Change-point approach to data analytic wavelet thresholding

Previous proposals in data dependent wavelet threshold selection have used only the magnitudes of the wavelet coefficients in choosing a threshold for each level. Since a jump (or other unusual feature) in the underlying function results in several non-zero coefficients which are adjacent to each other, it is possible to use change-point approaches to take advantage of the information contained in the relative position of the coefficients as well as their magnitudes. The method introduced here represents an initial step in wavelet thresholding when coefficients are kept in the original order.     

Misconceptions about strength exercise among older adults

The purposes of this study were to determine current opinions of strength exercise among older adults and whether knowledge of recommended protocols differs between strength-exercise participants and nonparticipants. One hundred twenty-nine older adults (77.5 +/- 8.6 years) responded to questions about their opinions, experiences, and knowledge of strength-exercise recommendations. Some misconceptions were identified in the sample, with 48.4% of participants responding "no" to "strength training increases muscle mass," 45% responding "no" to "increasing weight is more important than number of repetitions for building strength," and 37% responding that walking is more effective than lifting weights at building muscle strength. The number of correct responses was related to the number of years in school (semipartial r(2)= .046). More education is needed about the benefits and recommendations to ensure proper use of current strength-exercise protocols among older adults.     

The ABCs of engagement in out-of-school-time programs

The rapid growth of out-of-school time programs over the past five years has resulted in a dramatic increase in opportunities for young people. However, many programs have been ill defined, without appropriate attention to the developmental needs of children and adolescents and without the necessary elements in place to fully capture the interests and talents of youth. In this chapter, the author shows how constructs drawn from research in education can be applied to research and practice in the out-of-school-time arena, in an effort to learn how the field can more fully engage young people in activities and programs. With more and more research indicating positive connections between participation in safe, supportive, and challenging activity settings and healthy psychological and social adjustment, attempts to encourage engagement rather than casual participation are warranted. Researchers and practitioners need to be mindful that engagement results not just from showing up, but from the interplay of the affective, behavioral, and cognitive experiences of youth in these settings. Suggestions for designing growth-enhancing contexts that increase the likelihood of engagement are offered, as are suggestions for future research in this area.     

Non-parametric procedure for knockout tournaments

In a seeded knockout tournament, where teams have some preassigned strength, do we have any assurances that the best team in fact has won? Is there some insight to be gained by considering which teams beat which other teams solely examining the seeds? We pose an answer to these questions by using the difference in the seeds of the two players as the basis for a test statistic. We offer several models for the underlying probability structure to examine the null distribution and power functions and determine these for small tournaments (less than five teams). One structure each for 8 teams and 16 teams is examined, and we conjecture an asymptotic normal distribution for the test statistic.     

Taking Subjectivity and Reflexivity Seriously: Implications of Social Constructionism for Researching Volunteer Motivation

This paper explores the contributions a social constructionist paradigm can make for researching volunteer motivation, by reflecting on an active membership study of volunteer netball coaches at a New Zealand high school. Social constructionism is based on philosophical assumptions which differ from those of positivism and post-positivism, the dominant paradigms for understanding and representing volunteer motivation. It highlights the social processes through which people give meaning to their motives and view researchers as necessarily implicated in this meaning-making process. Through a critique of the extant literature on volunteer motivation and an illustration of the insights of social constructionism from our empirical study, we consider how volunteer motivation research could be different if subjectivity and reflexivity were taken more seriously.     

Should I Stay or Should I Go? Children's Placement Preferences Longitudinally

ABSTRACT

Perceptions of permanency from the child's perspective can aid in giving voices to children impacted by foster care, thus promoting their personal sense of empowerment. This research represents a longitudinal assessment of how children living in foster care perceive permanency; specifically, their placement preferences while living in temporary foster care. Analyses were conducted on a subset of 2,671 children from the National Survey of Child and Adolescent Well-Being (NSCAW). Utilizing attachment and social capital constructs, children's preferences were predicted using Generalized Ordered Logistic regression analyses. Results demonstrated differences in children's perceptions and preferences for permanency at three waves of data collection.     

Properties of the rank transformation in factorial analysis of covariance

Real world data often fail to meet the underlying assumption of population normality. The Rank Transformation (RT) procedure has been recommended as an alternative to the parametric factorial analysis of covariance (ANCOVA). The purpose of this study was to compare the Type I error and power properties of the RT ANCOVA to the parametric procedure in the context of a completely randomized balanced 3 × 4 factorial layout with one covariate. This study was concerned with tests of homogeneity of regression coefficients and interaction under conditional (non)normality. Both procedures displayed erratic Type I error rates for the test of homogeneity of regression coefficients under conditional nonnormality. With all parametric assumptions valid, the simulation results demonstrated that the RT ANCOVA failed as a test for either homogeneity of regression coefficients or interaction due to severe Type I error inflation. The error inflation was most severe when departures from conditional normality were extreme. Also associated with the RT procedure was a loss of power. It is recommended that the RT procedure not be used as an alternative to factorial ANCOVA despite its encouragement from SAS, IMSL, and other respected sources.     

Estimation following selection of the largest of two normal means

This paper considers the problem of estimation when one of a number of populations, assumed normal with known common variance, is selected on the basis of it having the largest observed mean. Conditional on selection of the population, the observed mean is a biased estimate of the true mean. This problem arises in the analysis of clinical trials in which selection is made between a number of experimental treatments that are compared with each other either with or without an additional control treatment. Attempts to obtain approximately unbiased estimates in this setting have been proposed by Shen [2001. An improved method of evaluating drug effect in a multiple dose clinical trial. Statist. Medicine 20, 1913–1929] and Stallard and Todd [2005. Point estimates and confidence regions for sequential trials involving selection. J. Statist. Plann. Inference 135, 402–419]. This paper explores the problem in the simple setting in which two experimental treatments are compared in a single analysis. It is shown that in this case the estimate of Stallard and Todd is the maximum-likelihood estimate (m.l.e.), and this is compared with the estimate proposed by Shen. In particular, it is shown that the m.l.e. has infinite expectation whatever the true value of the mean being estimated. We show that there is no conditionally unbiased estimator, and propose a new family of approximately conditionally unbiased estimators, comparing these with the estimators suggested by Shen.