ijsmr
Editor’s Choice : Conditional Two Level Mixture with Known Mixing Proportions: Applications to School and Student Level Overweight and Obesity Data from Birmingham, England
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Abstract: Two Level (TL) models allow the total variation in the outcome to be decomposed as level one and level two or ‘individual and group’ variance components. Two Level Mixture (TLM) models can be used to explore unobserved heterogeneity that represents different qualitative relationships in the outcome. In this paper, we extend the standard TL model by introducing constraints to guide the TLM algorithm towards a more appropriate data partitioning. Our constraints-based methods combine the mixing proportions estimated by parametric Expectation Maximization (EM) of the outcome and the random component from the TL model. This forms new two level mixing conditional (TLMc) approach by means of prior information. The new framework advantages are: 1. avoiding trial and error tactic used by TLM for choosing the best BIC (Bayesian Information Criterion), 2. permitting meaningful parameter estimates for distinct classes in the coefficient space and finally 3. allowing smaller residual variances. We show the benefit of our method using overweight and obesity from Body Mass Index (BMI) for students in year 6. We apply these methods on hierarchical BMI data to estimate student multiple deprivation and school Club effects. Keywords: Parametric Expectation Maximization, Multilevel Mixture, Conditional Multilevel Mixture Known Mix, Overweight and Obesity Data.Download Full Article |
Editor’s Choice : Predicting Risks of Increased Morbidity among Atrial Fibrillation Patients using Consumption Classes
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Abstract: Background: Atrial fibrillation (AF) is the most common chronic cardiac arrhythmia. Predicting the risk of complications, or associated increases in healthcare costs, among AF patients is important for effective health care management. Methods: A bivariate regression model including a latent morbidity index is used to predict both risk of transition to higher health costs, and mortality risk over a single year. A risk scoring algorithm for predicting transition to higher cost levels is then set out which incorporates the most significant risk factors from the regression. Results: The regression analysis shows that in addition to age and comorbidities, baseline consumption category, ethnic group, metropolitan residence and Warfarin adherence are also significant influences on progression to increased health consumption, and relevant to assessing risk. The resulting risk scoring algorithm produces a higher AUC than the widely applied CHADS2 score. Conclusions: The utility of a bivariate regression method with a latent morbidity index for predicting transition to worsening health status among AF patients is demonstrated. A risk scoring system based on this method outperforms an established risk score. Keywords: Morbidity, Risk scores, Latent variable, Atrial fibrillation, Consumption class.Download Full Article |
Editor’s Choice : Research Article: Survival Analysis of Under Five Mortality in Rural Parts of Ethiopia
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Abstract: Child mortality is a factor that is associated with the well-being of a population and it is taken as an indicator of health development and socioeconomic status. According to the 2011 UN report during the last 10 years, the death rate for children under five has decreased by 35% worldwide. UNICEF in 2008 reported that Ethiopia has reduced under-five mortality by 40 percent over the past 15 years. From the EDHS 2011 report child mortality rate in Ethiopia was reduced from 50/1000 deaths in 2005 to 31/1000 deaths in 2011. The Ethiopian Demographic and Health Survey data are used for the study. In this paper we have attempted to find out the impact of socioeconomic, demographic and environmental factors in the context of under five mortality. In this attempt we first analyzed our data using Kaplan-Meier non-parametric method of estimation of survival function and also using lifetable. We have also used Log-Rank test to compare different survival functions and found that sex, type of birth, religion, mothers’ education, birth order, maternity age, source of drinking water and region have statistically significant difference in the under five survival time. We have also used Cox proportional hazard model to identify the covariates which influence the under five mortality. But we found that our data do not fulfill the proportionality assumption of Cox proportional model in case of infant and child mortality. Then we applied stratified Cox proportional model to our data to find out the potential covariates which influence under five mortality and found birth order, mothers’ education level, sex, type of birth and the interaction of birth order and sex as vital factors for the deaths occurring under the age of five. The Cox proportional hazard models which were used separately for each stratum also identified mothers’ educational level, sex, type of birth, and the interaction of sex and water supply as the risk factors for the death of infants. Whereas for child stratum; type of birth, mothers’ education, sex and the interaction of water supply and sex were the risk factors associated with the death of children. Keywords: Under five mortality, maternal, socioeconomic and environmental factor.Download Full Article |
Editor’s Choice : Testing the Equivalence of Survival Distributions using PP- and PPP-Plots
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Abstract: This paper discusses the use of PP-plots for survival distributions where for a pair of survival distributions, one is plotted against the other. This is another way of visualizing the nature of the relationship between the two survival distributions along with typical Kaplan-Meier plots. For three survival distributions, the PPP-plot is introduced where the survival distributions are plotted against each other in three-dimensions. At the population level, measures of divergence between distributions are introduced based on areas and lengths associated with the PP- and PPP- plots. At the sample level, two test statistics are defined, based on these areas and lengths, to test the null hypothesis of equivalent survival curves. A simulation exercise showed that, overall, the new tests are worthy competitors to the log-rank and Wilcoxon tests and also to a Levine-type test and a Kolmogorov-Smirnov type test for the case of crossing survival curves. The paper also shows how the PP-plot can be used to estimate the hazard ratio and to assess the ratio of hazard functions if proportional hazards are not appropriate. Finally, the methods introduced are illustrated on two cancer data sets. Keywords: Crossing survival curves, Hazard ratio, Kaplan-Meier, Log-rank test, PP-plot, Wilcoxon test. |
