The effect of non-normality on estimating the variance of the combined ratio estimate in complex surveys

The performance of the balanced half-sample, jackknife and linearization methods for estimating the variance of the combined ratio estimate is studied by means of a computer simulation using artificially generated non-normally distributed populations.

The results of this investigation demonstrate that the variance estimates for the combined ratio estimate may be highly biased and unstable when the underlying distributions are non-normal. This is particularly true when the number of observations available from each stratum is small. The jack-     

A Diagnostic Test for Normality Within the Power Exponential Family

This article develops the locally uniformly most powerful unbiased Lagrange multiplier test of normality of regression disturbances within the family of power exponential distributions. The small sample power properties of the test are compared in a Monte Carlo study with 6 well-known tests across 12 alternative nonnormal distributions. In addition, the finite sample power properties for nonnormal alternatives within the power exponential family are summarized by estimating response surfaces. The results suggest that the proposed text is computationally convenient and possesses relatively attractive power properties even against alternatives outside the power exponential family.     

Cell Phone Survey Feasibility in The U.S.: Sampling and Calling Cell Numbers Versus Landline Numbers

In 2004, we conducted a nationwide dual frame survey of landlineand cell phone numbers to evaluate the feasibility of includingcell phone numbers in a random digit dial telephone survey.Households with both landline and cell phones were eligiblefor selection in both samples. This article describes our designand data collection methods; compares the results from the twosamples (with an emphasis on operational characteristics); andpresents the outcomes of two experimental manipulations designedto improve the cell phone response rate.     

THE HARMS SHOE COMPANY: DEVELOPMENT OF A COMPUTER MODEL FOR THE CLASSROOM

This paper describes a case that examines five key topics in production and operations management [1]—forecasting, inventory control, transportation planning, aggregate planning, and the disaggregation of the aggregate plan—in an integrated, realistic manner for upper-level undergraduate business majors [3]. The case structure stresses the linkage of these interrelated subjects and supplements the regular classroom presentations dealing with them. The case relies on computer calculations at each stage to provide the information input for calculations at the next stage. It is a static model with a twelve-month planning horizon. Students complete several exercises and assume several roles as the case unfolds. They act on their own in filling some roles and as members of teams in performing others. They do not compete with each other, as the purpose of the case is to help them develop an appreciation of the factors that persons performing the role must consider.     

Can Clinical Skills Be Taught Online? Comparing Skill Development Between Online and F2F Students Using a Blinded Review

This study compared the development of clinical assessment and intervention skills between students enrolled in a face-to-face (F2F) or an asynchronous online clinical social work class. All students from three semesters of F2F (n = 74) and online (n = 78) sections of an MSW clinical class taught by the same instructor were included. Two assignments were used to compare students: an assessment and treatment plan of a fictional case and a digital role-play. A doctoral student who was blinded to the course delivery mechanism graded the role-play. After controlling for baseline differences in age, there were no differences between online and F2F students in skill demonstration. It appears clinical skills can be taught as effectively online as in F2F situations based on blinded review of role-plays.     

Generalized Reflexive Responding and Cross-Modal Tactile Transfer of Stimulus Function in Children with Autism

We sought to evaluate the efficacy of successive matching training for establishing generalized reflexive matching across 4 children with autism. In Experiment 1, differential reinforcement with delay fading was efficacious in establishing “yes” and “no” matching and nonmatching responses in 2 participants when 2 identical or nonidentical picture stimuli were presented. In addition, emergent visual–visual reflexive relational responses were observed using novel picture stimuli in a transfer test phase. In Experiment 2, differential reinforcement alone was efficacious in establishing matching and nonmatching responses in the other 2 participants when 2 identical or nonidentical objects were presented. Transfer to identical objects presented through touch (i.e., tactile discrimination) was additionally observed for both participants. Procedures in the study were adapted from the PEAK Relational Training System to aid in clinical replication, and the translational results have implications for language training with individuals with autism.     

Raccoon use of the urban matrix in the Baltimore Metropolitan Area, Maryland

The raccoon is often considered a synanthropic species; however, most urban research on this species has been restricted to urban parks or green spaces. Little is known about the persistence of synanthropic characteristics in the raccoon within the urban matrix. We examined density, den selection, home range size, habitat selection, and survival for adult raccoons (Procyon lotor) during summer (June?CAugust) and autumn (September?CNovember) in two residential neighborhoods, Linthicum located inland, and Riviera Beach on a peninsula in the Potomac river, in Southern Maryland. Den site selection varied by gender (P?=?0.0002) and study site (P?=?0.052), and study site interacted with gender (P?=?0.0063), with female raccoons denning preferentially on the ground and male raccoons in human structures in Riviera Beach while in Linthicum females denned preferentially in trees and males avoided human structures. Seasonal home range size was larger for males (P?<?0.0001) than females at both sites. Habitat selection varied at different hierarchical levels, and between gender, season and site. Intersite differences in habitat selection were apparent at the second order and third order scale. Aquatic and urban habitat was ranked high and woodland consistently lowest in second order scale at Riviera Beach while urban habitat was consistently ranked lowest at Linthicum where woodland ranked highest. Between the hierarchal scales (2nd and 3rd order) a difference in habitat selection occurred at Linthicum only where urban habitats ranked lowest at 3rd order. The differences in patterns of habitat selection we observed between two urban sites at different hierarchical scales suggest that resource selection is dependent upon the specific characteristics of the site and that raccoons exhibit variable responses to changes in landscape features. Finally, male survival tended to be lower (P?=?0.079) than female survival in both study sites. Our results reveal that raccoons can continue to exhibit synanthropic characteristics within the urban matrix even in areas with little natural habitat. This ability to adjust to different levels of development allows the raccoon to occur throughout most parts of the urban landscape, which has important management implications for human-raccoon conflicts and disease management.     

Empirical Prediction Intervals for County Population Forecasts

Population forecasts entail a significant amount of uncertainty, especially for long-range horizons and for places with small or rapidly changing populations. This uncertainty can be dealt with by presenting a range of projections or by developing statistical prediction intervals. The latter can be based on models that incorporate the stochastic nature of the forecasting process, on empirical analyses of past forecast errors, or on a combination of the two. In this article, we develop and test prediction intervals based on empirical analyses of past forecast errors for counties in the United States. Using decennial census data from 1900 to 2000, we apply trend extrapolation techniques to develop a set of county population forecasts; calculate forecast errors by comparing forecasts to subsequent census counts; and use the distribution of errors to construct empirical prediction intervals. We find that empirically-based prediction intervals provide reasonably accurate predictions of the precision of population forecasts, but provide little guidance regarding their tendency to be too high or too low. We believe the construction of empirically-based prediction intervals will help users of small-area population forecasts measure and evaluate the uncertainty inherent in population forecasts and plan more effectively for the future.