Extra Care Housing in the UK: Can it be a Home for Life?

Extra care housing is believed to constitute a home for life, precluding the need for institutional accommodations, but currently there is little substantiating evidence. Longitudinal data show that 8.2% of extra care housing residents will move to institutional accommodations after 5 years. Matching analyses suggest that extra care housing residents aged 80 years and older are approximately half as likely to enter institutional care compared with older people in the community in receipt of domiciliary care, albeit with some caveats. Extra care housing may embody a home for life for the majority of residents, although a substantial minority is likely to require institutional care.     

Nonuniqueness of least absolute values regression

The question of nonuniqueness of the least absolute values (L₁) regression is discussed, and examples are given of situations where the L₁-regression is unique and where it has 2, 3 and 4 limiting positions. A method is proposed for finding a compromise regression line when the L₁ regression is not unique. Suggestions are made for further research.     

Another look at plotting positions

Probability paper was used as early as 1896, and was mentioned in the literature more than 30 times before 1950, mainly by hydrologists, most of whom used the plotting position (i-0.5)/n proposed by Hazen (1914). Gumbel (1942a) considered the modal position (i-1)/(n-1) and the mean position i/(n+1) [the latter proposed by Weibull (1939a,b)], and chose the latter. Lebedev (1952) and others proposed the use of (i-0.3)/(n+0.4), which is approximately the median position advocated by Johnson (1951). Blom (1958) sug-gested (i-α)/(n-2α+1), where a is a constant (usually 0 ≤ α ≤ 1), which includes all of the above plotting positions as special cases. Moreover, by proper choice of α, one can approximate F[E(x_i)], the position proposed by Kimball (1946), for any distri-bution of interest. Gumbel (1954) stated five postulates which plotting positions should satisfy. Chernoff & Lieberman (1954) discussed the optimum choice of plotting positions in various situ-ations. It is clear that the optimum plotting position depends on the use that is to be made of the results and may also depend on the underlying distribution. The author endeavors to formulate recommendations as to the best choice in various situations.     

Classification with discrete and continuous variables via general mixed-data models

We study the problem of classifying an individual into one of several populations based on mixed nominal, continuous, and ordinal data. Specifically, we obtain a classification procedure as an extension to the so-called location linear discriminant function, by specifying a general mixed-data model for the joint distribution of the mixed discrete and continuous variables. We outline methods for estimating misclassification error rates. Results of simulations of the performance of proposed classification rules in various settings vis-à-vis a robust mixed-data discrimination method are reported as well. We give an example utilizing data on croup in children.     

Controlling epileptic seizures in a neural mass model

In an effort to understand basic functional mechanisms that can produce epileptic seizures, we introduce some key features in a model of coupled neural populations that enable the generation of seizure-like events and similar dynamics with the ones observed during the route of the epileptic brain towards real seizures. In this model, modified from David and Friston’s neural mass model, an internal feedback mechanism is incorporated to maintain synchronous behavior within normal levels despite elevated coupling. Normal internal feedback quickly regulates an abnormally high coupling between the neural populations, whereas pathological internal feedback can lead to hypersynchronization and the appearance of seizure-like high amplitude oscillations. Feedback decoupling is introduced as a robust seizure control strategy. An external feedback decoupling controller is introduced to maintain normal synchronous behavior. The results from the analysis in this model have an interesting physical interpretation and specific implications for the treatment of epileptic seizures. The proposed model and control scheme are consistent with a variety of recent observations in the human and animal epileptic brain, and with theories from nonlinear systems, adaptive systems, optimization, and neurophysiology.     

Individual Differences in the Pathways into and Beyond Higher Education in the UK: A Life-Course Approach

This article uses data from the UK 1970 Birth Cohort ( N = 10,000) to address the research questions: (a) Who in this cohort made the transition to higher education (HE), and (b) how are the benefits and risks of such participation distributed? We assess the way that the benefits and risks of participation differ according to family background and child development, finding risks to mental health for individuals who attend HE against the odds. We also explore the errors in prediction of standard statistical models in order to introduce a discussion of selection bias linked to a broader policy question of the appreciation of the complexity and idiosyncrasy of individuals' educational pathways. We explore this question in relation to three particular cases that confound the prediction of the statistical analysis in order to clarify the assumptions and limitations of a standard analysis in approaching the problems of developing policy that recognizes individual heterogeneity and diversity .     

A monte carlo of plotting positions

A Monte Carlo study was made of the effects of using simple linear regression, on the appropriate probability paper, to estimate parameters, quantiles and cumulative probability for several distributions. These distributions were the Normal, Weibull (shape parameters 1, 2, and 4) and the Type I largest extreme-value distributions. The specific objective was to observe differences arising from choice of plotting positions. Plotting positions used were i/(n+l), (i?3)/(n+.04), (i?.5)/n, either (i?.375)/(n+.25) or (i?.4)/(n+.2), and either F[E(Y_i)] or F[E(£n Y)]. For each combination of 4 sample sizes (n=10(10)(40)), distribution, and plotting position, regression lines were found for each of N =9999 samples. Each regression line was used to estimate: (1) quantiles of 9 specific probabilities, (2) probabilities of 9 specific quantiles, and (3) return periods corresponding to 9 specific quantiles. Compa[rgrave]ison of the mean, variances, mean square error and medians of these estimates and of the regression coefficients confirm some results of Harter [Commun. Statist. A13(13), 1984] and provide further insight.     

Source Data Perturbation and consistent sets of safe tables

When tables are generated from a data file, the release of those tables should not reveal too detailed information concerning individual respondents. The disclosure of individual respondents in the microdata file can be prevented by applying disclosure control methods at the table level (by cell suppression or cell perturbation), but this may create inconsistencies among other tables based on the same data file. Alternatively, disclosure control methods can be applied at the microdata level, but these methods may change the data permanently and do not account for specific table properties. These problems can be circumvented by assigning a (single and fixed) weight factor to each respondent/record in the microdata file. Normally this weight factor is equal to 1 for each record, and is not explicitly incorporated in the microdata file. Upon tabulation, each contribution of a respondent is weighted multiplicatively by the respondent's weight factor. This approach is called Source Data Perturbation (SDP) because the data is perturbed at the microdata level, not at the table level. It should be noted, however, that the data in the original microdata is not changed; only a weight variable is added. The weight factors can be chosen in accordance with the SDC paradigm, i.e. such that the tables generated from the microdata are safe, and the information loss is minimized. The paper indicates how this can be done. Moreover it is shown that the SDP approach is very suitable for use in data warehouses, as the weights can be conveniently put in the fact tables. The data can then still be accessed and sliced and diced up to a certain level of detail, and tables generated from the data warehouse are mutually consistent and safe.