Optimal crossover designs for logistic regression models in pharmacodynamics

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.

Guiding local regression using visualisation

Solving many scientific problems requires effective regression and/or classification models for large high-dimensional datasets. Experts from these problem domains (e.g. biologists, chemists, financial analysts) have insights into the domain which can be helpful in developing powerful models but they need a modelling framework that helps them to use these insights. Data visualisation is an effective technique for presenting data and requiring feedback from the experts. A single global regression model can rarely capture the full behavioural variability of a huge multi-dimensional dataset. Instead, local regression models, each focused on a separate area of input space, often work better since the behaviour of different areas may vary. Classical local models such as Mixture of Experts segment the input space automatically, which is not always effective and it also lacks involvement of the domain experts to guide a meaningful segmentation of the input space. In this paper we addresses this issue by allowing domain experts to interactively segment the input space using data visualisation. The segmentation output obtained is then further used to develop effective local regression models.

The impact of ICT on productivity of airline industry

Airline industry is at the forefront of many technological developments and is often a pioneer in adopting such innovations in a large scale. It needs to improve its efficiency as the current trends for input prices and competitive pressures show that any airline will face increasingly challenging market conditions. This paper has focused on the relationship between ICT investments and efficiency in the airline industry and employed a two-stage analytical investigation, DEA, SFA and the Tobit regression model. In this study, we first estimate the productivity of the airline industry using a balanced panel of 17 airlines over the period 1999–2004 by the Data Envelop Analysis (DEA) and the Stochastic Frontier Analysis (SFA) methods. We then evaluate the impacts of the determinants of productivity in the industry concentrating on ICT. The results suggest that regardless of all the negative shocks to the airline industry during the sample period, ICT had a positive effect on productivity during 1999-2004.

When does leverage hurt productivity growth? A firm-level analysis:a firm-level analysis

In the wake of the global financial crisis, several macroeconomic contributions have highlighted the risks of excessive credit expansion. In particular, too much finance can have a negative impact on growth. We examine the microeconomic foundations of this argument, positing a non-monotonic relationship between leverage and firm-level productivity growth in the spirit of the trade-off theory of capital structure. A threshold regression model estimated on a sample of Central and Eastern European countries confirms that TFP growth increases with leverage until the latter reaches a critical threshold beyond which leverage lowers TFP growth. This estimate can provide guidance to firms and policy makers on identifying "excessive" leverage. We find similar non-monotonic relationships between leverage and proxies for firm value. Our results are a first step in bridging the gap between the literature on optimal capital structure and the wider macro literature on the finance-growth nexus. © 2012 Elsevier Ltd.

Guiding local regression using visualisation

Solving many scientific problems requires effective regression and/or classification models for large high-dimensional datasets. Experts from these problem domains (e.g. biologists, chemists, financial analysts) have insights into the domain which can be helpful in developing powerful models but they need a modelling framework that helps them to use these insights. Data visualisation is an effective technique for presenting data and requiring feedback from the experts. A single global regression model can rarely capture the full behavioural variability of a huge multi-dimensional dataset. Instead, local regression models, each focused on a separate area of input space, often work better since the behaviour of different areas may vary. Classical local models such as Mixture of Experts segment the input space automatically, which is not always effective and it also lacks involvement of the domain experts to guide a meaningful segmentation of the input space. In this paper we addresses this issue by allowing domain experts to interactively segment the input space using data visualisation. The segmentation output obtained is then further used to develop effective local regression models.

Local-Median Method of Forecasting for Regression Time Series under Outliers

2002 Mathematics Subject Classification: 62M20, 62-07, 62J05, 62P20.

Application of the D-Fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator to a Generalized Logistic Model

2000 Mathematics Subject Classification: 62J12, 62F35

Regression games

The solution of a TU cooperative game can be a distribution of the value of the grand coalition, i.e. it can be a distribution of the payo (utility) all the players together achieve. In a regression model, the evaluation of the explanatory variables can be a distribution of the overall t, i.e. the t of the model every regressor variable is involved. Furthermore, we can take regression models as TU cooperative games where the explanatory (regressor) variables are the players. In this paper we introduce the class of regression games, characterize it and apply the Shapley value to evaluating the explanatory variables in regression models. In order to support our approach we consider Young (1985)'s axiomatization of the Shapley value, and conclude that the Shapley value is a reasonable tool to evaluate the explanatory variables of regression models.

Tropical seagrass-associated macroalgae distributions and trends relative to water quality

Tropical coastal marine ecosystems including mangroves, seagrass beds and coral reef communities are undergoing intense degradation in response to natural and human disturbances, therefore, understanding the causes and mechanisms present challenges for scientist and managers. In order to protect our marine resources, determining the effects of nutrient loads on these coastal systems has become a key management goal. Data from monitoring programs were used to detect trends of macroalgae abundances and develop correlations with nutrient availability, as well as forecast potential responses of the communities monitored. Using eight years of data (1996–2003) from complementary but independent monitoring programs in seagrass beds and water quality of the Florida Keys National Marine Sanctuary (FKNMS), we: (1) described the distribution and abundance of macroalgae groups; (2) analyzed the status and spatiotemporal trends of macroalgae groups; and (3) explored the connection between water quality and the macroalgae distribution in the FKNMS. In the seagrass beds of the FKNMS calcareous green algae were the dominant macroalgae group followed by the red group; brown and calcareous red algae were present but in lower abundance. Spatiotemporal patterns of the macroalgae groups were analyzed with a non-linear regression model of the abundance data. For the period of record, all macroalgae groups increased in abundance (Abi) at most sites, with calcareous green algae increasing the most. Calcareous green algae and red algae exhibited seasonal pattern with peak abundances (Φi) mainly in summer for calcareous green and mainly in winter for red. Macroalgae Abi and long-term trend (mi) were correlated in a distinctive way with water quality parameters. Both the Abi and mi of calcareous green algae had positive correlations with NO3−, NO2−, total nitrogen (TN) and total organic carbon (TOC). Red algae Abi had a positive correlation with NO2−, TN, total phosphorus and TOC, and the mi in red algae was positively correlated with N:P. In contrast brown and calcareous red algae Abi had negative correlations with N:P. These results suggest that calcareous green algae and red algae are responding mainly to increases in N availability, a process that is happening in inshore sites. A combination of spatially variable factors such as local current patterns, nutrient sources, and habitat characteristics result in a complex array of the macroalgae community in the seagrass beds of the FKNMS.

Three essays on a longitudinal analysis of business start-ups using the Kauffman Firm Survey

This dissertation focused on the longitudinal analysis of business start-ups using three waves of data from the Kauffman Firm Survey. ^ The first essay used the data from years 2004-2008, and examined the simultaneous relationship between a firm's capital structure, human resource policies, and its impact on the level of innovation. The firm leverage was calculated as, debt divided by total financial resources. Index of employee well-being was determined by a set of nine dichotomous questions asked in the survey. A negative binomial fixed effects model was used to analyze the effect of employee well-being and leverage on the count data of patents and copyrights, which were used as a proxy for innovation. The paper demonstrated that employee well-being positively affects the firm's innovation, while a higher leverage ratio had a negative impact on the innovation. No significant relation was found between leverage and employee well-being.^ The second essay used the data from years 2004-2009, and inquired whether a higher entrepreneurial speed of learning is desirable, and whether there is a linkage between the speed of learning and growth rate of the firm. The change in the speed of learning was measured using a pooled OLS estimator in repeated cross-sections. There was evidence of a declining speed of learning over time, and it was concluded that a higher speed of learning is not necessarily a good thing, because speed of learning is contingent on the entrepreneur's initial knowledge, and the precision of the signals he receives from the market. Also, there was no reason to expect speed of learning to be related to the growth of the firm in one direction over another.^ The third essay used the data from years 2004-2010, and determined the timing of diversification activities by the business start-ups. It captured when a start-up diversified for the first time, and explored the association between an early diversification strategy adopted by a firm, and its survival rate. A semi-parametric Cox proportional hazard model was used to examine the survival pattern. The results demonstrated that firms diversifying at an early stage in their lives show a higher survival rate; however, this effect fades over time.^

Variables affecting the success of older applicants for employment in a public organization: An age -cued cognitive model of administrative decision-making

The dissertation takes a multivariate approach to answer the question of how applicant age, after controlling for other variables, affects employment success in a public organization. In addition to applicant age, there are five other categories of variables examined: organization/applicant variables describing the relationship of the applicant to the organization; organization/position variables describing the target position as it relates to the organization; episodic variables such as applicant age relative to the ages of competing applicants; economic variables relating to the salary needs of older applicants; and cognitive variables that may affect the decision maker's evaluation of the applicant. ^ An exploratory phase of research employs archival data from approximately 500 decisions made in the past three years to hire or promote applicants for positions in one public health administration organization. A logit regression model is employed to examine the probability that the variables modify the effect of applicant age on employment success. A confirmatory phase of the dissertation is a controlled experiment in which hiring decision makers from the same public organization perform a simulated hiring decision exercise to evaluate hypothetical applicants of similar qualifications but of different ages. The responses of the decision makers to a series of bipolar adjective scales add support to the cognitive component of the theoretical model of the hiring decision. A final section contains information gathered from interviews with key informants. ^ Applicant age has tended to have a curvilinear relationship with employment success. For some positions, the mean age of the applicants most likely to succeed varies with the values of the five groups of moderating variables. The research contributes not only to the practice of public personnel administration, but is useful in examining larger public policy issues associated with an aging workforce. ^

Três alternativas estocásticas para modelar morbimortalidade por doenças respiratórias e cardiovasculares via variáveis atmosféricas

Climate and air pollution, among others, are responsible factors for increase of health vulnerability of the populations that live in urban centers. Climate changes combined with high concentrations of atmospheric pollutants are usually associated with respiratory and cardiovascular diseases. In this sense, the main objective of this research is to model in different ways the climate and health relation, specifically for the children and elderly population which live in São Paulo. Therefore, data of meteorological variables, air pollutants, hospitalizations and deaths from respiratory and cardiovascular diseases a in 11-year period (2000-2010) were used. By using modeling via generalized estimating equations, the relative risk was obtained. By dynamic regression, it was possible to predict the number of deaths through the atmospheric variables and the betabinomial-poisson model was able to estimate the number of deaths and simulate scenarios. The results showed that the risk of hospitalizations due to asthma increases approximately twice for children exposed to high concentrations of particulate matter than children who are not exposed. The risk of death by acute myocardial infarction in elderly increase in 3%, 6%, 4% and 9% due to high concentrations CO, SO2, O3 and PM10, respectively. Regarding the dynamic regression modeling, the results showed that deaths by respiratory diseases can be predicted consistently. The beta-binomial-poisson model was able to reproduce an average number of deaths by heart insufficiency. In the region of Santo Amaro the observed number was 2.462 and the simulated was 2.508, in the Sé region 4.308 were observed and 4.426 simulated, which allowed for the generation of scenarios that may be used as a parameter for decision. Making with these results, it is possible to contribute for methodologies that can improve the understanding of the relation between climate and health and proved support to managers in environmental planning and public health policies.

Avaliação multidimensional da qualidade de vida em idosos: um estudo no Curimataú ocidental paraibano

The fast growth of the elderly population is a reality throughout the world and has become one of the greatest challenges for contemporary public health. When considering the increased life expectancy and the aging as a multidimensional phenomenon, one should highlight the need to investigate if the increase of longevity is associated with satisfactory levels of Quality of Life (QOL). This study has the objective of assessing the QOL of elderly people from the Paraíba’s Western Curimataú microregion, explained by its health and living conditions. This is a cross-sectional and observational study with quantitative design held with 444 elderly people from five cities: Barra de Santa Rosa, Cuité, Nova Floresta, Remígio e Sossego. In order to obtain information, the following instruments were used: I) Questionnaire for collection data related to the elderly population, for sociodemographic, clinical and behavioral characteristics; and II) WHOQOL-Old questionnaire, with a view to measuring and assessing QOL. Data were processed on the IBM-SPSS Statistics 20.0 software by means of the ANOVA (one-way), Student’s t, Mann-Whitney, Kruskal-Wallis and Pearson’s correlation tests, with p-values<0,05 accepted as being statistically significant. The results indicate a good global QOL (ETT=65,69%), with better assessment by elderly men, aged between 60 and 74 years, married, living with partner and children, without caregiver, physical activity practitioners, with up to one health problem before an aspect of multimorbidity and with very good and/or good assessment of basic needs. The self-reported stress showed a negative significant correlation before the global QOL, where the greater the perception of stress, the worse the assessment of QOL. In the faceted assessment of QOL, the Sensory Operation showed the best performance (ETF= 68,86%) and the Social Participation (SP) the worst (ETF=60,37%). In the multiple linear regression model, SP is singly responsible for 51,8% (R2=0,518) of explanation of the global QOL. In the intercorrelation among the WHOQOL-Old facets, only Death and Dying did not reveal significance. The harmony highlighted among the facets raises the need to ensure a comprehensive health care for the elderly population, especially in understanding the social participation as an intrinsic part of the QOL and that it requires the re-discussion and reconstruction of individual and collective, family and community, political and government actions. Hence, guaranteeing an active, healthy and participatory aging, with QOL, is the major challenge.

Avaliação multidimensional da qualidade de vida em idosos: um estudo no Curimataú ocidental paraibano

The fast growth of the elderly population is a reality throughout the world and has become one of the greatest challenges for contemporary public health. When considering the increased life expectancy and the aging as a multidimensional phenomenon, one should highlight the need to investigate if the increase of longevity is associated with satisfactory levels of Quality of Life (QOL). This study has the objective of assessing the QOL of elderly people from the Paraíba’s Western Curimataú microregion, explained by its health and living conditions. This is a cross-sectional and observational study with quantitative design held with 444 elderly people from five cities: Barra de Santa Rosa, Cuité, Nova Floresta, Remígio e Sossego. In order to obtain information, the following instruments were used: I) Questionnaire for collection data related to the elderly population, for sociodemographic, clinical and behavioral characteristics; and II) WHOQOL-Old questionnaire, with a view to measuring and assessing QOL. Data were processed on the IBM-SPSS Statistics 20.0 software by means of the ANOVA (one-way), Student’s t, Mann-Whitney, Kruskal-Wallis and Pearson’s correlation tests, with p-values<0,05 accepted as being statistically significant. The results indicate a good global QOL (ETT=65,69%), with better assessment by elderly men, aged between 60 and 74 years, married, living with partner and children, without caregiver, physical activity practitioners, with up to one health problem before an aspect of multimorbidity and with very good and/or good assessment of basic needs. The self-reported stress showed a negative significant correlation before the global QOL, where the greater the perception of stress, the worse the assessment of QOL. In the faceted assessment of QOL, the Sensory Operation showed the best performance (ETF= 68,86%) and the Social Participation (SP) the worst (ETF=60,37%). In the multiple linear regression model, SP is singly responsible for 51,8% (R2=0,518) of explanation of the global QOL. In the intercorrelation among the WHOQOL-Old facets, only Death and Dying did not reveal significance. The harmony highlighted among the facets raises the need to ensure a comprehensive health care for the elderly population, especially in understanding the social participation as an intrinsic part of the QOL and that it requires the re-discussion and reconstruction of individual and collective, family and community, political and government actions. Hence, guaranteeing an active, healthy and participatory aging, with QOL, is the major challenge.

Outcomes and Predictors of Mortality in Neurosurgical Patients at Mbarara Regional Referral Hospital

Background:

Knowing the scope of neurosurgical disease at Mbarara Hospital is critical for infrastructure planning, education and training. In this study, we aim to evaluate the neurosurgical outcomes and identify predictors of mortality in order to potentiate platforms for more effective interventions and inform future research efforts at Mbarara Hospital.

Methods:

This is retrospective chart review including patients of all ages with a neurosurgical disease or injury presenting to Mbarara Regional Referral Hospital (MRRH) between January 2012 to September 2015. Descriptive statistics were presented. A univariate analysis was used to obtain the odds ratios of mortality and 95% confidence intervals. Predictors of mortality were determined using multivariate logistic regression model.

Results:

A total of 1876 charts were reviewed. Of these, 1854 (had complete data and were?) were included in the analysis. The overall mortality rate was 12.75%; the mortality rates among all persons who underwent a neurosurgical procedure was 9.72%, and was 13.68% among those who did not undergo a neurosurgical procedure. Over 50% of patients were between 19 and 40 years old and the majority of were males (76.10%). The overall median length of stay was 5 days. Of all neurosurgical admissions, 87% were trauma patients. In comparison to mild head injury, closed head injury and intracranial hematoma patients were 5 (95% CI: 3.77, 8.26) and 2.5 times (95% CI: 1.64,3.98) more likely to die respectively. Procedure and diagnostic imaging were independent negative predictors of mortality (P <0.05). While age, ICU admission, admission GCS were positive predictors of mortality (P <0.05).

Conclusions:

The majority of hospital admissions were TBI patients, with RTIs being the most common mechanism of injury. Age, ICU admission, admission GCS, diagnostic imaging and undergoing surgery were independent predictors of mortality. Going forward, further exploration of patient characteristics is necessary to fully describe mortality outcomes and implement resource appropriate interventions that ultimately improve morbidity and mortality.