The Decline of Barriers to Immigrant Economic and Political Rights in the American States: 1977–20011

State governments exercise significant powers to regulate the economic and social activities of resident aliens. We review the laws of the six leading states of immigrant settlement regulating access of noncitizens to 23 occupations, updating existing studies from 1946–77. Citizenship requirements for these occupations have plummeted, a change we attribute to federal court decisions, advisory opinions of state attorneys general, and state legislative and administrative action. There are numerous additional citizenship requirements in the statutes of the six states, although these appear to be poorly enforced. The authority of states to regulate their political communities is the most important remaining constitutionally valid basis of citizenship requirements. States define their political community broadly, leading to questionable exclusions of noncitizens from important activities.     

Testing How Management Matters in an Era of Government by Performance Management

Public administration finds itself in an era of government byperformance management, which is reflected in the widespreadassumption that management is a key determinant of performance,and that it is reasonable to expect managers to measurably improveorganizational effectiveness. This article joins a growing literaturein seeking to conceptualize and empirically test how externalenvironmental influences and internal management factors combineto create performance, relying on data from the 2002–2003National Administrative Studies Project (NASP-II) survey ofstate government health and human services officials. We categorizemanagerial efforts to facilitate organizational performanceas determined either through their interactions with the organizationalenvironment, or through employing workable levers to changeinternal organizational culture, structure, and technology.Among the external environmental variables we find that thesupport of elected officials and the influence of the publicand media have a positive impact on effectiveness. Among internalmanagement choices, the ability to create a developmental organizationalculture, establish a focus on results through goal clarity,and decentralize decision-making authority are all positivelyassociated with organizational effectiveness.     

Asymptotic bias in the linear mixed effects model under non-ignorable missing data mechanisms

Summary.  In longitudinal studies, missingness of data is often an unavoidable problem. Estimators from the linear mixed effects model assume that missing data are missing at random. However, estimators are biased when this assumption is not met. In the paper, theoretical results for the asymptotic bias are established under non-ignorable drop-out, drop-in and other missing data patterns. The asymptotic bias is large when the drop-out subjects have only one or no observation, especially for slope-related parameters of the linear mixed effects model. In the drop-in case, intercept-related parameter estimators show substantial asymptotic bias when subjects enter late in the study. Eight other missing data patterns are considered and these produce asymptotic biases of a variety of magnitudes.     

Sources of drug information among adolescent students

A sample of 1023 eighth and tenth grade students in small to medium-sized central Texas school districts was assessed to determine the amount of information they receive from ten sources about six categories of drugs. The amount of information males reported receiving about each drug category was significantly greater than what females reported, and the amount of information that eighth graders reported receiving about each drug category was significantly greater than what tenth graders reported. Television was the primary source of drug information for all categories of drugs except inhalants, for which friends and television were equally important sources. Parents and printed media (magazines or newspapers) were of secondary importance, followed by friends and teachers. Adolescents were less likely to receive drug-related information from experience, siblings, church, doctors, and police. The reliance on the mass media for drug information in smaller school districts is a pattern which has been previously observed in larger urban districts. This consistency suggests that mass media approaches to drug education are likely to be as effective in rural areas and smaller towns as they are among urban adolescents. Implications for television programming are discussed.     

Model Diagnostics for Remote Access Regression Servers

To protect public-use microdata, one approach is not to allow users access to the microdata. Instead, users submit analyses to a remote computer that reports back basic output from the fitted model, such as coefficients and standard errors. To be most useful, this remote server also should provide some way for users to check the fit of their models, without disclosing actual data values. This paper discusses regression diagnostics for remote servers. The proposal is to release synthetic diagnostics—i.e. simulated values of residuals and dependent and independent variables–constructed to mimic the relationships among the real-data residuals and independent variables. Using simulations, it is shown that the proposed synthetic diagnostics can reveal model inadequacies without substantial increase in the risk of disclosures. This approach also can be used to develop remote server diagnostics for generalized linear models.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.