Book Reviews

Michael Seltzer, Christian Kullberg, Soren Peter Olesen, Ilmari Rostila (eds): Listening to the Welfare State. Aldershot, Ashgate, 2001. 267 pp, ISBN 0-7546-1565-0, £45.00     

Power, Politics, and the Framing of Environmental Illness

The medical community, along with other government agencies, has created its own frame of environmental illness. This frame has been generally accepted by the American public. In this paper we discuss framing in general and the factors related to how the environmental illness frame has been constructed and maintained. We offer a brief history of the medical institution and illustrate the frame with its definitions of environmental illness. Qualitative data from a study of Oak Ridge, a contaminated community located in Tennessee, are examined to analyze the consequences of challenging the environmental illness frame. Implications for future research are discussed.     

Ridge Autoregression Estimation: LS Method

In an AR (p)-model, least-squares estimation of the parameters is considered when it is suspected that the parameters may belong to a linear subspace and the estimated covariance matrix is ill-conditioned. Accordingly, we define five estimators and study their properties in an asymptotic setup to discover dominance properties based on asymptotic distributional bias (ADB), MSE (ADMSE) matrices, and under quadratic risks (ADQR).     

Linear Increments with Non‐monotone Missing Data and Measurement Error

Linear increments (LI) are used to analyse repeated outcome data with missing values. Previously, two LI methods have been proposed, one allowing non‐monotone missingness but not independent measurement error and one allowing independent measurement error but only monotone missingness. In both, it was suggested that the expected increment could depend on current outcome. We show that LI can allow non‐monotone missingness and either independent measurement error of unknown variance or dependence of expected increment on current outcome but not both. A popular alternative to LI is a multivariate normal model ignoring the missingness pattern. This gives consistent estimation when data are normally distributed and missing at random (MAR). We clarify the relation between MAR and the assumptions of LI and show that for continuous outcomes multivariate normal estimators are also consistent under (non‐MAR and non‐normal) assumptions not much stronger than those of LI. Moreover, when missingness is non‐monotone, they are typically more efficient.     

The effect of a novel ADL-based training program on performance of activities of daily living and physical fitness

The purpose of this study was to determine the degree to which a novel training program based on activities of daily living (ADL) would affect performance of ADLs, as well as the fitness of older adults. Fourteen individuals (mean age 82 years) took part in a 10-week control period followed by a 10-week ADL-based training program. Pre- and posttests included the Physical Performance Test (PPT), the Physical Functional Performance-10 (PFP-10), and the Senior Fitness Test (SFT). After the training period, improvements ranging from 7% to 33% (p<.05) were seen on the PPT and PFP-10 and on three items of the SFT. After conversion to standard scores, the magnitude of change in the PPT and the PFP10 was significantly greater (p<.05) than the magnitude of change in the SFT. These data support the idea that this novel ADL-based training program was able to facilitate improved performance of ADLs, as well as select measures of fitness among older adults.