Dropout Effects Research Articles

MCAR is not necessary for the complete cases to constitute a simple random subsample of the target sample

Missing data is the norm rather than the exception in complex epidemiological studies. Complete-case analyses, which discard all subjects with some data values missing, are known to be valid under the very restrictive assumption that the response mechanism is missing completely at random (MCAR). While conditions weaker than MCAR are known under which estimators of regression coefficients are unbiased, one often comes across the view in the literature that MCAR is necessary for the complete cases to form a simple random subsample of the target sample. In this paper, we explain why this is not the case, and we distill an assumption weaker than MCAR under which the simple random subsample condition holds, which we call available at random (AAR). Moreover, we show that, unlike MCAR, AAR response mechanisms can be missing not at random (MNAR). We also suggest how approximate AAR mechanisms might arise in practice through cancellation of selection and drop-out effects, and we conclude that before pooling partially complete and complete cases into an analysis, the investigator should consider how selection might impact on the representativeness of the cases included in the pooled analysis (compared to those comprising the complete cases only).

Adaptive reliable output tracking of networked control systems against actuator faults

This paper investigates the reliable adaptive observer-based output tracking control problem for a class of networked control systems subject to actuator faults and external disturbances via equivalent-input disturbance technique. Notably, the reliable control design based on adaptive mechanism is implemented to compensate the on-line actuator faults automatically and an observer-based controller is introduced through communication networks to drive the output of controlled plant to track the output of a reference model. Moreover, due to the effect of network-induced delays and packet dropouts in the controller-to-actuator channel, the inputs of controlled plant and observer-based tracking controller are updated in an asynchronous way. Then, based on the asynchronous characteristic, the resulting closed-loop networked control system is formulated with two interval time-varying delays for obtaining the required result. In particular, the equivalent-input disturbance approach improves the disturbance rejection performance and it does not require any prior knowledge of the disturbances. By constructing a suitable Lyapunov–Krasovskii functional and using free-weighting matrix approach, a new set of sufficient conditions for the solvability of the addressed problem is derived in terms of linear matrix inequalities. At last, the proposed result is validated through two numerical examples and also a comparison study is presented which shows the effectiveness of the developed control scheme over some existing conventional control schemes.

State Estimation of Networked System with Multiple Quantizers and Channel Packet Dropouts

This paper considers the effect of multiple quantizers and channel packet dropouts in state estimation of networked system. Taking into account the limit capacity of the quantizer, multiple quantizers in the networked system with respect to the multichannels are modeled firstly. In addition, channel packet dropouts with different packet loss probabilities in different channels are also proposed in this paper. To minimize the effect of the quantizers and the disturbances, state estimators are constructed under a given performance requirement. Finally, a simulation example is used to illustrate the effectiveness of the theoretical results.

Investigating the positive effects of packet dropouts on network-based [formula omitted] control for a class of linear systems

This paper investigates the positive effects of packet dropouts on network-based H∞ control for a linear system that cannot be stabilized by a non-delayed static output feedback controller, but can be stabilized by a delayed static output feedback controller. By intentionally inserting a lossy network between the system and the controller, and embedding a logical packet-selecting algorithm that produces some packet dropouts in the actuator module, the networked control system is modeled as a system with an interval time-delay, which is stable with some nonzero time-varying delay, but is unstable without a time-delay. By constructing a complete Lyapunov–Krasovskii functional and discretizing both the lower bound and the upper bound of the interval delay, some new delay-dependent criteria for H∞ performance and controller design are derived in terms of linear matrix inequalities. It is shown through an example that (i) proper packet dropouts can produce a stable control effect; (ii) utilizing the discretization of the lower delay bound can reduce the conservatism of the H∞ performance criterion; and (iii) the proposed design result is effective in achieving satisfactory H∞ control performance.

Teriflunomide for multiple sclerosis.

Teriflunomide for multiple sclerosis.

A Public Health Perspective on School Dropout and Adult Outcomes: A Prospective Study of Risk and Protective Factors From Age 5 to 27 Years

PurposeThis study aimed to advance a public health perspective on links between education and health by examining risk and protective factors that might alter the relation between dropping out of high school and subsequent negative outcomes. MethodsA community sample (N = 585) was followed from age 5 to 27 years. Data included self and parent reports, peer sociometric nominations, and observed mother-teen interactions. ResultsHigh school dropouts were up to four times more likely to experience individual negative outcomes (being arrested, fired, or on government assistance, using illicit substances, having poor health) by age 27 years and 24 times more likely compared to graduates to experience as many as four or more negative outcomes. Links between dropout and negative outcomes were more pronounced for individuals who were in low socioeconomic status families at age 5 years, rejected by elementary school peers, and became parents at a younger age; the dropout effect was decreased for individuals who had been treated for a behavioral, emotional, or drug problem by age 24 years. ConclusionsAddressing school dropout as a public health problem has the potential to improve the lives of dropouts and reduce societal costs of dropping out.

The ALSFRS as an outcome measure in therapeutic trials and its relationship to symptom onset

The reduction in ALS Functional Rating Score (ALSFRS) from reported symptom onset to diagnosis is used to estimate rate of disease progression. ALSFRS decline may be non-linear or distorted by drop-outs in therapeutic trials, reducing the reliability of change in slope as an outcome measure. The PRO-ACT database uniquely allows such measures to be explored using historical data from negative therapeutic trials. The decline of functional scores was analysed in 18 pooled trials, comparing rates of decline based on symptom onset with rates calculated between interval assessments. Strategies to mitigate the effects of trial drop-out were considered. Results showed that progression rate calculated by symptom onset underestimated the subsequent rate of disability accumulation, although it predicted survival more accurately than four-month interval estimates of δALSFRS or δFVC. Individual ALSFRS and FVC progression within a typical trial duration were linear. No simple solution to correct for trial drop-out was identified, but imputation using δALSFRS appeared least disruptive. In conclusion, there is a trade-off between the drive to recruit trial participants soon after symptom onset, and reduced reliability of the ALSFRS-derived progression rate at enrolment. The need for objective markers of disease activity as an alternative to survival-based end-points is clear and pressing.

AVANCEMOS: Effects of school dropout in the Home of Beneficiaries

The following paper shows the difference between the variables that explain school dropout in households in which at least one person is an AVANCEMOS beneficiary and in households where no member is. Furthermore, it seeks to demonstrate whether there is any effect on the program AVANCEMOS on siblings of a beneficiary in their decision to leave the educational system. Using The National Household Survey 2013 from INEC and through descriptive statistics and logistic models, we obtain results in which some variables that influence dropout such as area, quality of housing, basic services and gender have no influence in the same way households having AVANCEMOS or not. Meanwhile, age is always important for students when deciding to withdraw from the educational system regardless of the conditions of their home. Moreover, being 18 years old is a critical age since it represents a breaking point in the decision of the student to continue studying or not. If they come from an AVANCEMOS home, AVANCEMOS does not have any effect on siblings of beneficiaries of the program, but account to a higher proportion of students who leave school to go to work, 59.28%; against those who come from a home that does not participate in the program, which corresponds to a 48.35% of this population.

Robust quantized H∞ filtering for discrete-time uncertain systems with packet dropouts

This paper considers the problem of H∞ filtering for uncertain discrete-time systems with quantized measurements and packet dropouts. The time-invariant uncertain parameters are supposed to reside in a polytope. The system measurement outputs are quantized by a memoryless logarithmic quantizer before being transmitted to the filter and the performance of packet dropouts is described by Bernoulli random binary distribution. Attention is focused on the design of H∞ filter to mitigate the effects of quantization and packet dropouts, which ensured not only stochastically stability but also a prescribed H∞ noise attenuation level. Via parameter-dependent Lyapunov function approach and introducing some slack variables, sufficient conditions for the existence of an H∞ filter are expressed in terms of linear matrix inequalities (LMIs). Two examples are provided to demonstrate the effectiveness and applicability of the proposed method.

Does Classification of Chronic Musculoskeletal Disorder Patients Into Psychosocial Subgroups Predict Differential Treatment Responsiveness and 1-Year Outcomes After a Functional Restoration Program?

The objectives of this study: (1) to assess whether Multidimensional Pain Inventory (MPI) profiles predicted differential responses to a functional restoration program (FRP) in chronic disabling occupational musculoskeletal disorder (CDOMD) patients; (2) to examine whether coping style improves following FRP; and (3) to determine whether discharge MPI profiles predict discharge psychosocial and 1-year socioeconomic outcomes. Consecutive CDOMD patients (N=716) were classified into Adaptive Coper (AC, n=209), Interpersonally Distressed (ID, n=154), Dysfunctional (DYS, n=310), and Anomalous (n=43) using the MPI, and reclassified at discharge. Profiles were compared on psychosocial measures and 1-year socioeconomic outcomes. An intent-to-treat sample analyzed the effect of drop-outs on treatment responsiveness. The MPI classification significantly predicted program completion (P=0.001), although the intent-to-treat analyses found no significant effects of drop-out on treatment responsiveness. There was a significant increase in the number of patients who became AC or Anomalous at FRP discharge and a decrease in those who were ID or DYS. Patients who changed or remained as DYS at FRP discharge reported the highest levels of pain, disability, and depression. No significant interaction effect was found between MPI group and time for pain intensity or disability. All groups improved on psychosocial measures at discharge. DYS patients had decreased work retention and a greater health care utilization at 1 year. An FRP was clinically effective for CDOMD patients regardless of initial MPI profiles. The FRP modified profiles, with patients changing from negative to positive profiles. Discharge DYS were more likely to have poor 1-year outcomes. Those classified as Anomalous had a good prognosis for functional recovery similar to ACs.

Distributed state estimation for stochastic non‐linear systems with random delays and packet dropouts

A novel distributed fusion Kalman filter is proposed for a class of stochastic non-linear systems with multi-step transmission delays and packet dropouts. The stochastic non-linearities described by statistical means enter into both state equation and measurement equation, and some Bernoulli distributed random variables are introduced to model the delayed measurements. Using the measurement reorganisation approach instead of state augmentation, the addressed system is transformed into a delay-free one. For each subsystem, the optimal local estimators are designed via the innovation analysis method. The filtering error cross-covariance matrices between any two local filters are then obtained. On this basis, a distributed fusion filter is derived by means of matrix-weighted fusion estimation criterion. The effects of stochastic non-linearities, random delays and packet dropouts on the performance of the filter are all considered in the proposed algorithms. Moreover, some sufficient conditions that guarantee the convergence of the estimation error covariance matrices are established. Finally, a numerical example is given to illustrate the effectiveness of the developed algorithms.

The long-term effects of school dropout and GED attainment on substance use disorders

BackgroundEpidemiologic research suggests that 14% of the population do not complete high school, and dropout has been linked to mental health conditions, substance use, chronic health problems, and criminal behavior. Few studies have assessed whether attainment of the general education development (GED) credential is protective from substance use. PurposeTo assess the long-term outcomes of school dropout and GED attainment on past year substance use disorders, age of onset, and current smoking status. MethodsLongitudinal data were included for lifetime substance users who participated in the National Epidemiological Survey on Alcohol and Related Conditions (Waves I and II). Eligible participants (N=30,608) were classified as having completed high school, dropped out of high school and did not complete a GED, or completed GED at Wave I. Survey logistic regression analyses were used to determine whether high school graduation status was associated with substance use disorders and smoking at Wave II. ResultsMultivariate results suggest that participants who dropped out of high school (OR=1.53; p<.01) or attained a GED were more likely to have a past year marijuana use disorder (OR=1.62 p<.01) compared to high school graduates. High school dropouts were also more likely to be current smokers (OR=1.88; p<.05) than graduates. ConclusionsHigh school dropouts have higher long-term rates of marijuana use disorder and smoking in adulthood than graduates. Attainment of a GED does not appear to be protective from marijuana use disorders in adulthood.

Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies.

Effect of multiple allelic drop-outs in forensic RMNE calculations

Technological advances such as massively parallel sequencing enable increasing amounts of genetic information to be obtained from increasingly challenging samples. Certainly on low template, degraded and multi-contributor samples, drop-outs will increase in number for many profiles simply by analyzing more loci, making it difficult to probabilistically assess how many drop-outs have occurred and at which loci they might have occurred. Previously we developed a Random Man Not Excluded (RMNE) method that can take into account allelic drop-out while avoiding detailed estimations of the probability that drop-outs have occurred, nor making assumptions about at which loci these drop-outs might have occurred. The number of alleles that have dropped out, does not need to be exactly known. Here we report a generic Python algorithm to calculate the RMNE probabilities for any given number of loci. The number of allowed drop-outs can be set between 0 and twice the number of analyzed loci. The source code has been made available on https://github.com/fvnieuwe/rmne. An online web-based RMNE calculation tool has been made available on http://forensic.ugent.be/rmne. The tool can calculate these RMNE probabilities from a custom list of probabilities of the observed and non-observed alleles from any given number of loci. Using this tool, we explored the effect of allowing allelic drop-outs on the evidential value of random forensic profiles with a varying number of loci. Our results give insight into how the number of allowed drop-outs affects the evidential value of a profile and how drop-out can be managed in the RMNE approach.

Towards dropout training for convolutional neural networks

Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage.

Input-to-state stability for networked control system with predictive scheme

This paper studies the input-to-state stability (ISS) problem for a class of networked control systems (NCSs). The improved varying controller gain predictive scheme is used to compensate the effects of network-induced delays and packet dropouts. By introducing a new auxiliary variable and analyzing the relationship of the network-induced delays and packet dropouts between two consecutive sampling instants, the considered networked control system (NCS) is converted into a coupled switched system. Based on the small gain theorem, a novel stability criterion is proposed to guarantee the ISS property of the considered system. Compared with existing works in literature, the stability criterion obtained here is easier to test and is much less conservative. A numerical simulation is presented to show the effectiveness of the proposed method.

DISTINCTIVE FEATURES OF HYDRODYNAMIC INVESTIGATION OF GAS-CONDENSATE WELLS

An equation is proposed for constructing a theoretical pressure build-up curve, which takes into account the effect of the well storage capacity, skin effect and presence of condensate in the bottomhole zone. A method was developed to determine the pressure variation during the gas-condensate well inflow and pressure build-up test, that reflects the effects of condensate dropout and retrograde transition to the gaseous phase.

Dimethyl fumarate for multiple sclerosis.

Multiple sclerosis (MS) often leads to severe neurological disability and a serious decline in quality of life. The ideal target of disease-modifying therapy for MS is to prevent disability worsening and improve quality of life. Dimethyl fumarate is considered to have an immunomodulatory activity and neuroprotective effect. It has been approved by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency as a first-line therapy for adult patients with relapsing-remitting MS (RMSS). To assess the benefit and safety of dimethyl fumarate as monotherapy or combination therapy versus placebo or other approved disease-modifying drugs (interferon beta, glatiramer acetate, natalizumab, mitoxantrone, fingolimod, teriflunomide, alemtuzumab) for patients with MS. The Trials Search Co-ordinator searched the Trials Specialised Register of the Cochrane Multiple Sclerosis and Rare Diseases of the Central Nervous System Group (4 June 2014). We checked reference lists of published reviews and retrieved articles and searched reports (2004 to June 2014) from the MS societies in Europe and America. We also communicated with investigators participating in trials of dimethyl fumarate and the Biogen Idec Medical Information. We included randomised, controlled, parallel-group clinical trials (RCTs) with a length of follow-up equal to or greater than one year evaluating dimethyl fumarate, as monotherapy or combination therapy, versus placebo or other approved disease-modifying drugs for patients with MS without restrictions regarding dosage, administration frequency and duration of treatment. We used the standard methodological procedures of The Cochrane Collaboration. Two review authors independently assessed trial quality and extracted data. Disagreements were discussed and resolved by consensus among the review authors. We contacted the principal investigators of included studies for additional data or confirmation of data. Two RCTs were included, involving 2667 adult patients with RRMS to evaluate the efficacy and safety of two dosages of dimethyl fumarate (240 mg orally three times daily or twice daily) by direct comparison with placebo for two years. Among them, a subsample of 1221 (45.8%) patients were selected to participate in MRI evaluations by each study site with MRI capabilities itself. No powered head-to-head study with an active treatment comparator has been found. Meta-analyses showed that dimethyl fumarate both three times daily and twice daily reduced the number of patients with a relapse (risk ratio (RR) 0.57, 95% confidence interval (CI) 0.50 to 0.66, P < 0.00001 and 0.64, 95% CI 0.54 to 0.77, P < 0.00001, respectively) or disability worsening (RR 0.70, 95% CI 0.57 to 0.87, P = 0.0009 and 0.65, 95% CI 0.53 to 0.81, P = 0.0001, respectively) over two years, compared to placebo. The treatment effects were decreased in the likely-case scenario analyses taking the effect of dropouts into consideration. Both dosages also reduced the annualised relapse rate. Data of active lesions on MRI scans were not combined because there was a high risk of selection bias for MRI outcomes and imprecision of MRI data in both studies, as well as an obvious heterogeneity between the studies. In terms of safety profile, both dosages increased the risk for adverse events and the risk for drug discontinuation due to adverse events. The most common adverse events included flushing and gastrointestinal events (upper abdominal pain, nausea and diarrhoea). Uncommon adverse events included lymphopenia and leukopenia, but they were more likely to happen with dimethyl fumarate than with placebo (high dosage: RR 5.25, 95% CI 2.20 to 12.51, P = 0.0002 and 5.23, 95% CI 2.47 to 11.07, P < 0.0001, respectively; low dosage: RR 5.69, 95% CI 2.40 to 13.46, P < 0.0001 and 6.53, 95% CI 3.13 to 13.64, P < 0.00001, respectively). Both studies had a high attrition bias resulting from the unbalanced reasons for dropouts among groups. Quality of evidence for relapse outcome was moderate, but for disability worsening was low. There is moderate-quality evidence to support that dimethyl fumarate at a dose of 240 mg orally three times daily or twice daily reduces both the number of patients with a relapse and the annualised relapse rate over two years of treatment in comparison with placebo. However, the quality of the evidence to support the benefit in reducing the number of patients with disability worsening is low. There is no high-quality data available to evaluate the benefit on MRI outcomes. The common adverse effects such as flushing and gastrointestinal events are mild-to-moderate for most patients. Lymphopenia and leukopenia are uncommon adverse events but significantly associated with dimethyl fumarate. Both dosages of dimethyl fumarate have similar benefit and safety profile, which supports the option of low-dose administration. New studies of high quality and long-term follow-up are needed to evaluate the benefit of dimethyl fumarate on prevention of disability worsening and to observe the long-term adverse effects including progressive multifocal leukoencephalopathy.

Economic Effects of Student Dropouts: A Comparative Study

In global perspective, it is an incontestable fact that the progress of a nation is highly dependent on the education of their citizens. Education plays a central role and has a cross cutting impact on all aspects of human life. It is a vital investment for human and economic development. The main purpose of this study is to explore the causes of students drop outs and their impact on economy. This research find outs the reasons of dropouts in Pakistan and more importantly comparative analysis of the causes of students dropouts globally. The findings of this study are drawn from the extensive literature review of students’ dropout in different countries. Financial problems, parents’ unwillingness, distance and lack of basic facilities, bad quality of the education, inadequate school environment and building, overloaded class rooms, improper languages of teaching, carelessness of teachers and security problem in girls school are found as major causes of student dropouts in different countries. This study also find outs the effects of students dropouts on economy and suggest some remedial measures to reduce students’ dropouts. Study also has some policy implications for policy makers to combat this problem, such as free education program, curriculum adjustment, teachers training workshops, provision of all facilities in schools.

Many Dropouts? Never Mind! – Employment Prospects of Dropouts from Training Programs

The employment effects of training programs for the unemployed are frequently studied, but little is known about the number, the characteristics, and the labor market prospects of those who drop out of these programs. The aim of this paper is to contribute to filling this gap. Dropouts are identified in German administrative data. The medium- and long-term effect of dropout is estimated using a bivariate dynamic random effects probit model which takes into account state dependence and selection on unobservables. The model is estimated with Markov Chain Monte Carlo (MCMC) methods.