Using information on realized effects to determine prospective causal effects

The potential outcomes approach to causal inference postulates that each individual has a number of possibly latent outcomes, each of which would be observed under a different treatment. For any individual, some of these outcomes will be unobservable or counterfactual. Information about post-treatment characteristics sometimes allows statements about what would have happened if an individual or group with these characteristics had received a different treatment. These are statements about the realized effects of the treatment. Determining the likely effect of an intervention before making a decision involves inference about effects in populations defined only by characteristics observed before decisions about treatment are made. Information on realized effects can tighten bounds on these prospectively defined measures of the intervention effect. We derive formulae for the bounds and their sampling variances and illustrate these points with data from a hypothetical study of the efficacy of screening mammography.     

留住高绩效员工!——企业必须像管理资产那样对待人力资本

近几年来，企业界兴起了“新型工作合约”，其主题是员工对自己的工作负责，企业为员工提供培训、晋升等各种机会。但无论对企业还是对员工来说，这种合约都没有发挥出应有的作用。领导者对如何在经济动荡时期留住高绩效员工知之甚少。     

Detecting interaction links in a collaborating group using manually annotated data

Identification of network linkages through direct observation of human interaction has long been a staple of network analysis. It is, however, time consuming and labor intensive when undertaken by human observers. This paper describes the development and validation of a two-stage methodology for automating the identification of network links from direct observation of groups in which members are free to move around a space. The initial manual annotation stage utilizes a web-based interface to support manual coding of physical location, posture, and gaze direction of group members from snapshots taken from video recordings of groups. The second stage uses the manually annotated data as input for machine learning to automate the inference of links among group members. The manual codings were treated as observed variables and the theory of turn taking in conversation was used to model temporal dependencies among interaction links, forming a Dynamic Bayesian Network (DBN). The DBN was modeled using the Bayes Net Toolkit and parameters were learned using Expectation Maximization (EM) algorithm. The Viterbi algorithm was adapted to perform the inference in DBN. The result is a time series of linkages for arbitrarily long segments that utilizes statistical distributions to estimate linkages. The validity of the method was assessed through comparing the accuracy of automatically detected links to manually identified links. Results show adequate validity and suggest routes for improvement of the method.     

Abortion costs, sexual behavior, and pregnancy rates

This paper empirically examines the question: Do the direct (price) and indirect (restrictive abortion laws) costs of obtaining an abortion have an impact on the likelihood of women becoming pregnant? Using the economic model of fertility control, the empirical results find that increases in the real price of obtaining an abortion cause a statistically and numerically significant decrease in the pregnancy rate of all women of childbearing age (15–44 years) and teens (ages 15–19). A state parental involvement law is also found to decrease the pregnancy rate of all women of childbearing age and an even numerically larger decrease for teens. A state Medicaid funding restriction of abortion, waiting period law, and mandatory counseling law do not have a statistically significant impact on the pregnancy rate of either group. Taken together the empirical results are consistent with the hypothesis that women's sexual behavior is influenced by the direct and indirect cost of obtaining an abortion.     

The impact of tax rates, political partisanship and economic variables on the distribution of state and local tax burdens

This study finds that the effective state and local tax rate for the top 1% of income households as a percentage of the effective state and local tax rate for the bottom 20% of income households in 2002 is significantly influenced by whether a state has a multi-rate income tax, right-to-work laws, the liberalism of a state's electorate, the average tax burden in a state and past tax policy. Democratic Party strength in state government, Republican or Democratic Party institutional control of state government, change in real per capita income, a Democratic Governor and the change in the share of income going to the top 1% of income households are not significant predictors. The empirical results are identical for the top 2-5% of income households to the bottom 20% of income households.     

为自己打广告

如果不能把产品信息传递给购买人群的话，开发出再好的新产品也毫无意义。你必须告诉人们：“嘿，我来了”，然后给他们一个关注你的理由。同样道理，当你准备启动一项重大的个人项目时，也应该遵循同样的逻辑。别忘了，你是在创造一个全新的自我。如果不发起一轮宣传攻势的话，你觉得你的同事们会买账吗？     

高效管理知识型员工——以员工的愿望和需求为出发点来领导

当今,要管理有着各自专业造诣的人才,领导者得具备特别的管理能力。不过,这可不是你通常会联想到的那些技能噢!一般而言,知识型员工对于自己的本职工作,懂得的都比你多。那么,你要如何管理这些专业知识比你丰富的员工呢？     

a study of the generalized tukey lambda family

The Tukey lambda family of distributions together with its extensions have played an important role in statistical practice. In this paper a con¬tinuously defined two-parameter generalization of this family, which holds promise of a variety of additional applications, is variously studied. The coefficients of skewness and kurtosis and the density shapes of its members are examined and the family is related to the classical Pearsonian system of distributions.