6 resultados para Mixed integer models

em DigitalCommons@The Texas Medical Center


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The objective of this longitudinal study, conducted in a neonatal intensive care unit, was to characterize the response to pain of high-risk very low birth weight infants (<1,500 g) from 23 to 38 weeks post-menstrual age (PMA) by measuring heart rate variability (HRV). Heart period data were recorded before, during, and after a heel lanced or wrist venipunctured blood draw for routine clinical evaluation. Pain response to the blood draw procedure and age-related changes of HRV in low-frequency and high-frequency bands were modeled with linear mixed-effects models. HRV in both bands decreased during pain, followed by a recovery to near-baseline levels. Venipuncture and mechanical ventilation were factors that attenuated the HRV response to pain. HRV at the baseline increased with post-menstrual age but the growth rate of high-frequency power was reduced in mechanically ventilated infants. There was some evidence that low-frequency HRV response to pain improved with advancing PMA.

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In most epidemiological studies, historical monitoring data are scant and must be pooled to identify occupational groups with homogeneous exposures. Homogeneity of exposure is generally assessed in a group of workers who share a common job title or work in a common area. While published results suggest that the degree of homogeneity varies widely across job groups, less is known whether such variation differs across industrial sectors, classes of contaminants, or in the methods used to group workers. Relying upon a compilation of results presented in the literature, patterns of homogeneity among nearly 500 occupational groups of workers were evaluated on the basis of type of industry and agent. Additionally, effects of the characteristics of the sampling strategy on estimated indicators of homogeneity of exposure were assessed. ^ Exposure profiles for occupational groups of workers have typically been assessed under the assumption of stationarity, i.e., the mean exposure level and variance of the distribution that describes the underlying population of exposures are constant over time. Yet, the literature has shown that occupational exposures have declined in the last decades. This renders traditional methods for the description of exposure profiles inadequate. Thus, work was needed to develop appropriate methods to assess homogeneity for groups of workers whose exposures have changed over time. A study was carried out applying mixed effects models with a term for temporal trend to appropriately describe exposure profiles of groups of workers in the nickel-producing industry over a 20-year period. Using a sub-set of groups of nickel-exposed workers, another study was conducted to develop and apply a framework to evaluate the assumption of stationarity of the variances in the presence of systematic changes in exposure levels over time. ^

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The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

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Asthma is the most common chronic disorder in childhood, affecting an estimated 6.2 million children under 18 years (1). The purpose of this study was to look at individual- and community-level characteristics simultaneously to examine and explain the factors that contribute to the use of emergency department services by children 18 years old or less and to determine if there was an association between air quality and ED visits in the same population, from 2005-2007 in Houston/Harris County. Data were collected from the Houston Safety Net Hospital Emergency Department Use Study and the 2000 US Census. Bivariate and multivariate logistic regression models and mixed effects models were used to analyze data that was collected during the study period.^ There were 704,902 ED visits made by children 18 and younger, who were living in Houston from January 1, 2005 to December 31, 2007. Of those, 19,098 had a primary discharge diagnosis of asthma. Asthma ED visits varied by season, with proportions of ED visits for asthma highest from September-December. African-American children were 2.6 (95% CI, 2.43-2.66) times more likely to have an ED visit for asthma compared to White children. Poverty, single parent headed households, and younger age all a greater likelihood of having gone to the ED for asthma treatment. Compared to Whites living in lightly-monitored pollution areas, African-Americans and Hispanics living in heavily monitored areas were 1.15 (95% CI, 1.04-1.28) times more likely to have an ED visit for asthma.^ Race and poverty seem to account for a large portion of the disparities in ED use found among children. This was true even after accounting for multiple individual- and community-level variables. These results suggest that racial disparities in asthma continue to pose risks for African American children, and they point to the need for additional research into potential explanations and remedies. Programs to reduce inappropriate ED use must be sensitive to an array of complex socioeconomic issues within minority and income populations. ^

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BACKGROUND: This observational research study investigated the association of cardiorespiratory fitness and weight status with repeated measures of 24-hr ambulatory blood pressure (24-hr ABP). Little is known about these associations and few data exist examining the interaction between cardiorespiratory fitness and weight status and the contributions of each on 24-hr ABP in youth. ^ METHODS: This research study used secondary analysis data from the "Adolescent Blood Pressure and Anger: Ethnic Differences" study. This current study sample included 374 African-American, Anglo-American, and Mexican-American adolescents 11-16 years of age. Mixed-effects models were used for testing the relationship between weight status and cardiorespiratory fitness and repeated measures of ambulatory blood pressure over 24 hours (24-hr ABP). Weight status was categorized into "normal weight" (BMI<85th percentile), "overweight" (85th≤BMI<95th), and "obese" (BMI≥95th). Cardiorespiratory fitness, determined by heart rate recovery (HRR), was defined as the difference between heart rate at peak exercise and heart rate at two minutes post-exercise, as measured by a height-adjusted step test and stratified into two groups: low and high fitness, using a median split. Ambulatory blood pressure (ABP) was monitored for a 24-hr period on a school day using the Spacelabs ambulatory monitor (Model 90207). Blood pressure and heart rate were recorded at 30 minute intervals throughout the day of recording and at 60 minute intervals during sleep. ^ RESULTS: No significant associations were found between weight status and mean 24-hr systolic blood pressure (SBP) or mean arterial pressure (MAP). A significant and inverse association between weight status and mean 24-hr diastolic blood pressure (DBP) was revealed. Cardiorespiratory fitness was significantly and inversely associated with mean 24-hr ABP. High fitness adolescents had significantly lower mean 24-hr SPB, DBP, and MAP measurements than low fitness adolescents. Compared to low fitness adolescents, high fitness adolescents had 1.90 mmHg, 1.16 mmHg, and 1.68 mmHg lower mean 24-hr SBP, DBP, and MAP, respectively. Additionally, high fitness appeared to afford protection from higher mean 24-hr SBP and MAP, irrespective of weight status. Among normal weight adolescents, low fitness resulted in higher mean 24-hr SBP and MAP, compared to their fit counterparts. Among adolescents categorized as high fitness, increasing weight status did not appear to result in higher mean 24-hr SBP or MAP. Cardiorespiratory fitness, rather than weight status, appeared to be a more dominant predictor of mean 24-hr SBP and MAP. ^ CONCLUSIONS: To our knowledge, this research is the first study to investigate the independent and combined contributions of cardiorespiratory fitness and weight status on 24-hr ABP, all objectively measured. The results of this study may potentially guide and inform future research. It appears that early cardiovascular disease (CVD) prevention should focus on improving cardiorespiratory fitness levels among all adolescents, particularly those adolescents least fit, regardless of their weight status, while obesity prevention efforts continue.^

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The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^