Homogamy by education and migration status in Monterrey,Mexico: changes and continuities over time

This paper reviews changes in homogamy by migration status and educational level in Monterrey, Mexico, through the analysis of marriage patterns for two cohorts of men born in 1905–1934 and 1940–1969. Results show a significant increase in educational homogamy, as well as in homogamy by rural origins. The changes suggest that education has played an increasingly important role in the process of mate selection, although certain particularistic characteristics, such as being a rural immigrant, are still important in marriage formation. The paper concludes with a discussion of the implications of these findings for the relationship between homogamy and social stratification.

Penalized Pseudolikelihood Inference in Spatial Interaction Models with Covariates

Given spatially located observed random variables ( x , z = {( x _i , z _i )} _i , we propose a new method for non-parametric estimation of the potential functions of a Markov random field p ( x | z ), based on a roughness penalty approach. The new estimator maximizes the penalized log-pseudolikelihood function and is a natural cubic spline. The calculations involved do not rely on Monte Carlo simulation. We suggest the use of B-splines to stabilize the numerical procedure. An application in Bayesian image reconstruction is described.     

Testing the dilation order by using cumulative residual Tsallis entropy

In this paper, we introduce a new test for the dilation order based on cumulative residual Tsallis entropy of order α. The effect of the values of parameter α on the power of the test statistics is numerically investigated. The asymptotic distribution of the test statistic is given. The performance of the test statistic is evaluated using a simulation study. Finally, some numerical examples illustrating the theory are also given.     

Noninformative priors for the between-group variance in the unbalanced one-way random effects model with heterogeneous error variances

For the unbalanced one-way random effects model with heterogeneous error variances, we propose the non-informative priors for the between-group variance and develop the first- and second-order matching priors. It turns out that the second-order matching priors do not exist and the reference prior and Jeffreys prior do not satisfy a first-order matching criterion. We also show that the first-order matching prior meets the frequentist target coverage probabilities much better than the Jeffreys prior and reference prior through simulation study, and the Bayesian credible intervals based on the matching prior and reference prior give shorter intervals than the existing confidence intervals by examples.     

Linear scalar-on-surface random effects regression models

Many research fields increasingly involve analyzing data of a complex structure. Models investigating the dependence of a response on a predictor have moved beyond the ordinary scalar-on-vector regression. We propose a regression model for a scalar response and a surface (or a bivariate function) predictor. The predictor has a random component and the regression model falls in the framework of linear random effects models. We estimate the model parameters via maximizing the log-likelihood with the ECME (Expectation/Conditional Maximization Either) algorithm. We use the approach to analyze a data set where the response is the neuroticism score and the predictor is the resting-state brain function image. In the simulations we tried, the approach has better performance than two other approaches, a functional principal component regression approach and a smooth scalar-on-image regression approach.     

Is the web a promising tool for data collection in developing countries? An analysis of the sample bias of 10 web and face-to-face surveys from Africa,Asia, and South America

Whereas the sample composition biases of web surveys have been discussed extensively for developed countries, studies for developing countries are scarce. This article helps to fill that gap by comparing similar non-probability-based web surveys (WEB) and probability-based face-to-face (F2F) surveys both to each other and to the labor force. An analysis of WageIndicator data on work and wages derived from surveys held in 2009–2013 in 10 developing countries (WEB-sample N = 9135; F2F-sample N = 14,659), shows that F2F samples resemble the labor force to a larger extent than web samples do. In both cases, individuals in their 20s and early 30s are overrepresented, and younger and older respondents are underrepresented. This trend is more pronounced in WEB than in F2F samples. However, the differences converge in countries with higher Internet usage. A comparison of the WEB and F2F samples shows that compositions differ greatly, with web respondents being younger, more often male, more often living alone, and higher educated, although these differences are smaller in countries with higher Internet usage. Given the cost differences between the two survey modes, one should nevertheless consider the potential of web surveys as an instrument to gain explorative insights, specifically when searching for individuals with particular characteristics.     

Educational assortative mating and time use in the home

This study examines the association between individuals' educational assortative mating and time spent on child care and housework. Focus is put on hypogamous couples, or couples in which wives have more education than their husbands. Relative resources and gender revolution frameworks are considered as contexts to explain why hypogamous couples may share their time differently than other couples. A series of ordinary least squares regressions with population and sampling weights are employed using American Time Use Survey data from 2003 to 2018. Three, separate analyses using relative education, gender, and all educational pairings as the independent variables of interest are presented with child care and housework as the dependent variables. The current findings show that men in hypogamous marriages perform about 10 min more of child care per day on average than their peers in hypergamous and homogamous marriages, and that this comes primarily from basic care activities. This accounts for approximately 43% of the difference between men and women in the average amount of time spent on child care. No clear pattern of significance is apparent comparing individuals’ time spent on housework by relative education, suggesting that housework and child care have evolved differently in the context of gendered domestic responsibilities. Men in hypogamous marriages are more egalitarian in their sharing of child care. However, this is only true for couples in which men have at least a high school diploma and women are highly educated.     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

Heating up the debate? Measuring fragmentation and polarisation in a German climate change hyperlink network

Research into polarisation on the internet has so far primarily focused on contentious issues and yielded contradictory results. Shifting the focus to a non-contentious setting, this article combines community detection with brokerage analysis and exponential random graph models to assess the degree of polarisation at different levels of a German hyperlink network on climate change. Although homophily accounts for a moderate degree of polarisation at the top level of the network, the communities reveal that other factors prove more decisive in shaping its structure and the article thus contributes to a more refined understanding of the nature of online polarisation.     

Univariate and multivariate models of positive and negative networks: Liking,disliking, and bully–victim relationships

Three relations between elementary school children were investigated: networks of general dislike and bullying were related to networks of general like. These were modeled using multivariate cross-sectional (statistical) network models. Exponential random graph models for a sample of 18 classrooms, numbering 393 students, were summarized using meta-analyses. Results showed (balanced) network structures with positive ties between those who were structurally equivalent in the negative network. Moreover, essential structural parameters for the univariate network structure of positive (general like) and negative (general dislike and bullying) tie networks were identified. Different structures emerged in positive and negative networks. The results provide a starting point for further theoretical and (multiplex) empirical research about negative ties and their interplay with positive ties.