On implementation of a test for Kronecker product covariance structure for multivariate repeated measures data

Under the assumption of multivariate normality the likelihood ratio test is derived to test a hypothesis for Kronecker product structure on a covariance matrix in the context of multivariate repeated measures data. Although the proposed hypothesis testing can be computationally performed by indirect use of Proc Mixed of SAS, the Proc Mixed algorithm often fails to converge. We provide an alternative algorithm. The algorithm is illustrated with two real data sets. A simulation study is also conducted for the purpose of sample size consideration.     

Modelling association between two irregularly observed spatiotemporal processes by using maximum covariance analysis

Summary.  Climatic phenomena such as the El-Niño–southern oscillation and the north Atlantic oscillation are results of complex interactions between atmospheric and oceanic processes. Understanding the interactions has enabled scientists to give early warning of the forthcoming phenomena, thereby reducing damage caused by them. Statistical methods have played an important role in revealing effects of these phenomena on different regions of the world. One such method is maximum covariance analysis (MCA). Two apparent weaknesses are associated with MCA. Firstly, it tends to produce estimates with a low signal-to-noise ratio, especially when the sample size is small. Secondly, there has been no objective way of incorporating incomplete records, which are frequently encountered in climatology and oceanographic data-bases. We introduce an MCA which incorporates a smoothing procedure on the estimates. The introduction of the smoothing procedure is shown to improve the signal-to-noise ratio on the estimates. The estimation of smoothing parameters is carried out by using a penalized likelihood approach, which makes the inclusion of incomplete records quite straightforward. The methodology is applied to investigate the association between Irish winter precipitation and sea surface temperature anomalies around the world. The results show relationships between Irish precipitation anomalies and the El-Niño–southern oscillation and the north Atlantic oscillation phenomena.     

Modelling concurrency of events in on-line auctions via spatiotemporal semiparametric models

Summary.  We introduce a semiparametric approach for modelling the effect of concurrent events on an outcome of interest. Concurrency manifests itself as temporal and spatial dependences. By temporal dependence we mean the effect of an event in the past. Modelling this effect is challenging since events arrive at irregularly spaced time intervals. For the spatial part we use an abstract notion of 'feature space' to conceptualize distances among a set of item features. We motivate our model in the context of on-line auctions by modelling the effect of concurrent auctions on an auction's price. Our concurrency model consists of three components: a transaction-related component that accounts for auction design and bidding competition, a spatial component that takes into account similarity between item features and a temporal component that accounts for recently closed auctions. To construct each of these we borrow ideas from spatial and mixed model methodology. The power of this model is illustrated on a large and diverse set of laptop auctions on eBay.com. We show that our model results in superior predictive performance compared with a set of competitor models. The model also allows for new insight into the factors that drive price in on-line auctions and their relationship to bidding competition, auction design, product variety and temporal learning effects.     

Organizational culture influence on service delivery: A mixed methods design in a child welfare setting

Despite the growing acknowledgement that mixed methods can be useful to better understand complex organizational cultures, there are few examples of studies, which demonstrate how organizational culture studies combine quantitative and qualitative methods in a single study within the child welfare setting. The purpose of the article is to illustrate how a concurrent triangulation was accomplished in a single organizational culture study in a child welfare agency. A sample of 92 employees was selected from a Midwestern private, non-profit, faith-based child welfare agency. Four distinct methods were used to measure organizational culture and its influence on service delivery which allowed for greater validity by collecting different data bearing on the same organizational culture phenomena. Strengths and implications are discussed.     

"An Inner Group of Willing People": Volunteering in a Religious Context

In the age of "welfare pluralism", volunteers are attracting increasing attention from academics and policy-makers. This paper focuses on volunteering in the context of religious congregations. It is found to be similar in some ways to that in secular organizations but there are also significant differences including the impact of religious values on motivation, the fact that congregational volunteers are also "members", and the special relationship with clergy. It is concluded that congregational volunteers can be important constituents of the "mixed economy of care"and "civil society". However, long-term care may be provided better by institutions which are less dependent on individual enthusiams.     

Evaluating a community based mental health programme in West Bengal,India: Description of the methodology and lessons learned

Mental disorders impose an enormous burden on society. In developing countries like India, there is a lack of adequate number of trained mental health professionals to provide specialized care and 75–85 % of affected individuals do not have access to appropriate mental health services. The National Mental Health Programme (NMHP) is being implemented by the Government of India to support state governments in providing mental health services in the country. The Urban Mental Health Programme (UMHP) is a pilot initiative that has attempted the integration of mental health services in primary health care settings in two municipal wards in Kolkata, West Bengal, India. The overarching aim of this paper is to describe the methodology used for the evaluation of the community based mental health programme and to understand the processes of the programme in terms of barriers and facilitators. The current evaluation is based on a concurrent nested design, where qualitative and quantitative data are both collected at the same time but analysed separately and priority was given to qualitative data. This experience will contribute in helping other researchers to make some evaluations more effective, useful and manageable. Ethics approval was obtained from an institutional ethics committee of an organization (Ekjut) based in Ranchi, Jharkhand, India. The evaluation was undertaken by the George Institute for Global Health, New Delhi from February- June 2016.     

SenseMaker® as a monitoring and evaluation tool to provide new insights on gender-based violence programs and services in Lebanon

Monitoring and evaluation (M&E) of gender-based violence (GBV) programs is challenging in humanitarian settings. To address these challenges, we used SenseMaker® as a mixed methods M&E tool for GBV services and programs in Lebanon. Over a three-month period in 2018, a total of 198 self-interpreted stories were collected from women and girls accessing GBV programs from six service providers across five locations. The resultant mixed-methods analysis provided holistic and nuanced insights on how perceived benefits differed by type of GBV program, how motivations for accessing programs differed by location, and how feelings while accessing programs differed by participant nationality. SenseMaker reinforced the intersectionality between events leading up to the accessed services, the experiences of accessing the services, and subsequent outcomes as a result of having accessed the services, helping to contextualize the findings within the broader experiences of participating women and girls. Limited literacy and technology skills among participants proved to be a challenge and future work should investigate how technology might facilitate use of the tool among participants with lower literacy and technology skills in addition to exploring the feasibility and added value of SenseMaker as an M&E tool in acute humanitarian settings.     

Analysis of mixed correlated bivariate zero-inflated count and (k,l)-inflated beta responses with application to social network datasets

This paper presents a new model that monitors the basic network formation mechanisms via the attributes through time. It considers the issue of joint modeling of longitudinal inflated (0, 1)-support continuous and inflated count response variables. For joint model of mentioned response variables, a correlated generalized linear mixed model is studied. The fraction response is inflated in two points k and l (k < l) and a k and l inflated beta distribution is introduced to use as its distribution. Also, the count response is inflated in zero and we use some members of zero-inflated power series distributions, hurdle-at-zero, members of zero-inflated double power series distributions and zero-inflated generalized Poisson distribution as our count response distribution. A full likelihood-based approach is used to yield maximum likelihood estimates of the model parameters and the model is applied to a real social network obtained from an observational study where the rate of the ith node’s responsiveness to the jth node and the number of arrows or edges with some specific characteristics from the ith node to the jth node are the correlated inflated (0, 1)-support continuous and inflated count response variables, respectively. The effect of the sender and receiver positions in an office environment on the responses are investigated simultaneously.     

A simple unit root testing methodology that does not require knowledge regarding the presence of a break

We develop a simple methodology that allows practitioners to test for the presence of a unit root without a priori knowledge regarding the occurrence of a break under the null hypothesis. We use a pre-test that is readily available in the estimated regression used to calculate the unit root statistics, and so our methodology is very easy to implement. The t-statistic corresponding to the impulse dummy variables evaluated at break date estimator is used as a pre-test to ascertain whether a break exists under the null hypothesis. Finite sample simulations show that our methodology yields tests that maintain their size.     

A taxonomy of mixing and outcome distributions based on conjugacy and bridging

Abstract

The generalized linear mixed model (GLMM) is commonly used for the analysis of hierarchical non Gaussian data. It combines an exponential family model formulation with normally distributed random effects. A drawback is the difficulty of deriving convenient marginal mean functions with straightforward parametric interpretations. Several solutions have been proposed, including the marginalized multilevel model (directly formulating the marginal mean, together with a hierarchical association structure) and the bridging approach (choosing the random-effects distribution such that marginal and hierarchical mean functions share functional forms). Another approach, useful in both a Bayesian and a maximum-likelihood setting, is to choose a random-effects distribution that is conjugate to the outcome distribution. In this paper, we contrast the bridging and conjugate approaches. For binary outcomes, using characteristic functions and cumulant generating functions, it is shown that the bridge distribution is unique. Self-bridging is introduced as the situation in which the outcome and random-effects distributions are the same. It is shown that only the Gaussian and degenerate distributions have well-defined cumulant generating functions for which self-bridging holds.