Two Graphical Techniques Useful in Detecting Correlation Structure in Repeated Measures Data

Analysis of repeated measures data using a mixed model includes specifying a form for the covariance matrix of the within-subject observations. This reduction in the number of estimated parameters from the unspecified structure may improve the efficiency of inferences made. An implementation of this technique has been incorporated in the MIXED procedure of the SAS® statistical package, and includes a wide range of options for the structure of the covariance matrix. It is demonstrated that draftman's display plots and/or plots in a coordinate system with parallel axes can aid in visualizing the dispersion structure.     

Fourier analysis of irregularly spaced data on Rd

Summary.  The purpose of the paper is to propose a frequency domain approach for irregularly spaced data on R ^d . We extend the original definition of a periodogram for time series to that for irregularly spaced data and define non-parametric and parametric spectral density estimators in a way that is similar to the classical approach. Introduction of the mixed asymptotics, which are one of the asymptotics for irregularly spaced data, makes it possible to provide asymptotic theories to the spectral estimators. The asymptotic result for the parametric estimator is regarded as a natural extension of the classical result for regularly spaced data to that for irregularly spaced data. Empirical studies are also included to illustrate the frequency domain approach in comparisons with the existing spatial and frequency domain approaches.     

Youth perceptions of neighborhood hassles and resources: A mixed method analysis

Empirical investigations exploring the processes and mechanisms of neighborhood influences on child and youth development are needed to contribute to the growing body of research on neighborhood as a context for development. Using a mixed method design, this study examined the relationship between structurally identified resources in three urban public housing neighborhoods, youth perceptions and experiences of resources, and youth report of neighborhood hassles and cohesion. Survey data from 153 ethnically and culturally diverse youth between 6th and 8th grade were analyzed using regression analyses; constant comparative analysis was used to code interviews from a subsample of 22 youth. Results indicated an inverse relationship between the number of neighborhood resources and the level of daily hassles youth report. Analysis of mixed method results further highlights the importance of young people's perceptions of neighborhood influences.     

Linear predictors of future order statistics

In this paper we establish an optimal asymptotic linear predictor which does not involve the finite-sample variance-covariance structure. Extensions to the problem of finding the best linear unbiased and simple linear unbiased predictors for k samples are given. Moreover, we obtain alternative linear predictors by modifying the covariance matrix by either an identity matrix or a diagonal matrix. For normal, logistic and Rayleigh samples of size 10, the alternative linear predictors with these modifications have high efficiency when compared with the best linear unbiased predictor.     

On left-truncating and mixing Poisson distributions

ABSTRACT

The distributions obtained by left-truncating at k a mixed Poisson distribution, denoted kT-MP, and those obtained by mixing previously left-truncated Poisson distributions, denoted M-kTP, are characterized by means of their probability generating function. The main consequence is that every kT-MP distribution is a M-kTP distribution, but not the other way around.     

Bootstrap mean squared error of a small-area EBLUP

Concerning the estimation of linear parameters in small areas, a nested-error regression model is assumed for the values of the target variable in the units of a finite population. Then, a bootstrap procedure is proposed for estimating the mean squared error (MSE) of the EBLUP under the finite population setup. The consistency of the bootstrap procedure is studied, and a simulation experiment is carried out in order to compare the performance of two different bootstrap estimators with the approximation given by Prasad and Rao [Prasad, N.G.N. and Rao, J.N.K., 1990, The estimation of the mean squared error of small-area estimators. Journal of the American Statistical Association, 85, 163–171.]. In the numerical results, one of the bootstrap estimators shows a better bias behavior than the Prasad–Rao approximation for some of the small areas and not much worse in any case. Further, it shows less MSE in situations of moderate heteroscedasticity and under mispecification of the error distribution as normal when the true distribution is logistic or Gumbel. The proposed bootstrap method can be applied to more general types of parameters (linear of not) and predictors.     

An innovative medical and dental hygiene clinic for street youth: Results of a process evaluation

Canada has a noteworthy reputation for high quality health care. Nonetheless, street youth are one of our most vulnerable yet underserved populations. Consequently, a medical and dental clinic was created in downtown Ottawa, Ontario to respond to their needs. The purpose of this study is to describe a process evaluation of the clinic during its first year of operation with a focus on program fidelity, dose, reach, and satisfaction. A mixed methods approach was used involving interviews with providers, focus groups with street youth, analysis of Electronic Medical Record (EMR) data, and supplemental information such as document reviews. The evaluation identified areas that were working well along with challenges to program implementation. Areas of concerns and possible solutions were presented to the management team that then helped to plan and make improvements to the clinic. Our evaluation design and working relationship with clinic management promoted the integration of real-time evidence into program improvements.     

Exact Multivariate Permutation Tests for Fixed Effects in Mixed-Models

A test for the fixed effect in mixed-models is proposed. It is based on permutation strategy and is exact. The testing approach presented is very general and the class of models covered is very broad.

Multivariate responses with different type of variables (e.g., continuous, categorical, and ranks) are usually tested with separated models and the overall test are usually reached through Bonferroni-like combinations, i.e., without taking into account the joint distribution of the test statistics. On the contrary, in this approach the joint distribution is immediately obtained and the dependence among tests is taken into account in the overall test. The methods are implemented in the R package flip, freely available on CRAN.     

The Use of Working Variables in the Bayesian Modeling of Mean and Dispersion Parameters in Generalized Nonlinear Models with Random Effects

This article is aimed at reviewing a novel Bayesian approach to handle inference and estimation in the class of generalized nonlinear models. These models include some of the main techniques of statistical methodology, namely generalized linear models and parametric nonlinear regression. In addition, this proposal extends to methods for the systematic treatment of variation that is not explicitly predicted within the model, through the inclusion of random effects, and takes into account the modeling of dispersion parameters in the class of two-parameter exponential family. The methodology is based on the implementation of a two-stage algorithm that induces a hybrid approach based on numerical methods for approximating the likelihood to a normal density using a Taylor linearization around the values of current parameters in an MCMC routine.     

美国混合居住模式对我国社会福利事业的启示

自20世纪80年代以来美国的社会福利政策发生重大变化,在住房领域的"混合居住"模式被提出,并逐渐上升为一种发展策略,这种模式将收入不同的阶层结为邻里关系,从而形成邻里之间相互利益互补的一种居住方式和住房保障模式,以此增加中低收入群体的社会资本,同时使其不至于远离主流社会,从而促进社会融合。该政策取得很好的政策效果,而我国社会福利事业方兴未艾,需要加大投入,美国经验提供非常好的吸纳民间资本、公民个人参与进社会福利事业的微观路径。