London Joint Share Clubs

L. Strashun

"Joint Share Clubs", London

L. Straschun

Joint Attention in Young Children with Autism

Autism spectrum disorders (ASDs) are classified as pervasive developmental disorders characterized by social, communicative, and behavioral impairments. According to formal and informal reports, children with ASD present with receptive and expressive language delay. Joint attention (JA: the behavior that occurs when two individuals focus on the same object or event) has been identified as a possible marker of delayed language development in children with ASD. In this study, the JA behaviors in children with ASD were contrasted with initially language-matched typically developing (TYP) children across three visits. Measures of language, the frequency, duration, and source of initiation of JA episodes, and the choice of toy during those episodes, were coded. Across visits and groups, mothers initiated more JA episodes than children; however, typical children also initiated more JA episodes than ASD children at visits 1 and 2. Also, the total duration of typically developing children’s JA episodes was generally longer than that of the ASD children’s, significantly so at Visit 2. Significant associations emerged between children’s vocabulary and two measures of JA: frequency and number of maternal initiations. Teaching parents to incorporate JA training in their interactions with their children may likely help children with ASD acquire language.

Bayesian joint modeling of longitudinal and survival data

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. ^

Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

Joint effects of pulmonary function and aerobic power on survival in a cohort of healthy adults

Objective measurements of physical fitness and pulmonary function are related individually to long-term survival, both in healthy people and in those who are ill. These factors are furthermore known to be related to one another physiologically in people with pulmonary disease, because advanced pulmonary disease causes ventilatory limitation to exercise. Healthy people do not have ventilatory limitation to exercise, but rather have ventilatory reserve. The relationship between pulmonary function and exercise performance in healthy people is minimal. Exercise performance has been shown to modify the effect of pulmonary function on mortality in people with chronic obstructive pulmonary disease, but the relationship between these factors in healthy people has not been studied and is not known. The purpose of this study is to quantify the joint effects of pulmonary function and exercise performance as these bear on mortality in a cohort of healthy adults. This investigation is an historical cohort study over 20 years of follow-up of 29,624 adults who had complete preventive medicine, spirometry and treadmill stress examinations at the Cooper Clinic in Dallas, Texas.^ In 20 years of follow-up, there were 738 evaluable deaths. Forced expiratory volume in one second (FEV$\sb1$) percent of predicted, treadmill time in minutes percent of predicted, age, gender, body mass index, baseline smoking status, serum glucose and serum total cholesterol were all significant, independent predictors of mortality risk. There were no frank interactions, although age had an important increasing effect on the risk associated with smoking when other covariates were controlled for in a proportional-hazards model. There was no confounding effect of exercise performance on pulmonary function. In agreement with the pertinent literature on independent effects, each unit increase in FEV$\sb1$ percent predicted was associated with about eight tenths of a percent reduction in adjusted mortality rate. The concept of physiologic reserve is useful in interpretation of the findings. Since pulmonary function does not limit exercise tolerance in healthy adults, it is reasonable to expect that exercise tolerance would not modify the effect of pulmonary function on mortality. Epidemiologic techniques are useful for elucidating physiological correlates of mortality risk. ^

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

International Collection of JGOFS (Joint Global Ocean Flux Study), Volume 2: Integrated Data Sets (1989-2003)

The JGOFS International Collection Volume 2: Integrated Data Sets CD is a coherent, organised compilation of existing data sets produced by member countries which participated in JGOFS. In most cases, the data were gathered from the JGOFS International Collection, Volume 1: Discrete Datasets DVD. To produce Vol. 1 data were taken from the original sources and copied "as is" on the DVD. For Vol. 2 data and metadata have been harmonized using the conversion software PanTool and the import routine of PANGAEA checking for completeness of metadata and defining the relations between data and metadata. Prior to the import, data had performed a technical quality control, i.e. format and readability of the file, availability and combination of parameters and units, range of values.

Design Patterns in Software Maintenance: An Experiment Replication at UPM - Experiences with the RESER'11 Joint Replication Project

Replication of software engineering experiments is crucial for dealing with validity threats to experiments in this area. Even though the empirical software engineering community is aware of the importance of replication, the replication rate is still very low. The RESER'11 Joint Replication Project aims to tackle this problem by simultaneously running a series of several replications of the same experiment. In this article, we report the results of the replication run at the Universidad Politécnica de Madrid. Our results are inconsistent with the original experiment. However, we have identified possible causes for them. We also discuss our experiences (in terms of pros and cons) during the replication.