Emerging Rural Settlement Patterns and the Geographic Redistribution of America's New Immigrants*

Abstract This paper analyzes geographic patterns of population concentration and deconcentration among the foreign‐born population during the 1990–2000 period. A goal is to examine whether the foreign‐born population, including recent arrivals, are dispersing geographically from metro gateway cities into rural and other less densely populated parts of the country. The paper also evaluates the so‐called balkanization hypothesis, which is that immigration flows run counter‐cyclical to the redistribution trends of the native‐born population, while reinforcing spatial isolation and immigrant segregation. Data for U.S. counties or county equivalents come from the 1990 and 2000 U.S. Census (Summary Files 1, 3 and 4). Our results suggest that America's immigrant population is dispersing spatially. Immigrants are less concentrated today than in the past and they are less segregated from other population groups, including their own racial group and whites. However, changes over the past decade have been modest. The immigrant population, even in 2000, remained considerably more concentrated than the native‐born population. The empirical results provide little evidence of geographic balkanization.     

A Multivariate, Multilevel Rasch Model with Application to Self–Reported Criminal Behavior

In studying correlates of social behavior, attitudes, and beliefs, a measurement model is required to combine information across a large number of item responses. Multiple constructs are often of interest, and covariates are often multilevel (e.g., measured at the person and neighborhood level). Some item–level missing data can be expected. This paper proposes a multivariate, multilevel Rasch model with random effects for these purposes and illustrates its application to self–reports of criminal behavior. Under assumptions of conditional independence and additivity, the approach enables the investigator to calibrate the items and persons on an interval scale, assess reliability at the person and neighborhood levels, study the correlations among crime types at each level, assess the proportion of variation in each crime type that lies at each level, incorporate covariates at each level, and accommodate data missing at random. Using data on 20 item responses from 2842 adolescents ages 9 to 18 nested within 196 census tracts in Chicago, we illustrate how to test key assumptions, how to adjust the model in light of diagnostic analyses, and how to interpret parameter estimates.     

IDENTIFYING TREATMENT EFFECTS IN MULTI-CHANNEL MEASUREMENTS IN ELECTROENCEPHALOGRAPHIC STUDIES: MULTIVARIATE PERMUTATION TESTS AND MULTIPLE COMPARISONS

A versatile procedure is described comprising an application of statistical techniques to the analysis of the large, multi‐dimensional data arrays produced by electroencephalographic (EEG) measurements of human brain function. Previous analytical methods have been unable to identify objectively the precise times at which statistically significant experimental effects occur, owing to the large number of variables (electrodes) and small number of subjects, or have been restricted to two‐treatment experimental designs. Many time‐points are sampled in each experimental trial, making adjustment for multiple comparisons mandatory. Given the typically large number of comparisons and the clear dependence structure among time‐points, simple Bonferroni‐type adjustments are far too conservative. A three‐step approach is proposed: (i) summing univariate statistics across variables; (ii) using permutation tests for treatment effects at each time‐point; and (iii) adjusting for multiple comparisons using permutation distributions to control family‐wise error across the whole set of time‐points. Our approach provides an exact test of the individual hypotheses while asymptotically controlling family‐wise error in the strong sense, and can provide tests of interaction and main effects in factorial designs. An application to two experimental data sets from EEG studies is described, but the approach has application to the analysis of spatio‐temporal multivariate data gathered in many other contexts.     

Comparing customer satisfaction across industries and countries

Although aggregate satisfaction measures continue to proliferate, their value in making broad-based comparisons remains unclear. This study uses arguments from the economics, psychology, sociology and marketing domains to predict systematic differences in aggregate customer satisfaction across both industries and countries. These predictions are tested using a database created from three broad-based national satisfaction surveys in Sweden, Germany and the United States. The results reveal that, across countries, satisfaction is highest for competitive products, lower for competitive services and retailers, and lower still for government and public agencies. However, the differences vary by country. Satisfaction is also predictably lower in Sweden and Germany compared to the US, and shown to change systematically in Sweden over time. Methodological differences do not appear to limit the comparability of the aggregate satisfaction measures. Overall the study supports the use of national indices for making meaningful comparisons of satisfaction on a broad scale.     

Downsizing Survival: The Experience of Work and Organizational Commitment

Although downsizing has become a common feature of American workplaces, the existing literature has focused on the effects of how downsizing is conducted, rather than considering how downsizing affects the experience of work for downsizing survivors. Using data from the 1997 National Employee Survey and structural modeling techniques, this study compares downsizing survivors and workers unaffected by downsizing on a variety of sociodemographic indicators, job characteristics, and organizational environment measures in order to explain the lower levels of organizational commitment among survivors. The model in which downsizing survival was directly and indirectly associated with commitment was generally supported. Survivors reported less commitment than unaffected workers. In addition, downsizing survival was positively associated with job-related stress and negatively associated with perceived organizational support, which translated into survivors' lower levels of commitment. This research suggests that organizations that downsize should consider ways to redesign work processes so as to reduce job-related stress and should engage in organizational practices that demonstrate organizational support for surviving employees.     

Using Community-Level Correlates to Evaluate Nonresponse Effects in a Telephone Survey

Understanding the relationship between nonresponse processesand key research variables is central to evaluating if and hownonresponse introduces bias into survey estimates. In most telephonesurveys, however, little information is available with whichto estimate these effects. We report a procedure for examiningthe potential effects of nonresponse via analyses that (1) investigatethe linkages between community-level (zip code) variables andsurvey nonresponse and (2) examine the associations betweenthese community-level variables and key survey measures. Wedemonstrate these procedures using hierarchical modeling toanalyze data from a state-wide telephone survey in Illinois.One zip code–level indicator of concentrated disadvantage—thepercentage of the population below poverty level—was foundto be positively associated with nonresponse and, among respondents,with both current physical disability status and lack of healthinsurance coverage, suggesting that both may have been underestimatedin this survey. This inexpensive approach has the potentialof enabling researchers to routinely evaluate nonresponse effectsin their survey data.     

Post Adoption Service Need and Use as Predictors of Adoption Dissolution: Findings From the 2012 National Adoptive Families Study

Data from the 2012 National Adoptive Families Study (NAFS) were used to examine the relationships between adoptive parents' need for and utilization of post-adoption services and adoption dissolution. NAFS was an online survey administered to adoptive parents (N = 437) who had adopted a child from the United States foster care system. The study found that needing and accessing post-adoption services predicted 26% of the variance in dissolution. Substance abuse treatment, educational advocacy, and parent support groups were the only significant predictors of adoption dissolution. Both needing and accessing substance abuse treatment increased the likelihood of adoption dissolution. Needing educational advocacy increased the likelihood of dissolution, but actually accessing it decreased the likelihood of dissolution. Accessing parent support groups similarly decreased the likelihood of dissolution. Policy and practice implications of the findings are discussed.     

Educational and Financial Institutions Partnering to Implement CSAs: Evaluation of Financial Partners’ Perspectives from the 2011 GEAR UP Invitational Priority

Educational and financial institutions are increasingly partnering to open Children’s Savings Accounts (CSAs); however, little is known about these partnerships’ effectiveness for planning and implementing CSAs. A 2011 invitational priority from the Department of Education encouraged partnerships between Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) programs and financial institutions to open CSAs for low-income students, which provided an opportunity to evaluate these partnerships. In-depth interviews with 10 personnel from 6 financial institutions who partnered with 4 GEAR UP programs revealed that partnerships with stakeholders, time spent on planning, and strategies for overcoming barriers were important for implementing CSAs. Lessons for practice and policy are discussed.     

Early‐Onset Alcohol Use Among Native American Youth: Examining Female Caretaker Influence

This article investigates the influence of female caretaker substance use on early‐onset youth drinking among Native American families in the Northern Midwest. Data include 603 Native American families, with reports from female caretakers and youths aged 10 – 13 years. Two potential caretaker influences are taken into account: adolescent modeling of caretaker behaviors and the effects of caretaker substance abuse on parenting. Results of bivariate and path analysis provide support for the influence of caretaker substance use on adolescent drinking from both perspectives; these effects vary, however, depending on the type or degree of adult substance use, or both.