A time-varying measurement error model for age of onset of a psychiatric diagnosis: applied to first depressive episode diagnosed by the Composite International Diagnostic Interview (CIDI)

A substantial degree of uncertainty exists surrounding the reconstruction of events based on memory recall. This form of measurement error affects the performance of structured interviews such as the Composite International Diagnostic Interview (CIDI), an important tool to assess mental health in the community. Measurement error probably explains the discrepancy in estimates between longitudinal studies with repeated assessments (the gold-standard), yielding approximately constant rates of depression, versus cross-sectional studies which often find increasing rates closer in time to the interview. Repeated assessments of current status (or recent history) are more reliable than reconstruction of a person's psychiatric history based on a single interview. In this paper, we demonstrate a method of estimating a time-varying measurement error distribution in the age of onset of an initial depressive episode, as diagnosed by the CIDI, based on an assumption regarding age-specific incidence rates. High-dimensional non-parametric estimation is achieved by the EM-algorithm with smoothing. The method is applied to data from a Norwegian mental health survey in 2000. The measurement error distribution changes dramatically from 1980 to 2000, with increasing variance and greater bias further away in time from the interview. Some influence of the measurement error on already published results is found.     

A fleshpeddler at work: Power,pain, and profit in the prizefighting economy

Theory and Society -     

膨润土常用性能指标的测定分析方法

本文对膨润土常用性能指标的分析测试方法作了系统介绍,主要包括吸兰量、胶质价、活性度、游离酸、脱色率、水分、粒度等的测定方法。     

Supplementing a survey with respondent Twitter data to measure e-cigarette information exposure

ABSTRACT

Social media data are increasingly used by researchers to gain insights on individuals’ behaviors and opinions. Platforms like Twitter provide access to individuals’ postings, networks of friends and followers, and the content to which they are exposed. This article presents the methods and results of an exploratory study to supplement survey data with respondents’ Twitter postings, networks of Twitter friends and followers, and information to which they were exposed about e-cigarettes. Twitter use is important to consider in e-cigarette research and other topics influenced by online information sharing and exposure. Further, Twitter metadata provide direct measures of user’s friends and followers as opposed to survey self-reports. We find that Twitter metadata provide similar information to survey questions on Twitter network size without inducing recall error or other measurement issues. Using sentiment coding and machine learning methods, we find Twitter can elucidate on topics difficult to measure via surveys such as online expressed opinions and network composition. We present and discuss models predicting whether respondents’ tweet positively about e-cigarettes using survey and Twitter data, finding the combined data to provide broader measures than either source alone.     

Structural reforms and labor markets in Argentina

Argentina is considered to be one of the most successful cases of structural reforms in Latin America, because of the extent and rapid pace of the reforms after the hyperinflationary process of 1989–1990. At the beginning of 1991, the convertible plan was launched and inflation fell sharply. However, even when the economy is growing fast, the problems in the labor market seem to worsen. Unemployment and underemployment have risen, and an increasing number of people have fallen out of normal work. The article analyzes how changes in labor markets are closely related to the transformation process in the economic system. After a summary of the situation before the crisis of the 1980s, the article analyzes the stabilization plans applied and then discusses the current dynamics of labor markets and the policies implemented to change labor regulations. Finally, some hypotheses about future scenarios are presented.     

Assessing job self-efficacy and organizational commitment considering a mediating role of information asymmetry

This study establishes a model by drawing from key postulates and findings under information asymmetry to explain the formation of organization commitment and job self-efficacy. In the proposed model, organizational commitment and job self-efficacy are influenced indirectly by social support, knowledge creation, and information intensity via the mediation of decision-making quality and perceived opportunism. Knowledge creation is influenced directly by both social support and information intensity. Empirical testing of this model, by investigating personnel from firms in one of Taiwan's well-known industrial zones, confirms the applicability of information asymmetry in understanding employees’ organizational commitment and job self-efficacy. The test results indicate that all the model paths except one (linking perceived opportunism and job self-efficacy) are significant. Finally, the research provides managerial implications and limitations.