ObjectiveThe objective of the CARRECT software is to make cutting edge statistical methods for reducing bias in epidemiological studies easy to use and useful for both novice and expert users. IntroductionAnalyses produced by epidemiologists and public health practitioners are susceptible to bias from a number of sources including missing data, confounding variables, and statistical model selection. It often requires a great deal of expertise to understand and apply the multitude of tests, corrections, and selection rules, and these tasks can be time-consuming and burdensome. To address this challenge, Aptima began development of CARRECT, the Collaborative Automation Reliably Remediating Erroneous Conclusion Threats system. When complete, CARRECT will provide an expert system that can be embedded in an analysts workflow. CARRECT will support statistical bias reduction and improved analyses and decision making by engaging the user in a collaborative process in which the technology is transparent to the analyst.MethodsOlder approaches to imputing missing data, including mean imputation and single imputation regression methods, have steadily given way to a class of methods known as multiple imputation (hereafter MI; Rubin 1987). Rather than making the restrictive assumption that the data are missing completely at random (MCAR), MI typically assumes the data are missing at random (MAR). There are two key innovations behind MI. First, the observed values can be useful in predicting the missing cells, and thus specifying a joint distribution of the data is the first step in implementing the models. Second, single imputation methods will likely fail not only because of the inherent uncertainty in the missing values but also because of the estimation uncertainty associated with generating the parameters in the imputation procedure itself. By contrast, drawing the missing values multiple times, thereby generating m complete datasets along with the estimated parameters of the model properly accounts for both types of uncertainty (Rubin 1987; King et al. 2001). As a result, MI will lead to valid standard errors and confidence intervals along with unbiased point estimates.In order to compute the joint distribution, CARRECT uses a bootstrapping-based algorithm that gives essentially the same answers as the standard Bayesian Markov Chain Monte Carlo (MCMC) or Expectation Maximization (EM) approaches, is usually considerably faster than existing approaches and can handle many more variables. ResultsTests were conducted on one of the proposed methods with an epidemiological dataset from the Integrated Health Interview Series (IHIS) producing verifiably unbiased results despite high missing rates. In addition, mockups (Figure 1) were created of an intuitive data wizard that guides the user through the analysis processes by analyzing key features of a given dataset. The mockups also show improve the handling of imperfect datasets, as well as the selection of the most appropriate algorithms and models. ConclusionsOur approach and program were designed to make bias mitigationmuch more accessible to much more than only the statistical elite. We hope that it will have a wide impact on reducing bias in epidemiological studies and provide more accurate information to policymakers.

This paper examined the National Health Interview Survey (NHIS) 2007 and explored acupuncture users sociodemographics characteristics, reasons and the nature of acupuncture use, and the relationship of such use with conventional medical care. All individuals who completed adults core interviews (N = 23,393) were included. Three subsets of samples (nonuser, former user, and recent user) were used in the analysis performed in Stata. Our findings revealed that ever acupuncture user (including former and recent user) increased from 4.2% to 6.3% of the population, representing 8.19 million and 14.01 million users in 2002 and 2007, respectively. We expected this trend to continue. People not only used acupuncture as a complementary and alternative approach to conventional treatment for a specific health condition, but also used it as a preventive means to promote general health. Effectiveness and safety appeared not to be the main predictors of acupuncture use; rather, awareness, cost, and insurance coverage played a bigger role in decision making.

Unlike southern freedmen, former slaves in the Cherokee Nation had the opportunity to claim free land after they were emancipated. In previous work, I found that their access to free land was associated with higher levels of average income and wealth than that of southern freedmenand lower levels of racial inequality than in the postbellum South. In this paper, I look more closely at a linked sample of three cohorts of Cherokee freedmen families to examine the extent to which individuals and their descendents were able to maintain high levels of income and wealth. I also examine potential mechanisms by which the economic success of Cherokee freedmen in 1880 could be transmitted to their children and grandchildren. I find remarkable persistence in economic status of those who were adults in both 1880 and 1900. Additionally, I find that the next generation of Cherokee freedmen largely exhibited the ability to either maintain or improve their social status vis-a-vis their parents. Evidence suggests that one mechanism through which parental income and wealth was transmitted across generations was related to human capital acquisition. The children and grandchild of freedmen in the upper income quartile in 1880 were more likely to be literate or attend school than the children and grandchildren of freedmen in the lower income quartile.

The wage gap between whites and blacks is substantial in the US. Even when controlling for measured individual characteristics in human capital, studies have shown that a significant residual wage gap remains and is partly due to labor-market discrimination. Charles and Guryan(2008) find that one-quarter of the residual racial wage gap is due to prejudice. However, their empirical specification considers only employer discrimination and therefore does not take into account the existence of consumer discrimination. I add this source of discrimination in adding another discriminatory force : the proportion of jobs in contact with the public. I also construct consistent local labor markets to analyze the interaction between blacks and prejudiced jobs and employers. Using the 1960-2000 Integrated Public Use Microdata Series (IPUMS), the GeneralSocial Survey (GSS) and the Occupational Information Network (O*NET), I show that the racial wage differential responds positively to the relative supply of contact jobs and the proportion of prejudiced individuals in the local population. My empirical results put forward evidence ofcustomer discrimination in the US labor market.

Since the trough of our most recent recession, the unemployment rate has began to decline slowly. However, unlike any other recession, the average number of weeks the unemployed remain without a job continues to increase. The lack of correlation has left many perplexed as to how the 2007-2009 recession differs from previous recessions. This paper investigates how unemployment transition rates during the 2007-2009 recession changed in the presence of observable and unobservable heterogeneity compared to previous recessions. Using data from the Current Population Survey and a separated markets approach, the hazard rate for various types of people is estimated using maximum likelihood estimation. Furthermore, I estimate the average lengths of unemployment for various groups of people and the proportion of people falling into these groups to see if the lengths and proportions have changed. Results show that for some types of people the hazard rate has considerably changed compared to previous recessions. Additionally, the findings suggest that while lengths of unemployment for various groups of people have remained unchanged, the proportions of people falling into these groups have changed during our most recent recession.

Problem, research strategy, and findings: Metropolitan planning organizations attempt to shape urban form at the regional and metropolitan scale, including the pattern of suburban centers. How do these efforts change behavior? Our study informs that question by way of a new family of urban form metrics summarizing the polycentric structure of U.S. metropolitan areas. Using a spatial statistical approach, these measures are sensitive to the size, amount, and location of suburban centers. The article then tests the influence of these structures on commute times nationally from 1970 to 2000. Takeaway for practice: The influence of development densities on travel in sprawling regions is more complicated than previously understood or measured. While the level of both neighborhood density and regional density explain average commuting times, density also works relatively. The spatial variation of density, the density of suburban centers relative to the region, and the spatial distribution of high-density nodes each appear to play distinct roles in influencing travel. Research support: Centers for Disease Control and Prevention, and Institute for Bioscience and Biomedical Engineering.

Nearly half of U.S. employers test job applicants and workers for drugs. I use variation in the timing and nature of drug testing regulation to study discrimination against blacks related to perceived drug use. Black employment in the testing sector is suppressed in the absence of testing, consistent with ex ante discrimination on the basis of drug use perceptions. Adoption of pro-testing legislation increases black employment in the testing sector by 7-30% and relative wages by 1.4-13.0%, with the largest shifts among low skilled black men. Results suggest that employers substitute white women for blacks in the absence of testing.

ObjectivesThe aim of this study was to determine if changes in annual temperature influence the prevalence of frequent otitis media (FOM) and respiratory allergy in children.MethodsAnnual prevalence data for FOM (defined as 3 or more ear infections per year), respiratory allergy, and seizures (nonrespiratory, control condition) in children were extracted from the National HealthInterview Survey for 1998 to 2006. Average US annual temperatures for the same period were recorded from the Environmental Protection Agency. Complex samples logistic regression analyses were performed to identify possible correlations between annual temperature and each of the 3 disease conditions, controlling for age and sex.ResultsA total of 113 067 children were studied (mean age, 8.6 years; 51.1% girls). Overall prevalences (95% confidence interval) were 6.3% 0.2%, 11.8% 0.2%, and 0.7% 0.1% for FOM, respiratory allergy, and seizures (nonrespiratory, control condition), respectively. Average annual temperatures ranged from 53.64F to 55.09F. Regression analysis found that annual temperature did not influence the prevalence of FOM (P = .681); male sex and younger age were associated with a higher prevalence of FOM (P = .025 and P < .001, respectively). Similarly, annual temperature did not influence prevalence of respiratory allergy (P = .883); male sex and increasing age were associated with a higher prevalence of respiratory allergy (both P < .001). Annual temperature and sex did not influence seizure prevalence; however, increasing age was negatively associated.ConclusionsChanges in average annual temperature do not appear to influence the prevalence of otitis media or respiratory allergy. This negative finding suggests that although global warming continues to affect our environment, childhood otolaryngologic disease prevalence may not be directly influenced.

Microdata protection is a hot topic in the field of Statistical Disclosure Control, which has gained special interest after the disclosure of 658,000 queries by the America Online (AOL) search engine in August 2006. Many algorithms, methods and properties have been proposed to deal with microdata disclosure. One of the emerging concepts in microdata protection is k-anonymity, introduced by Samarati and Sweeney. k-Anonymity provides a simple and efficient approach to protect private individual information and is gaining increasing popularity. k-Anonymity requires that every record in the microdata table released be indistinguishably related to no fewer than k respondents.In this paper, we apply the concept of entropy to propose a distance metric to evaluate the amount of mutual information among records in microdata, and propose a method of constructing dependency tree to find the key attributes, which we then use to process approximate microaggregation. Further, we adopt this new microaggregation technique to study k-anonymity problem, and an efficient algorithm is developed. Experimental results show that the proposed microaggregation technique is efficient and effective in the terms of running time and information loss.

Illegal immigration is one of the most contentious issues of our times. The lack of comprehensive federal immigration reform has pushed states to enact provisions (e.g. Arizona's S.B. 1070 and Alabama's H.B. 56) intended to reduce their unauthorized immigrant populations. The question for policymakers is whether these bills are achieving their goalsmainly to improve labor market outcomes for natives and to reduce the size of the unauthorized immigrant population. Employing data from the American Community Survey and the National Conference of State Legislatures, this analysis seeks to add to the very limited literature on the impact of recent state immigration legislation on the undocumented population. I analyze the relationship between punitive state law enforcement, omnibus, and labor immigrationrelated laws and the share of workers in the lowskilled sector who are undocumented immigrants. I also analyze the relationship between this legislation and the size of the undocumented immigrant population. The results show that law enforcement, omnibus, and labor legislation do not have a statistically significant relationship with the share of workers in the lowskilled sector who are undocumented. The results also show that this legislation does not have a statistically significant relationship with the size of the undocumented immigrant population. However, there is weak evidence that law enforcement legislation is associated with a small decline in the size of the population of undocumented immigrants with less than a high school education. These findings suggest that, for policymakers seeking to improve employment opportunities for natives or to reduce the size of the undocumented immigrant population, pursuing law enforcement, omnibus, and labor legislation may not be an effective approach.

Are rural homeowners in the workforce as mobile as urban homeowners? This paper focuses on whether rural unemployedhomeowners end their unemployment spells more or less often without moving than urban homeowners. A competing hazardmodel is estimated using a five-year panel that controls for the demographics of the individuals and the economic characteristics of their workplaces. Evidence is found that unemployed rural homeowners appear to be less mobile than unemployed urban homeowners, which may suggest the presence of a lock-in effect similar to those identified by other researchers associated with subsidized housing, homeownership compared with renting, and mortgage illiquidity.

Learning English is a potentially profitable investment for immigrants in the U.S.: while there are initial costs, the subsequent benefits include the ability to communicate with the majority of the population, potentially leading to better paying jobs and economic success in the new country. These payoffs are lessened if immigrants choose to live and work in ethnic enclaves where the necessity to communicate in English is weak. Ethnic enclaves are widespread andpersistent in the U.S. This study uses data from the 2010 American Community Survey to examine the impact of residential and occupational segregation on immigrants ability to speak English. We allow for heterogeneity in the relationship between segregation and English language proficiency across ethnic groups and focus specifically on Mexican and Chinese immigrants. Our results show that immigrants in the U.S. who live and work among high concentrations of their countrymen are less likely to be proficient in English than those who are less residentially and occupationally segregated. The magnitude of the effect of segregation on language proficiency varies across immigrants birthplaces and other salient characteristics defining the immigration context.

The Community Development and Policy Studies division (CDPS) of the Federal Reserve Bank of Chicago hosted the Industrial Cities Initiative Symposium (ICI) on February 28, 2012. More than 50 economists, development professionals, city representatives, and analysts from business, academia, and city government attended the symposium.

OBJECTIVE I develop and explain a new method for interpolating detailed fertility schedules from age-group data. The method allows estimation of fertility rates over a fine grid of ages, from either standard or non-standard age groups. Users can calculate detailed schedules directly from the input data, using only elementary arithmetic. METHODS The new method, the calibrated spline (CS) estimator, expands an abridged fertility schedule by finding the smooth curve that minimizes a squared error penalty. The penalty is based both on fit to the available age-group data, and on similarity to patterns of 1fx schedules observed in the Human Fertility Database (HFD) and in the US Census International Database (IDB). RESULTS I compare the CS estimator to two very good alternative methods that require more computation: Beers interpolation and the HFD's splitting protocol. CS replicates known 1fx schedules from 5fx data better than the other two methods, and its interpolated schedules are also smoother. CONCLUSIONS The CS method is an easily computed, flexible, and accurate method for interpolating detailed fertility schedules from age-group data.

Given the current state of retirement income security in the United States, we propose states offer all workers a voluntary, low-fee, low-risk, retirement plan to help boost savings for retirement