How do men with paraplegia choose activities in the light of striving for optimal participation? A qualitative study,based on a phenomenological–hermeneutical method

The objective of this study was to explore the experiences of men with paraplegia with regard to how they choose activities. The study involved a qualitative research design, based on a phenomenological–hermeneutical method. The findings revealed that the activities participants were choosing could be on a continuum between the individual’s self and the influence from their environment. On this continuum, the choice to perform activities was influenced by two mediating factors: the individual’s activities performed during their life-history, and their activity challenges for the future. We conclude that choosing activities is an individually constructed internal process of negotiation. Feelings of resignation and revolt appear in combination with feelings of justice and injustice when balance is not found. This knowledge provides a better understanding of the impact of spinal cord injury, sheds light on the development of distress after spinal cord injury and sheds new light on individuals’ feelings of participation.     

Modern times: an ethnographic study on the quality of life of people with a high support need in a Flemish residential facility

This ethnographic study shows the impact of the care system on clients' and staff's life experiences, with the clear distance between these two groups as one of the core issues. Together with a dominant care approach and a well established but subtile system of control, it makes them function in systems that are characterized by an oppressing care culture. Learned helplessness prevents both groups of acting upon quality of life outcomes. The idea of supporting a life of good quality through merely improving these traditional care systems should therefore be considered with caution, and real alternatives should be considered to open this barrier of the oppressing care culture.     

A local-influence-based diagnostic approach to a speeded item response theory model

Summary.  An item response theory model for dealing with omitted responses in a test is proposed. In this model formulation, non-response does not only depend on an examinee's ability and on item difficulty, but additionally also on 'test speededness'. Using a local-influence-based diagnostic approach, the sensitivity of the model regarding assumptions concerning the drop-out mechanism is explored. The methodology proposed is applied to the Chilean Sistema de Medición de la Calidad de la Educación mathematics test case-study.     

Regression modelling of weighted κ by using generalized estimating equations

In many clinical studies more than one observer may be rating a characteristic measured on an ordinal scale. For example, a study may involve a group of physicians rating a feature seen on a pathology specimen or a computer tomography scan. In clinical studies of this kind, the weighted κ coefficient is a popular measure of agreement for ordinally scaled ratings. Our research stems from a study in which the severity of inflammatory skin disease was rated. The investigators wished to determine and evaluate the strength of agreement between a variable number of observers taking into account patient-specific (age and gender) as well as rater-specific (whether board certified in dermatology) characteristics. This suggested modelling κ as a function of these covariates. We propose the use of generalized estimating equations to estimate the weighted κ coefficient. This approach also accommodates unbalanced data which arise when some subjects are not judged by the same set of observers. Currently an estimate of overall κ for a simple unbalanced data set without covariates involving more than two observers is unavailable. In the inflammatory skin disease study none of the covariates were significantly associated with κ, thus enabling the calculation of an overall weighted κ for this unbalanced data set. In the second motivating example (multiple sclerosis), geographic location was significantly associated with κ. In addition we also compared the results of our method with current methods of testing for heterogeneity of weighted κ coefficients across strata (geographic location) that are available for balanced data sets.     

An equivalence test for comparing DNA sequences

The practice of sequence alignment is constantly oscillating between the risk of overlooking important structure and that of discovering any arbitrarily defined kind of structure anywhere. On the other hand, the use of a condensed consensus sequence may lead to a substantial loss in valuable information. While adopting a Mahalanobis‐type index we allow for a certain degree of uncertainty in the measurements. This uncertainty may be caused by inaccurate measurements or ambiguity. In this paper, we test the similarity between DNA sequences within the framework of equivalence testing, accounting for both variances and covariances between frequencies of nucleotides. Statistical methods for testing equivalence were first developed in the context of pharmacokinetics and later extended to the field of clinical trials. Nowadays, (bio)equivalence tests seem to be less frequently used outside the drug testing field, including statistical genetics. Copyright © 2005 John Wiley & Sons, Ltd.     

Screening for prostate cancer by using random-effects models

Summary. Random-effects models are used to screen male participants in a long-term longitudinal study for prostate cancer. By using posterior probabilities, each male can be classified into one of four diagnostic states for prostate disease: normal, benign prostatic hyperplasia, local cancer and metastatic cancer. Repeated measurements of prostate-specific antigen, collected when there was no clinical evidence of prostate disease, are used in the classification process. An individual's screening data are considered one repeated measurement at a time as his data are collected longitudinally over time. Posterior probabilities are calculated on the basis of data from other individuals with confirmed diagnoses of each of the four diagnostic states.     

Odorous childhoods and scented worlds of learning: a sensory history of health and outdoor education initiatives in Western Europe (1900s-1960s)

ABSTRACT

This paper develops a sensory history of health and outdoor education initiatives which featured (non-)formal schooling, analyzing these as belonging to (a) scented and more generally sensed world(s) of learning. Working with photographs as sensory objects of affect, and using as examples Belgian and Luxembourg open-air schools and associated sanitary and social welfare provisions, the paper explores issues that have gone under-researched in sensory scholarship internationally: those of precise educational purposes, methods, processes and effects of sensory engagement, particularly pertaining to “smell”. Sensory practices and experiences and uses of senses generally are thereby traced in/as “situated, embodied” movements inextricably “enmeshed” with symbolism. The paper argues that while the educational goals underpinning the initiatives investigated and the approaches and practices characterizing these have changed, some (un)intended effects still have an impact today, for instance through Forest School as given shape in the United Kingdom. The concept of “odorous”, or rather “sensuous childhoods”, is proposed to denote ways that particular target groups have come to be imagined as in need of explicitly sensorial health and outdoor education.     

Fat tail distributions and local thin tail alternatives

The behaviour of the Hill estimator for the tail index of fat tailed distributions in the presence of local alternatives which have a thin tail is investigated. The converse problem is also briefly addressed. A local thin tail alternative can severely bias the Hill statistic. The relevance of this issue for the class of stable distributions is discussed. We conduct a small simulation study to support the analysis. In the conclusion it is argued that for moderate out of sample quantile analysis the problem of local alternatives may be less pressing.     

Fast,closed-form,and efficient estimators for hierarchical models with AR(1) covariance and unequal cluster sizes

This article is concerned with statistically and computationally efficient estimation in a hierarchical data setting with unequal cluster sizes and an AR(1) covariance structure. Maximum likelihood estimation for AR(1) requires numerical iteration when cluster sizes are unequal. A near optimal non-iterative procedure is proposed. Pseudo-likelihood and split-sample methods are used, resulting in computing weights to combine cluster size specific parameter estimates. Results show that the method is statistically nearly as efficient as maximum likelihood, but shows great savings in computation time.