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.     

Gender,lineage, and fertility‐related outcomes in Ghana

A growing literature examines the empirical relationship between the joint reproductive preferences of marital partners and reproductive outcomes in Africa. Less explored is how spousal power in decision making may be influenced by lineage type. Using pooled data from Ghana, we investigate how lineage affects gendered reproductive decision outcomes and find some evidence that matrilineal women are more able than nonmatrilineal women to translate their reproductive preferences into action consistent with their goals.     

HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.     

How Welfare Policies Affect Adolescents' School Outcomes: A Synthesis of Evidence From Experimental Studies

Using data from 8 random assignment studies and employing meta‐analytic techniques, this article provides systematic evidence that welfare and work policies targeted at low‐income parents have small adverse effects on some school outcomes among adolescents ages 12 to 18 years at follow‐up. These adverse effects were observed mostly for school performance outcomes and occurred in programs that required mothers to work or participate in employment‐related activities and those that encouraged mothers to work voluntarily. The most pronounced negative effects on school outcomes occurred for the group of adolescents who had a younger sibling, possibly because of the increased home and sibling care responsibilities they assumed as their mothers increased their employment.     

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.     

Testing symmetry under a skew Laplace model

We develop tests of hypothesis about symmetry based on samples from possibly asymmetric Laplace distributions and present exact and limiting distribution of the test statistics. We postulate that the test statistic derived under the Laplace model is a rational choice as a measure of skewness and can be used in testing symmetry for other, quite general classes of skew distributions. Our results are applied to foreign exchange rates for 15 currencies.     

Vulnerability and Agenda: Context and Process in Project Management

This paper explores how the project management role is conditioned by the context in which change is progressed. The argument draws on Pettigrew's (1985, 1987) contextual and processual view of change, a view which does not clarify the management implications of contextual variation. Using data from a two-stage research design combining diary and survey methods, four context dimensions are identified, concerning ‘interlocking’, ‘shifting sands’, ‘ownership’ and ‘senior management view’. For analytical purposes, two extreme contexts are characterized as exposing the project manager to high and low levels of ‘vulnerability’ respectively. Project management literature typically offers a rational-linear account of change, and concentrates on ‘content’ and ‘control’ agendas, concerning technical expertise on the one hand, and planning, budgeting and monitoring techniques on the other. Sociological analyses reveal the limitations of the rational-linear account, and focus on the political and cultural dimensions of the ‘process’ agenda. The data suggest how contextual variation affects the relative priority of these agendas. The management implications of these findings are explored, for project management selection, career progression, and the development of diagnostic skills and ‘agenda management’ strategies.     

Ethnic preferences and perceptions among Asian and White British middle school children

Asian and White middle school children were shown photographs of unknown Afro-Caribbean, Asian, and White individuals of approximately the same age as themselves, and asked which one wax most like them, which one they would prefer to be, which ones they would prefer to engage in various activities with, and finally, to allocate positive and negative traits to the three groups or to nobody. A similar majority of both Asian and While children selected an own-race photograph as being most like them, but only about a half selected the own-race photograph as the one they would most like to he. For sharing activities, children showed a strong own-tender preference, followed by an own-race preference. White children stated a greater preference for sharing activities with White children, then with Afro-Caribbean children, and least with Asian children. Asian children preferred Asian and White children the most, Afro-Caribbean the least. On a stereotypes test, similar trends were obtained; White children evaluated While children highest and Asian lowest; Asian children tended to evaluate Asian children highest but to a nonsignificant extent. The relative proportion of Asian/White children in school appeared to have little systematic influence on the results, thus arguing against the contact hypothesis of prejudice reduction in its simple form.