Achieving a national sample of nursing homes: Balancing probability techniques and practicalities

Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Ionization and breakdown in sf6-air and freon-nitrogen mixtures

The sparking potentials and swarm coefficients (ionization and attachment coefficients) have been measured in sulphurhexafluoride- air and freon-nitrogen mixtures over the range of 110 ¿ E/p ¿ 240 V cm-1 torr-l and gas pressures varying between 1 and 20 torr, at 20°C. Addition of strongly attaching salphur-hexafluoride and freon gases increased the sparking potentials and the rate of increase of the attachment coefficient with increasing percentage of the strongly attaching gases in the mixtures was much larger than the rate of change of the first ionization coefficient.

Impulse Voltage Breakdown Characteristics of Point-Plane Gaps at Low Pressures

Practical applications of vacuum as an insulator necessitated determining the low-pressure breakdown characteristics of long gap lengths of a point-plane electrode system. The breakdown voltage has been found to vary as the square root of the gap length. Further, with the point electrode as the anode, the values of the breakdown voltages obtained have been found to be larger than those obtained with a plane-parallel electrode system at a corresponding gap length. By applying the theory of the anode heating mechanism as the cause for breakdown, the results have been justified, and by utilizing a field efficiency factor which is the ratio of the average to maximum field, an empirical criterion has been developed. This criterion helps in calculating the breakdown voltage of a nonuniform gap system by the knowledge of the breakdown voltage of a plane-parallel electrode system.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Some investigations on secondary breakdown in p-n junctions considering the effect of thermally generated carriers

The V-I characteristic of a p-n junction under breakdown is calculated taking the thermally generated carriers into account. The current density distributions computed under different conditions have been given. The light emission and other characteristics reported by Chiang and Lauritzen and others have been explained.

A lower bound to the survival probability and an approximate first passage time distribution for Markovian and non-Markovian dynamics in phase space

We derive a very general expression of the survival probability and the first passage time distribution for a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space, which is valid irrespective of the statistical nature of the dynamics. The expression, together with the Jensen's inequality, naturally leads to a lower bound to the actual survival probability and an approximate first passage time distribution. These are expressed in terms of the position-position, velocity-velocity, and position-velocity variances. Knowledge of these variances enables one to compute a lower bound to the survival probability and consequently the first passage distribution function. As examples, we compute these for a Gaussian Markovian process and, in the case of non-Markovian process, with an exponentially decaying friction kernel and also with a power law friction kernel. Our analysis shows that the survival probability decays exponentially at the long time irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant.

Estimation of thermal breakdown voltage of HVDC cables - A theoretical framework

The insulation in a dc cable is subjected to both thermal and electric stress at the same time. While the electric stress is generic to the cable, the temperature rise in the insulation is, by and large, due to the Ohmic losses in the conductor. The consequence of this synergic effect is to reduce the maximum operating voltage and causes a premature failure of the cable. The authors examine this subject in some detail and propose a comprehensive theoretical formulation relating the maximum thermal voltage (MTV) to the physical and geometrical parameters of the insulation. The heat flow patterns and boundary conditions considered by the authors here and those found in earlier literature are provided. The MTV of a dc cable is shown to be a function of the load current apart from the resistance of the insulation. The results obtained using the expressions, developed by the authors, are compared with relevant results published in the literature and found to be in close conformity.

Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains

We consider the problem of detecting statistically significant sequential patterns in multineuronal spike trains. These patterns are characterized by ordered sequences of spikes from different neurons with specific delays between spikes. We have previously proposed a data-mining scheme to efficiently discover such patterns, which occur often enough in the data. Here we propose a method to determine the statistical significance of such repeating patterns. The novelty of our approach is that we use a compound null hypothesis that not only includes models of independent neurons but also models where neurons have weak dependencies. The strength of interaction among the neurons is represented in terms of certain pair-wise conditional probabilities. We specify our null hypothesis by putting an upper bound on all such conditional probabilities. We construct a probabilistic model that captures the counting process and use this to derive a test of significance for rejecting such a compound null hypothesis. The structure of our null hypothesis also allows us to rank-order different significant patterns. We illustrate the effectiveness of our approach using spike trains generated with a simulator.

Women and Marital Breakdown in South India : Reconstructing Homes, Bonds and Persons

Women and Marital Breakdown in South India: Reconstructing Homes, Bonds and Persons is an ethnographic analysis of the situation of divorced and separated women and their families in the South Indian city of Bangalore. The study is based on 16 months of anthropological fieldwork, i.e., participant observation and life history interviews among 50 divorced and separated women from different socio-religious backgrounds in their homes, in the women s organisations and in the Family Court. The study follows the divorced and separated women from their natal homes to their affinal homes through homelessness and legal battles to their reconstructed natal, affinal or single homes in order to find out what it means to be a person within hierarchical gender and kinship relations in South India. Marital breakdown impacts on kin relations and discloses the existing gender relations and power structure through its consequences. It makes the transformability of relational personhood as well as the transformability of relational society and culture visible. Although the study reveals the painful history of women s ill-treatment in marriage, family and kinship systems, it also demonstrates the women s rejection of the domination; and shows their ability to re-negotiate and promote changes not only to their own positions but to the whole hierarchical system as well. The study explores the divorced and separated women s manifold dilemmas, complicated legal battles, and endless arrangements when they have to struggle with the very practical problems of supporting themselves financially, finding and making a new home for themselves, and re-arranging relationships with their kin and friends. As marital breakdown fundamentally transforms the women s relational field, it forces them to recreate substitutive relations in a flexible way and, simultaneously, to re-construct themselves and their lives without a ready or positive cultural or behavioural template. This process reveals the agency of the divorced and separated women as well as shedding light on issues of gender and the cultural construction of the person in South India. This topical study explores the previously neglected subject of marital breakdown in India and shows the new meaning of kinship in South India.

Reactive characteristics of narrow germanium p-n junctions in the breakdown region

An inductive behaviour observed in germanium p-n junctions in the breakdown region is reported.

Reverse bias capacitance measurements on copper-doped germanium p-n junctions in the breakdown region

Results of measurements at a high frequency on reverse bias capacitance of copper-doped germanium junctions are reported. Phenomenal increase in capacitance is found in the breakdown region, particularly at low temperatures.

Impulse-voltage breakdown characteristics of large gaps at low pressures

A study of the gap breakdown voltage characteristic at a low pressure of 7×10-5 Torr with a standard (1/50)-μsec impulse-voltage wave reveals an agreement with the criterion Vb=Cd0.5 suggested by Cranberg. Voltage-time-to-breakdown characteristics has also been determined. From these studies, it is concluded that impulse breakdown in vacuum is initiated by an electron current heating an anode spot and thereby liberating a clump which causes breakdown.

First passage probability during random vibration

The probability that a random process crosses an arbitrary level for the first time is expressed as a Gram—Charlier series, the leading term of which is the Poisson approximation. The coefficients of this series are related to the moments of the number of level crossings. The results are applicable to both stationary and non-stationary processes. Some numerical results are presented for the response process of a linear single-degree-of-freedom oscillator under Gaussian white noise excitation.