PREAMBLE......e4

APPENDIX 1......e121

APPENDIX 2......e122

APPENDIX 3......e124

REFERENCES......e124

It is important that the medical profession play a significant role in critically evaluating the use of diagnostic procedures and therapies as they are introduced in the detection, management,

/pdf/acc-aha-2006-guidelines-for-the-management-of-patients-with-27qfh9fc7i.pdf

ACC/AHA 2006 Guidelines for the Management of Patients With Valvular Heart Disease

2008 Focused Update Incorporated Into the ACC/AHA 2006 Guidelines for the Management of Patients With Valvular Heart Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 1998 Guidelines for the Management of Patients With Valvular Heart Disease) Endorsed by the Society of Cardiovascular Anesthesiologists, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons

SUMMARY The empirical distribution function based on a sample is well known to be the maximum likelihood estimate of the distribution from which the sample was taken. In this paper the likelihood function for distributions is used to define a likelihood ratio function for distributions. It is shown that this empirical likelihood ratio function can be used to construct confidence intervals for the sample mean, for a class of M-estimates that includes quantiles, and for differentiable statistical functionals. The results are nonparametric extensions of Wilks's (1938) theorem for parametric likelihood ratios. The intervals are illustrated on some real data and compared in a simulation to some bootstrap confidence intervals and to intervals based on Student's t statistic. A hybrid method that uses the bootstrap to determine critical values of the likelihood ratio is introduced.

Empirical likelihood ratio confidence intervals for a single functional

There is increasing interest in developing better predictive tools and a broader conceptual framework to guide the restoration of degraded land. Traditionally, restoration efforts have focused on re-establishing historical disturbance regimes or abiotic conditions, relying on successional processes to guide the recovery of biotic communities. However, strong feedbacks between biotic factors and the physical environment can alter the efficacy of these successional-based management efforts. Recent experimental work indicates that some degraded systems are resilient to traditional restoration efforts owing to constraints such as changes in landscape connectivity and organization, loss of native species pools, shifts in species dominance, trophic interactions and/or invasion by exotics, and concomitant effects on biogeochemical processes. Models of alternative ecosystem states that incorporate system thresholds and feedbacks are now being applied to the dynamics of recovery in degraded systems and are suggesting ways in which restoration can identify, prioritize and address these constraints.

/pdf/alternative-states-and-positive-feedbacks-in-restoration-3p92oa7stw.pdf

Alternative states and positive feedbacks in restoration ecology

https://cdr.lib.unc.edu/downloads/4m90dx441

ACC/AHA 2006 Guidelines for the Management of Patients With Valvular Heart Disease. A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 1998 Guidelines for the Management of Patients With Valvular Heart Disease)

The likelihood ratio method for confidence interval estimation of survival or life-time probabilities is investigated for censored data. This approach depends on a constrained product-limit estimator for the survival function. The likelihood method is compared with two alternative methods based on normal approximations to the product-limit estimator for several cases of uncensored and randomly censored samples. The methods are generalized for the ratio of two survival probabilities.

Confidence Interval Estimation of Survival Probabilities for Censored Data

A method is given for adjustment of the Neyman smooth goodness-of-fit test to allow for estimation of parameters in a composite hypothesis. With this method the limiting distribution under the hypothesis is chi-squared, in contrast to a method given by Barton for this problem. The basis of the method is a standard modification of the quadratic score statistic.

Neyman's Smooth Goodness-of-Fit Test When the Hypothesis Is Composite

We consider the estimation of a distribution function when observations from this distribution are contaminated by measurement error. The unknown distribution is modeled as a mixture of a finite number of known distributions. Model parameters can be estimated and confidence intervals constructed using well-known likelihood theory. We show that it is also possible to apply this approach to estimation of a unimodal distribution. An application is presented using data from a dietary survey. Simulation results are given to indicate the performance of the estimators and the confidence interval procedures.

Deconvolution of a Distribution Function

Statistical considerations in the analysis and reporting of time-related events. Application to analysis of prosthetic valve-related thromboembolism and pacemaker failure.

An experimental study was conducted in Tillamook, Oregon, USA, to quantify the effectiveness of edge-of-field vegetated buffers for reducing transport of fecal coliform bacteria (FCB) from agricultural fields amended with dairy cow manure. Installation of vegetated buffers on loamy soils dramatically reduced the bacterial contamination of runoff water from manure-treated pasturelands, but the size of the vegetated buffer was not an important determinant of bacterial removal efficiency. Only 10% of the runoff samples collected from treatment cells having vegetated buffers exhibited FCB concentrations >200 colony forming units (cfu)/100 mL (a common water quality standard value), and the median concentration for all cells containing vegetated buffers was only 6 cfu/100 mL. The presence of a vegetated buffer of any size, from 1 to 25 m, generally reduced the median FCB concentration in runoff by more than 99%. Results for FCB load calculations were similar. Our results suggest that where substantial FCB contamination of runoff occurs from manure-treated pasturelands, it might be disproportionately associated with specific field or management conditions, such as the presence of soils that exhibit low water infiltration and generate larger volumes of runoff or the absence of a vegetated buffer. Buffer size regulations that do not consider such differences might not be efficient or effective in reducing bacterial contamination of runoff.

/pdf/efficacy-of-vegetated-buffers-in-preventing-transport-of-ld29t8c5tt.pdf

David R. Thomas

Papers

Confidence Interval Estimation of Survival Probabilities for Censored Data

Neyman's Smooth Goodness-of-Fit Test When the Hypothesis Is Composite

Deconvolution of a Distribution Function

Statistical considerations in the analysis and reporting of time-related events. Application to analysis of prosthetic valve-related thromboembolism and pacemaker failure.

Efficacy of vegetated buffers in preventing transport of fecal coliform bacteria from pasturelands.