Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

Parenting Behaviors Among Mainland Puerto Rican Adolescent Mothers: The Role of Grandmother and Partner Involvement

Relations between grandmother and partner involvement (coresidence, social support, child care) and Puerto Rican adolescent mothers' parenting behaviors were examined. Few associations between grandmother involvement and behavior emerged, and these were moderated by coresidence. In contrast, partner involvement showed a number of significant (positive) direct and moderated relations with behavior. For both providers, the direction of the relations between social support and behavior during teaching was the opposite depending on coresidence: Greater social support was related to the display of more positive behavior among coresiding mothers but to less competent behavior among non‐coresiding mothers. The relations between child care support and behavior differed across providers. For grandmothers, greater child care was related to less positive behavior during teaching among coresiding mothers but to more competent behavior among non‐coresiding mothers. For partners, greater child care was more strongly related to positive behavior during play among non‐coresiding than coresiding mothers. Results are discussed in light of Latino cultural values, developmental issues, and implications for intervention.     

Silphids in urban forests: Diversity and function

Many ecologists have examined the process of how urbanization reduces biological diversity but rarely have its ecological consequences been assessed. We studied forest-dwelling burying beetles (Coleoptera: Silphidae)—a guild of insects that requires carrion to complete their life cycles—along an urban-rural gradient of land use in Maryland. Our objective was to determine how forest fragmentation associated with urbanization affects (1) beetle community diversity and structure and (2) the ecological function provided by these insects, that is, decomposition of vertebrate carcasses. Forest fragmentation strongly reduced burying beetle diversity and abundance, and did so far more pervasively than urbanization of the surrounding landscape. The likelihood that beetles interred experimental baits was a direct, positive function of burying beetle diversity. We conclude that loss of burying beetle diversity resulting from forest fragmentation could have important ecological consequences in urban forests.     

2½‐Year‐Old Children Use Animacy and Syntax to Learn a New Noun

We examine how attention to animacy information may contribute to children's developing knowledge of language. This research extends beyond prior research in that children were shown dynamic events with novel entities, and were asked not only to comprehend sentences but to use sentence structure to infer the meaning of a new word. In a 4 × 3 design, animacy status (e.g., animate agent, inanimate patient) and labeling syntax (agent, patient, nonlabel control) were varied. Across most events, 2 1/2‐year‐old participants responded as if they expected animate entities to be named. However, in a prototypical (animate agent‐inanimate patient) event condition, children responded differentially across different syntactic structures. Thus, the clearest evidence for attention to syntactic cues was found in the prototypical event condition. These results suggest that young children attend to the animacy status of unfamiliar entities, that they have expectations about animacy relations in events, and that these expectations support emerging syntactic knowledge.     

The Robustness of Trend Stationarity: An Illustration with the Extended Nelson-Plosser Dataset

We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson-Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson-Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown.     

Muted Masculinity as an Outsider Strategy: Gender Sharing in Ethnographic Work with Wives of Professional Athletes

Using findings from a study of the world of the wives of professional athletes, this article explores the complex motivations for and displays of trust, rapport, and group acceptance during ethnographic research. Episodic exchanges between a male ethnographer and female collaborators revealed subtle issues of gender and perceived relative worth. This article proposes the outsider strategy of “muted masculinity” as a means of exploring ethnographic issues in which the boundaries between insiders and outsiders are uncertain.     

A general inverse sampling scheme and its application to adaptive cluster sampling

Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation.