Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects

The purpose of this study is to highlight the application of sparse logistic regression models in dealing with prediction of tumour pathological subtypes based on lung cancer patients'' genomic information. We consider sparse logistic regression models to deal with the high dimensionality and correlation between genomic regions. In a hierarchical likelihood (HL) method, it is assumed that the random effects follow a normal distribution and its variance is assumed to follow a gamma distribution. This formulation considers ridge and lasso penalties as special cases. We extend the HL penalty to include a ridge penalty (called ‘HLnet’) in a similar principle of the elastic net penalty, which is constructed from lasso penalty. The results indicate that the HL penalty creates more sparse estimates than lasso penalty with comparable prediction performance, while HLnet and elastic net penalties have the best prediction performance in real data. We illustrate the methods in a lung cancer study.     

The Relationship Between Divorce and Children with AD/HD of Different Subtypes and Comorbidity: Results from a Clinically Referred Sample

This study investigated the relationship between divorce and the symptom profile of children with attention deficit/hyperactivity disorder (AD/HD). The files of 1,201 children from a pediatric practice in Sydney, Australia were used in this study. Children were aged 6 to 18 years, and were diagnosed with either the inattentive or combined type of AD/HD. Results show that 213 children had parents who were divorced. Children with the combined type, and especially boys with comorbid conduct disorder/oppositional defiant disorder (CD/ODD) were more common in the divorced group, and children of the inattentive type with comorbid learning disabilities were overrepresented in nondivorced families. Results suggest that divorce is associated with disruptive behavior patterns in children with AD/HD. The importance of including marital status as an important correlate in AD/HD treatment outcomes is discussed.     

A test for detecting etiologic heterogeneity in epidemiological studies

Current statistical methods for analyzing epidemiological data with disease subtype information allow us to acquire knowledge not only for risk factor-disease subtype association but also, on a more profound account, heterogeneity in these associations by multiple disease characteristics (so-called etiologic heterogeneity of the disease). Current interest, particularly in cancer epidemiology, lies in obtaining a valid p-value for testing the hypothesis whether a particular cancer is etiologically heterogeneous. We consider the two-stage logistic regression model along with pseudo-conditional likelihood estimation method and design a testing strategy based on Rao's score test. An extensive Monte Carlo simulation study is carried out, false discovery rate and statistical power of the suggested test are investigated. Simulation results indicate that applying the proposed testing strategy, even a small degree of true etiologic heterogeneity can be recovered with a large statistical power from the sampled data. The strategy is then applied on a breast cancer data set to illustrate its use in practice where there are multiple risk factors and multiple disease characteristics of simultaneous concern.     

美国教师职业倦怠的案例研究

20世纪60~70年代开始,美国的一批临床心理学家开始关注职业倦怠问题,90年代后职业倦怠研究扩展到教育领域。美国哥伦比亚大学教育心理学教授法泊提出教师职业倦怠有三种类型:情绪衰竭型、狂热型、能力富余型。不同类型的教师倦怠需要不同的应对策略,本文以情绪衰竭型教师为例,分析一个美国高中教师倦怠的表现及其应对策略。