Frequency domain bootstrap for ratio statistics under long-range dependence

A frequency domain bootstrap (FDB) is a common technique to apply Efron’s independent and identically distributed resampling technique (Efron, 1979) to periodogram ordinates – especially normalized periodogram ordinates – by using spectral density estimates. The FDB method is applicable to several classes of statistics, such as estimators of the normalized spectral mean, the autocorrelation (but not autocovariance), the normalized spectral density function, and Whittle parameters. While this FDB method has been extensively studied with respect to short-range dependent time processes, there is a dearth of research on its use with long-range dependent time processes. Therefore, we propose an FDB methodology for ratio statistics under long-range dependence, using semi- and nonparametric spectral density estimates as a normalizing factor. It is shown that the FDB approximation allows for valid distribution estimation for a broad class of stationary, long-range (or short-range) dependent linear processes, without any stringent assumptions on the distribution of the underlying process. The results of a large simulation study show that the FDB approximation using a semi- or nonparametric spectral density estimator is often robust for various values of a long-memory parameter reflecting magnitude of dependence. We apply the proposed procedure to two data examples.     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

Adaptive and repeated cumulative meta‐analyses of safety data during a new drug development process

During a new drug development process, it is desirable to timely detect potential safety signals. For this purpose, repeated meta‐analyses may be performed sequentially on accumulating safety data. Moreover, if the amount of safety data from the originally planned program is not enough to ensure adequate power to test a specific hypothesis (e.g., the noninferiority hypothesis of an event of interest), the total sample size may be increased by adding new studies to the program. Without appropriate adjustment, it is well known that the type I error rate will be inflated because of repeated analyses and sample size adjustment. In this paper, we discuss potential issues associated with adaptive and repeated cumulative meta‐analyses of safety data conducted during a drug development process. We consider both frequentist and Bayesian approaches. A new drug development example is used to demonstrate the application of the methods. Copyright © 2015 John Wiley & Sons, Ltd.     

Minority comparison model: Effects of Whites’ multiracial evaluation on symbolic racism and racialized policy preferences

Most Racial Studies primarily focus on African Americans without paying attention to nonblack minorities, and it fails to capture recent increase in racial diversity. Based on previous theories and empirical findings, we propose a new model, minority comparison model, which accounts for theoretical shortcomings in Racial Studies. This model (1) captures psychological processes that compare blacks and nonblacks, and (2) explores the effects of whites’ multiracial evaluation on racialized policy preferences. Drawing on a 2008 national representative sample, this study finds that whites who have positive stereotype of nonblacks (e.g., Hispanics and/or Asians) but negative stereotype of blacks show substantially higher symbolic racism and stronger opposition to Affirmative Action, whereas whites who have positive stereotype of blacks but negative stereotypes of nonblacks have stronger opposition to expansive immigration policy. Our study offers new ways of understanding and accounting for symbolic racism in modern context, and shows how whites’ preferences in racialized policies are influenced by multiracial evaluation.     

Part-time employment and worker health in the United States

A growing body of research has highlighted the consequences of part-time employment for workers’ health and well-being. However, these studies have yielded inconsistent results and relied on cross-sectional data. In addition, relatively little empirical research has explored whether the effect of working part-time on health varies by gender, particularly in the United States. Using longitudinal data from three waves of the General Social Survey panel (2010–2012–2014), our study examined the association between part-time employment and perceived health among U.S employees, and whether this association varied by gender. The results showed that part-time workers were less likely to report poor self-rated health than full-time workers, especially among males. The pattern of results was consistent across empirical approaches—including generalized estimating equations and random effects models, with an extensive set of covariates. Taken together, these findings suggest that for U.S. employees, working part-time appears to be beneficial or at least not detrimental to perceived health, which warrants further investigation.     

Revisiting the effectiveness of the employment‐oriented welfare state: Considering the quality of employment achievement

The purpose of this study was to examine the effectiveness of an employment‐oriented welfare state. While previous studies have focused on employment growth, this study considers the quality of employment, especially its mediating impact between public social expenditure and fiscal soundness. Three‐step mediated regression analysis was conducted on a data sample from 19 developed countries from 1991 to 2013. The results show that while public social expenditure negatively affects fiscal soundness, if it promotes total and part‐time employment, it can positively affect fiscal soundness. However, when the incidence of involuntary part‐time employment is high, public social expenditure and its impact on employment performance no longer guarantee fiscal soundness. This study addresses the importance of promoting not only employment growth but also employment quality to secure fiscal soundness.