			Home About us Contact

Reliable Inferences (reliable + inference)

Distribution by Scientific Domains

Life Sciences	60%

Selected Abstracts

Seeking a second opinion: uncertainty in disease ecology

ECOLOGY LETTERS, Issue 6 2010
Brett T. McClintock
Ecology Letters (2010) 13: 659,674 Abstract Analytical methods accounting for imperfect detection are often used to facilitate reliable inference in population and community ecology. We contend that similar approaches are needed in disease ecology because these complicated systems are inherently difficult to observe without error. For example, wildlife disease studies often designate individuals, populations, or spatial units to states (e.g., susceptible, infected, post-infected), but the uncertainty associated with these state assignments remains largely ignored or unaccounted for. We demonstrate how recent developments incorporating observation error through repeated sampling extend quite naturally to hierarchical spatial models of disease effects, prevalence, and dynamics in natural systems. A highly pathogenic strain of avian influenza virus in migratory waterfowl and a pathogenic fungus recently implicated in the global loss of amphibian biodiversity are used as motivating examples. Both show that relatively simple modifications to study designs can greatly improve our understanding of complex spatio-temporal disease dynamics by rigorously accounting for uncertainty at each level of the hierarchy. [source]

Screening for mild cognitive impairment: a systematic review

INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY, Issue 9 2009
Jane A. Lonie
Abstract Objective Patients with mild cognitive impairment account for a significant number of referrals to old age psychiatry services and specialist memory clinics. The cognitive evaluation of such patients is commonly restricted to brief dementia screens, with no consideration to their suitability for assessing MCI. Here, we review the utility of such cognitive screens for MCI and provide an overview of validated instruments. Methods We identified papers published after Petersen and colleagues 1999 MCI criteria (Petersen et al., 1999) and examining face-to-face cognitive screening for MCI from publication databases using combinations of the search terms ,mild cognitive impairment' and ,cognitive screening'. We also combined the former search with the names of 39 screening tests recently identified in a relevant review (Cullen et al., 2007). Results Fifteen cognitive screening instruments were identified, 11 cover a restricted range of cognitive domains. High sensitivity and specificity for MCI relative to healthy controls were reported for two comprehensive and two noncomprehensive screening instruments, adequate test-retest and inter-rater reliability for only one of these. With the exception of three studies, sample sizes were universally small (i.e. n,,,100), and prognostic values were reported for only two of the identified 15 screening measures. Sensitivities of the full domain measures were universally high, but information about their specificity against psychiatric and non-progressive neurological conditions and predictive validity is lacking. Conclusion Several cognitive screening instruments afford the clinician the ability to detect MCI, early AD, and in some cases non-AD dementia, but they cannot currently be used to make reliable inferences about the course and eventual outcome of MCI. Copyright © 2009 John Wiley & Sons, Ltd. [source]

MPowering ecologists: community assembly tools for community assembly rules

OIKOS, Issue 7 2010
Joshua Ladau
Null model tests of presence,absence data (,NMTPAs') provide important tools for inferring effects of competition, facilitation, habitat filtering, and other ecological processes from observational data. Many NMTPAs have been developed, but they often yield conflicting conclusions when applied to the same data. Type I and II error rates, size, power, robustness and bias provide important criteria for assessing which tests are valid, but these criteria need to be evaluated contingent on the sample size, null hypothesis of interest, and assumptions that are appropriate for the data set that is being analyzed. In this paper, we confirm that this is the case using the software MPower, evaluating the validity of NMTPAs contingent on the null hypothesis being tested, assumptions that can be made, and sample size. Evaluating the validity of NMTPAs contingent on these factors is important towards ensuring that reliable inferences are drawn from observational data about the processes controlling community assembly. [source]

Robust Estimation and Outlier Detection for Overdispersed Multinomial Models of Count Data

AMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 2 2004
Walter R. Mebane Jr.
We develop a robust estimator,the hyperbolic tangent (tanh) estimator,for overdispersed multinomial regression models of count data. The tanh estimator provides accurate estimates and reliable inferences even when the specified model is not good for as much as half of the data. Seriously ill-fitted counts,outliers,are identified as part of the estimation. A Monte Carlo sampling experiment shows that the tanh estimator produces good results at practical sample sizes even when ten percent of the data are generated by a significantly different process. The experiment shows that, with contaminated data, estimation fails using four other estimators: the nonrobust maximum likelihood estimator, the additive logistic model and two SUR models. Using the tanh estimator to analyze data from Florida for the 2000 presidential election matches well-known features of the election that the other four estimators fail to capture. In an analysis of data from the 1993 Polish parliamentary election, the tanh estimator gives sharper inferences than does a previously proposed heteroskedastic SUR model. [source]

Relationships among non-native plants, diversity of plants and butterflies, and adequacy of spatial sampling

BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 2 2005
ERICA FLEISHMAN
Non-native invasive species are altering ecosystems in undesirable ways, often leading to biotic homogenization and rapid reduction of evolutionary potential. However, lack of money and time hampers attempts to monitor the outcome of restoration efforts. Hence, it is useful to determine whether relatively limited sampling can provide valid inferences about biological responses to pattern-based and process-based variables that are affected by restoration actions. In the Mojave Desert, invasion of salt-cedar (Tamarix ramosissima) has altered vegetational communities and some measures of faunal diversity. We tested whether six vegetation-based predictor variables affected species richness of butterflies in the Muddy River drainage (Nevada, USA). We also explored whether similar conclusions about relationships between vegetation and butterflies could have been obtained by using data from a subset of the 85 locations included in the study. We found that the effect of non-native plants on species richness of butterflies was negligible. Availability of nectar had the greatest independent explanatory power on species richness of butterflies, followed by species richness of plants. In comparison with the full data set, subsamples including 10, 25 and 50% of sites yielded similar conclusions. Our results suggest that relatively limited data sets may allow us to draw reliable inferences for adaptive management in the context of ecological restoration and rehabilitation. © 2005 The Linnean Society of London, Biological Journal of the Linnean Society, 2005, 85, 157,166. [source]