A command for fitting mixture regression models for bounded dependent variables using the beta distribution

In this article, we describe the betamix command, which fits mixture regression models for dependent variables bounded in an interval. The model is a generalization of the truncated inflated beta regression model introduced in Pereira, Botter, and Sandoval (2012, Communications in Statistics—Theory and Methods 41: 907-919) and the mixture beta regression model in Verkuilen and Smithson (2012, Journal of Educational and Behavioral Statistics 37: 82-113) for variables with truncated supports at either the top or the bottom of the distribution. betamix accepts dependent variables defined in any range that are then transformed to the interval (0, 1) before estimation

Development of methods for the mapping of utilities using mixture models: An application to asthma

Objectives: To develop methods for mapping to preference-based measures using mixture model approaches. These methods are compared to map from the Asthma Quality of Life Questionnaire (AQLQ) to both EQ5D-5L and HUI-3 as the target health utility measures in an international dataset. Methods: Data from 856 patients with asthma collected as part of the Multi-Instrument Comparison (MIC) international project were used. Adjusted limited dependent variable mixture models (ALDVMMs) and beta-regression based mixture models were estimated. Optional inclusion of the gap between full health and the next value, and a mass point at the next feasible value were explored. Response-mapping could not be implemented due to missing data. Results: In all cases, model specifications which formally modelled the gap between full health and the next value were an improvement on those which did not. Mapping to HUI3 required more components in the mixture models than mapping to EQ5D-5L due to its uneven distribution. The optimal beta-based mixture models mapping to HUI3 included a probability mass at the utility value adjacent to full health. This is not the case when estimating EQ5D-5L, due to the low proportion of observations at this point. Conclusion: The beta-based mixture models marginally outperformed ALDVMM in this dataset when comparing models with the same number of components. This is at the expense of requiring a larger number of parameters and estimation time. Both model types are able to closely fit the data without biased characteristic of many mapping approaches. Skilled judgment is critical in determining the optimal model. Caution is required in ensuring a truly global maximum likelihood has been identified

BMI trajectories and the influence of missing data

31st European Congress on Obesity (ECO 2024) : Meeting Reports / Abstract

Family Lifestyle Dynamics and Childhood Obesity: Evidence from the Millennium Cohort Study

Using data from the Millennium Cohort Study, we investigate the dynamic relationship between underlying family lifestyle and childhood obesity during early childhood. We use a dynamic latent factor model, an approach that allows us to identify family lifestyle, its evolution over time and its influence on childhood obesity and other observable outcomes. We find that family lifestyle is persistent and has a significant influence on childhood weight status as well as other outcomes for all family members. Interventions should therefore be prolonged and persuasive and target the underlying lifestyle of a family as early as possible during childhood in order to have the greatest cumulative influence. Furthermore, the results indicate that to reduce inequalities in childhood obesity, policy makers should target disadvantaged families and design interventions specifically for these families

Understanding the role of the primary somatosensory cortex: Opportunities for rehabilitation.

Emerging evidence indicates impairments in somatosensory function may be a major contributor to motor dysfunction associated with neurologic injury or disorders. However, the neuroanatomical substrates underlying the connection between aberrant sensory input and ineffective motor output are still under investigation. The primary somatosensory cortex (S1) plays a critical role in processing afferent somatosensory input and contributes to the integration of sensory and motor signals necessary for skilled movement. Neuroimaging and neurostimulation approaches provide unique opportunities to non-invasively study S1 structure and function including connectivity with other cortical regions. These research techniques have begun to illuminate casual contributions of abnormal S1 activity and connectivity to motor dysfunction and poorer recovery of motor function in neurologic patient populations. This review synthesizes recent evidence illustrating the role of S1 in motor control, motor learning and functional recovery with an emphasis on how information from these investigations may be exploited to inform stroke rehabilitation to reduce motor dysfunction and improve therapeutic outcomes

Site assessment of Douglas Shoal ship grounding in the Great Barrier Reef

The bulk carrier Shen Neng 1 ran aground on Douglas Shoal in the Great Barrier Reef Marine Park in April 2010. At over 40 hectares, this is the largest ship grounding scar known in the Great Barrier Reef, and possibly the largest reef-related grounding in the world. Challenges for assessment of the site included its large scale and the remote nature of Douglas Shoal coupled with its high exposure to wind, wave conditions and fauna that may pose safety hazards. Marine surveys used multiple and novel methods including sediment sampling combined with visual and acoustic survey techniques

Determination of cadmium in solutions containing uranium, neptunium, and plutonium

An analytical method was developed for determining cadmium in solutions containing fissionable materials and high alpha activities. The solutions were first extracted with 30% tributyl phosphate in dodecane to separate the actinide elements from the cadmium. This extraction step removed interfering ions and reduced the alpha activity. The cadmium concentrations were determined by atomic absorption analysis. The method has been applied to solutions containing 20 to 30 g Cd/liter, about 10 g Pu/liter (38% /sup 238/Pu), about 15 g /U/liter (66% /sup 235/U) and about 0.05 g Np/liter with a standard deviation for cadmium of 2.65%. The fissionable materials were generally reduced from about 25 g/liter to about 10/sup -7/ g/liter in the solutions analyzed, i.e., about 0.5 picogram of fissionable material was introduced to the atomic absorption flame. 2 figures, 6 tables

Mapping the FACT-B instrument to EQ-5D-3L in patients with breast cancer using adjusted limited dependent variable mixture models versus response mapping

Objectives Preference based measures (PBMs) of health, such as EQ-5D-3L, are required to calculate QALYs for use in cost-effectiveness analysis, but are often not recorded in clinical studies. In these cases, mapping can be used to estimate PBMs. We model the relationship between EQ-5D-3L and Functional Assessment of Cancer Therapy - Breast Cancer (FACT-B), comparing indirect and direct mapping methods, and the use of FACT-B summary score verses subscale scores. Methods We use data from 3 clinical studies for advanced breast cancer providing 11,958 observations with full information on FACT-B and EQ-5D-3L. We compare direct mapping using adjusted limited dependent variable mixture models (ALDVMMs) with indirect mapping using seemingly unrelated ordered probit models. EQ-5D-3L was estimated as a function of FACT-B and other patient related covariates. Results The use of FACT-B subscales was better than using total FACT-B score. A good fit to the observed data was observed across the range of disease severity in all models. ALDVMMs outperform the indirect mapping. The breast cancer specific scale significantly predicts EQ-5D-3L and this subscale has large influences on pain and self-care dimensions of EQ-5D-3L. Conclusion This paper adds to the growing literature that demonstrates the performance of the ALDVMM method for mapping. Regardless of which model is used, the subscales of FACT-B should be included as independent variables wherever possible. The breast cancer specific subscales of FACT-B are important in predicting EQ-5D-3L. This suggests that generic cancer measures should not be used for utility mapping in patients with breast cancer

Leaf:wood allometry and functional traits together explain substantial growth rate variation in rainforest trees

Plant growth rates drive ecosystem productivity and are a central element of plant ecological strategies. For seedlings grown under controlled conditions, a large literature has firmly identified the functional traits that drive interspecific variation in growth rate. For adult plants, the corresponding knowledge is surprisingly poorly understood. Until recently it was widely assumed that the key trait drivers would be the same (e.g. specific leaf area, or SLA), but an increasing number of papers has demonstrated this not to be the case, or not generally so. New theory has provided a prospective basis for understanding these discrepancies. Here we quantified relationships between stem diameter growth rates and functional traits of adult woody plants for 41 species in an Australian tropical rainforest. From various cost-benefit considerations, core predictions included that: (i) photosynthetic rate would be positively related to growth rate; (ii) SLA would be unrelated to growth rate (unlike in seedlings where it is positively related to growth); (iii) wood density would be negatively related to growth rate; and (iv) leaf mass:sapwood mass ratio (LM:SM) in branches (analogous to a benefit:cost ratio) would be positively related to growth rate. All our predictions found support, particularly those for LM:SM and wood density; photosynthetic rate was more weakly related to stem diameter growth rates. Specific leaf area was convincingly correlated to growth rate, in fact negatively. Together, SLA, wood density and LM:SM accounted for 52 % of variation in growth rate among these 41 species, with each trait contributing roughly similar explanatory power. That low SLA species can achieve faster growth rates than high SLA species was an unexpected result but, as it turns out, not without precedent, and easily understood via cost-benefit theory that considers whole-plant allocation to different tissue types. Branch-scale leaf:sapwood ratio holds promise as an easily measurable variable that may help to understand growth rate variation. Using cost-benefit approaches teamed with combinations of leaf, wood and allometric variables may provide a path towards a more complete understanding of growth rates under field conditions