Title: CAUSAL INFERENCE WITH GROUPBASED TRAJECTORIES AND PROPENSITY SCORE MATCHING: IS HIGH SCHOOL DROPOUT A TURNING POINT? Gary Allen Sweeten, Ph.D., 2006 Dissertation directed by: Professor Shawn D. Bushway Department of Criminology and Criminal Justice Life course criminology focuses on trajectories of deviant or criminal behavior punctuated by turning point events that redirect trajectories...

BACKGROUND Chemoprevention crossover trials of tea can be more efficient than parallel designs but the attrition and compliance rates with such trials are unknown. METHODS Attrition (dropouts) and compliance with treatment were assessed in a 25-week randomized, placebo controlled, crossover, feasibility clinical trial of four tea treatments to investigate the effect of tea on oral cancer biom...

BACKGROUND Addiction treatment faces high pretreatment and treatment dropout rates, especially among Aboriginals. In this study we examined characteristic differences between Aboriginal and non-Aboriginal clients accessing an inpatient medical withdrawal management program, and identified risk factors associated with the probabilities of pretreatment and treatment dropouts, respectively. METH...

Allelic dropout is a commonly observed source of missing data in microsatellite genotypes, in which one or both allelic copies at a locus fail to be amplified by the polymerase chain reaction. Especially for samples with poor DNA quality, this problem causes a downward bias in estimates of observed heterozygosity and an upward bias in estimates of inbreeding, owing to mistaken classifications o...

Randomized longitudinal clinical trials are the gold standard to evaluate the effectiveness of interventions among different patient treatment groups. However, analysis of such clinical trials becomes difficult in the presence of missing data, especially in the case where the study endpoints become difficult to measure because of subject dropout rates or/and the time to discontinue the assigned...

We explore the use of neural networks trained with dropout in predicting epileptic seizures from electroencephalographic data (scalp EEG). The input to the neural network is a 126 feature vector containing 9 features for each of the 14 EEG channels obtained over 1-second, non-overlapping windows. The models in our experiments achieved high sensitivity and specificity on patient records not used...

In this paper, we explore student dropout behavior in Massive Open Online Courses(MOOC). We use as a case study a recent Coursera class from which we develop a survival model that allows us to measure the influence of factors extracted from that data on student dropout rate. Specifically we explore factors related to student behavior and social positioning within discussion forums using standar...

BACKGROUND School dropout is a persisting problem with major socioeconomic consequences. Although poor health probably contributes to pathways leading to school dropout and health is likely negatively affected by dropout, these issues are relatively absent on the public health agenda. This emphasises the importance of integrative research aimed at identifying children at risk for school dropout...

Training deep belief networks (DBNs) requires optimizing a non-convex function with an extremely large number of parameters. Naturally, existing gradient descent (GD) based methods are prone to arbitrarily poor local minima. In this paper, we rigorously show that such local minima can be avoided (upto an approximation error) by using the dropout technique, a widely used heuristic in this domain...