping 176 samples, and aggregating the results from 176 logistic regressions based on the sub-samples, we calculate an averaged model. The variables anxiety and physical health were significant in 76% and 70% of the models respectively, while depression was significant in 30% of the models. Gender was significant in 15% of the models and health status in 0,006%. The averaged model correctly classified the most unresponsive patients at cut-off value 0.5. As the cut –off value was increased, the number of correctly classified unresponsive patients decreased while the number of correctly classified responsive patients increased, as well as unresponsive patients classified as responsive. We concluded that the model did not discriminate enough between the two groups. We were also interested in finding out how the variables anxiety, depression, heath status, willingness to participate in activities as well as engagement in activities, mental and physical health relate with one another. The results from confirmatory factor analysis showed that a patient’s health status is highly related to their physical health and activity engagement while pain willingness and engagement in activity were least related. Furthermore, the analysis showed that mental health is highly related with anxiety and health status, indicating that mental health is indeed important to reflect upon when considering the health status of a patient.

In this paper we seek to answer the following question: How complete is the Swespineregister? In order to answer this question we believe that in a register that has the ambitionto follow-up patients throughout a specified period of time, two types of completeness haveto be defined: external and internal completeness. In our opinion, the correct assessment ofa register’s level of completeness, results in an increase in its credibility, revealing whetherthe register has met its desired level of quality.By defining the register’s target population we came to the conclusion that the methodused by Swespine to calculate external completeness yielded misleading results. We definedanother method of assessing external completeness and concluded that our questioncannot be answered.We have also found an appropriate way to calculate the register’s internal completenesslevel. Since the internal completeness decreases as the follow-up period increases, wesought to discover which groups of patients are more likely to respond to the follow-upquestionnaire. For this a Logistic Regression Method was applied.

Four subjects, ecology, applied mathematics, sociology and economics, were selected to assess whether there is a citation advantage between journal articles that have an open access (OA) version on the Internet compared to those articles that are exclusively toll access (TA). In two rounds of data collection, citations were counted using the Web of Science and the OA status of articles was determined by using the search tools OAIster, OpenDOAR, Google and Google Scholar. In the first round a purposive sample of 4633 articles for the four subjects from high impact journals were examined, 2280 (49%) were OA and had a mean citation count of 9.04, whereas the mean for TA articles was 5.76. There was a clear citation advantage for those articles that were OA as opposed to those that were TA. This advantage, however, varied between disciplines, with sociology having the highest citation advantage but the lowest number of OA articles from the sample taken and ecology having the highest individual citation count for OA articles but the smallest citation advantage. Tests of correlation between OA status and a number of variables were generally found to be weak or inconsistent but some associations were significant. Google and Google Scholar were more successful at finding OA articles on the Internet than were OAIster or OpenDOAR. The country of origin of the citing authors for applied maths was found in order to assess whether those authors from poorer countries cited OA articles more frequently than TA articles. While cited to citing article ratios from lower income countries favoured OA articles, overall percentages gave mixed results. The data from the second round confirmed the result for sociology. The second sample for ecology was randomly taken from 82 journals and exhibited a greater OA advantage. For economics, a second purposive sample of articles from 21 mid-range impact journals was taken and also exhibited a greater OA advantage. In an attempt to establish the cause of any citation advantage, logistic regression was used to try to determine whether the bibliographic characteristics of the articles from both rounds could be used to predict OA status. Results from this were generally inconclusive.

This research investigated the association of street network connectivity differences across travel modes with travel behaviour – mode choice, distance traveled and number of trips. To date research on travel behaviour relationships with urban form has not developed empirical evidence on street designs as distinct networks for walking and driving. A street network having greater connectivity and continuity for the pedestrian mode of travel vis-à-vis the vehicular network, like the Fused Grid, will likely encourage more walking. This hypothesis was investigated using a quasi-experimental approach within a rational utility behavioural framework. Local travel behaviour is theorized to be affected by desire to access goods and services (broadly termed, ‘activities’) in the community where people live. Using inferential statistics, the research tested for relationships between measured street patterns and self-reported local travel by King County, WA households. The main variables were ratios (walking : driving) of network connectivity and density, in the vicinity of travel survey households. Demographics and household characteristics, as well as other behaviourally influential urban form factors (residential density, proximity of destinations, etc.), were included in regression models, allowing control for confounding factors. Findings suggest that street networks with connectivity that provides better routing for one mode of transportation over others encourage more travel by the favored mode. The regression model demonstrated that a change from a pure small-block grid to a modified grid (i.e. Fused Grid) can result in an 11.3% increase in odds of a home-based trip being walked. The modified street pattern like a Fused Grid is also associated with a 25.9% increase, over street patterns with equivalent route directness for walking and driving, in the odds a person will meet recommended levels of physical activity. Finally, the Fused Grid’s 10% increase in relative connectivity for pedestrians is associated with a 23% decrease in local vehicle travel distance (VMT), and its improved continuity is associated with increased walking trips and distance. Conclusions: Other factors being equal, residential street networks with either more direct routing for pedestrians or more pedestrian facilities relative to vehicular network are associated with improved odds of walking and reduced odds of driving.

The Association of Hypertension Diagnosis with Smoking Cessation: Application of Multiple Logistic Regression Using Biostatistical and Epidemiological Methods by LaTonia A. Clay Under the Direction of Yu-Sheng Hsu, PhD. ABSTRACT Hypertension and smoking are two major issues threatening the nation’s health. Previous studies examining their relationship have resulted in conflicting reports. The aim of this study is to determine if a relationship exists between smoking cessation and hypertension diagnosis. Data from the Third National Health and Nutrition Examination Survey (NHANES III) were used in this investigation. Physical examination measurements of blood pressure and self-reported diagnosis and smoking behavior were used to define hypertension and smoking status. The odds of prior hypertension diagnosis associated with smoking cessation was estimated from a multivariate logistic regression model, adjusting for gender, age, ethnicity, BMI, physical activity, HDL cholesterol, and alcohol use. Results of the investigation found that unsuccessful smoking cessation was associated with a decreased odds of prior hypertension diagnosis, adjusting for the presence of confounders (OR=0.816, p<.001). Thus, hypertension diagnosis may indeed lead to the decision to quit smoking. Future studies on this finding are encouraged. INDEX WORDS: hypertension, smoking, cessation, diagnosis, logistic regression, NHANES

Statement of the Problem The national six-year graduation rate is less than 60 percent. This alarming yet consistent feature of higher education has led researchers like Bean (1980), Tinto (1975, 1993), Astin (1993), Adelman (1999), Braxton (2000) and DesJardins (2002) to create a body of research which attempts to explain the causes of student attrition and suggest possible interventions. Learning Communities and Freshman Experience courses are two efforts to improve retention which are derived from this research. The purpose of this study was to test portions of Tinto’s longitudinal model of institutional departure that relates academic fit to persistence and degree completion. The study examined placement testing and advising procedures and the effects these procedures have on eventual degree completion. The results of this study should inform the academic community about the efficacy of using a placement test to promote academic fit for first time freshmen enrolled in mathematics courses. Method This quantitative study was an ex-post facto, quasi experimental design which compared three procedures for placement into the initial college mathematics course and the impact on retention and eventual degree completion. The data for this study was obtained from existing data sources. Logistic regression was used to compare the three placement methods and the effect on the odds of eventual degree completion. Results While the placement instrument did provide some useful information for placement decisions about some courses, it does not provide as much information as other available measures, in particular, the high school history expressed as the grade point average. Quality point production at the end of the first year was found to be a strong predictor of eventual graduation. The results suggest that for each one unit increase in the quality points earned the odds of graduation are 1.042 times better. Statistically significant differences were found in the efficacy of the different placement methods; however these differences were overshadowed by the effect of the introduction of a new mathematics course. The average grade in the initial collegiate math class for the groups in this study has risen from a low of 1.87 to 2.37 after the introduction of Math Modeling to the curriculum.

The speed and accuracy of conservation planning could be improved if maps indicating areas where grassed waterways should be placed to reduce erosion could be easily created. For five central Kentucky fields, elevation data were obtained with real time kinematic (RTK) global positioning system (GPS) and from US Geological Survey (USGS) digital elevation models (DEMs). Terrain attributes were calculated from these datasets which were used as predictor variables for neural network and logistic regression analyses. Grassed waterway prediction models were developed with these analyses. The type of activation function, type of standardization procedure, number of neurons, number of preliminary runs, and number of hidden layers had little impact on the results of the neural network analysis. Logistic regression and neural network analyses produced similar erosion prediction maps. The type of flow direction algorithm used to calculate terrain attributes did not change prediction maps substantially. Grassed waterways could be predicted in most cases with the RTK data but only in some cases with the USGS data. This modeling approach was robust and could aid conservation planners in identifying suitable areas for waterways more efficiently if accurate elevation data can be acquired.

This study, concentrating on the Ouachita Mountain Range in western-central Arkansas, extends prior work on treethrows and their influence on soil development in the region by supplying a method of determining hotspots of bedrock mining by treethrow. Binary logistic regression analysis was employed to determine the abiotic and biotic factors that are highly correlated with the rate of bedrock detachment found in uprooted rootwads from three study sites within the Ouachita National Forest. The produced logistic regression models suggest topographic factors, tree specific characteristics, as well as the local geology and soil characteristics all have a significant effect upon the probability of bedrock mining activity by treethrow throughout the Ouachita National Forest, Arkansas. This methodology has demonstrated that the forcing mechanism that causes the uprooting event intrinsically changes the relationship between the abiotic and biotic factors that control bedrock mining. Finally, the computed probabilities of bedrock being mined were geographically assigned to the appropriate environmental setting using a geographic information system to identify areas of highest odds of mining, hotspots, and lowest odds of mining highlighted.

Customer targeting is the key to the success of bank telemarketing. To compare the flexible discriminant analysis and the logistic regression in customer targeting, a survey dataset from a Portuguese bank was used. For the flexible discriminant analysis model, the backward elimination of explanatory variables was used with several rounds of manual re-defining of dummy variables. For the logistic regression model, the automatic stepwise selection was performed to decide which explanatory variables should be left in the final model. Ten-fold stratified cross validation was performed to estimate the model parameters and accuracies. Although employing different sets of explanatory variables, the flexible discriminant analysis model and the logistic regression model show equally satisfactory performances in customer classification based on the areas under the receiver operating characteristic curves. Focusing on the predicted “right” customers, the logistic regression model shows slightly better classification and higher overall correct prediction rate.