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Incorrect Assumption (incorrect + assumption)
Selected AbstractsHaplotype analysis in the presence of informatively missing genotype dataGENETIC EPIDEMIOLOGY, Issue 4 2006Nianjun Liu Abstract It is common to have missing genotypes in practical genetic studies, but the exact underlying missing data mechanism is generally unknown to the investigators. Although some statistical methods can handle missing data, they usually assume that genotypes are missing at random, that is, at a given marker, different genotypes and different alleles are missing with the same probability. These include those methods on haplotype frequency estimation and haplotype association analysis. However, it is likely that this simple assumption does not hold in practice, yet few studies to date have examined the magnitude of the effects when this simplifying assumption is violated. In this study, we demonstrate that the violation of this assumption may lead to serious bias in haplotype frequency estimates, and haplotype association analysis based on this assumption can induce both false-positive and false-negative evidence of association. To address this limitation in the current methods, we propose a general missing data model to characterize missing data patterns across a set of two or more markers simultaneously. We prove that haplotype frequencies and missing data probabilities are identifiable if and only if there is linkage disequilibrium between these markers under our general missing data model. Simulation studies on the analysis of haplotypes consisting of two single nucleotide polymorphisms illustrate that our proposed model can reduce the bias both for haplotype frequency estimates and association analysis due to incorrect assumption on the missing data mechanism. Finally, we illustrate the utilities of our method through its application to a real data set. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source] A critical essay on professional development in dietetics through a process of reflection and clinical supervisionJOURNAL OF HUMAN NUTRITION & DIETETICS, Issue 5 2000S. Burton Background The concept of clinical supervision is well known within the nursing profession though numerous definitions and theoretical models proposed for implementation have led to a degree of confusion. The debate within dietetics is just beginning, with the recent formation of a BDA working group seeking to clarify clinical supervision for the profession. Aims This essay provides an overview of clinical supervision together with reflection which is considered to be integral to the process and proposes that clinical supervision can provide a vehicle for supporting continuous professional development for all dietitans. It is perhaps unfortunate that the descriptive ,clinical' is used throughout the literature as this often leads to an incorrect assumption that the scope of the process is limited to acute services. However, as patient care takes many forms within a range of environments, the broader meaning of ,clinical' as pertaining to ,patient care' needs to be acknowledged. Caution in choosing a model for the profession is advised, as any model needs to fit the practice and not vice versa. [source] Movement patterns and study area boundaries: influences on survival estimation in capture,mark,recapture studiesOIKOS, Issue 8 2008Gregg E. Horton The inability to account for the availability of individuals in the study area during capture,mark,recapture (CMR) studies and the resultant confounding of parameter estimates can make correct interpretation of CMR model parameter estimates difficult. Although important advances based on the Cormack,Jolly,Seber (CJS) model have resulted in estimators of true survival that work by unconfounding either death or recapture probability from availability for capture in the study area, these methods rely on the researcher's ability to select a method that is correctly matched to emigration patterns in the population. If incorrect assumptions regarding site fidelity (non-movement) are made, it may be difficult or impossible as well as costly to change the study design once the incorrect assumption is discovered. Subtleties in characteristics of movement (e.g. life history-dependent emigration, nomads vs territory holders) can lead to mixtures in the probability of being available for capture among members of the same population. The result of these mixtures may be only a partial unconfounding of emigration from other CMR model parameters. Biologically-based differences in individual movement can combine with constraints on study design to further complicate the problem. Because of the intricacies of movement and its interaction with other parameters in CMR models, quantification of and solutions to these problems are needed. Based on our work with stream-dwelling populations of Atlantic salmon Salmo salar, we used a simulation approach to evaluate existing CMR models under various mixtures of movement probabilities. The Barker joint data model provided unbiased estimates of true survival under all conditions tested. The CJS and robust design models provided similarly unbiased estimates of true survival but only when emigration information could be incorporated directly into individual encounter histories. For the robust design model, Markovian emigration (future availability for capture depends on an individual's current location) was a difficult emigration pattern to detect unless survival and especially recapture probability were high. Additionally, when local movement was high relative to study area boundaries and movement became more diffuse (e.g. a random walk), local movement and permanent emigration were difficult to distinguish and had consequences for correctly interpreting the survival parameter being estimated (apparent survival vs true survival). [source] Coping With Uncertainties in Advance Care PlanningJOURNAL OF COMMUNICATION, Issue 3 2001Stephen C. Hines This essay extends problematic integration theory and related theories of uncertainty management to communication about serious illness and death. These extensions (a) note that theorizing must focus on multiple, interrelated uncertainties rather than a single such uncertainty; (b) explain how communication with others often problematizes efforts to cope with illness-related uncertainties; and (c) identify specific factors that may influence how persons choose to cope with these uncertainties. The essay describes implications for ongoing efforts to improve communication with persons nearing death. Specifically, they point to 5 incorrect assumptions that limit the effectiveness of current efforts to encourage persons to talk about their end-of-life preferences with others in a process referred to as advance care planning and then suggest concrete changes derived from this framework that can improve the advance care planning process and enhance the quality of end-of- life care. [source] How to account for the lipid effect on carbon stable-isotope ratio (,13C): sample treatment effects and model biasJOURNAL OF FISH BIOLOGY, Issue 4 2008K. Mintenbeck This study investigated the impact of lipid extraction, CaCO3 removal and of both treatments combined on fish tissue ,13C, ,15N and C:N ratio. Furthermore, the suitability of empirical ,13C lipid normalization and correction models was examined. ,15N was affected by lipid extraction (increase of up to 1·65,) and by the combination of both treatments, while acidification alone showed no effect. The observed shift in ,15N represents a significant bias in trophic level estimates, i.e. lipid-extracted samples are not suitable for ,15N analysis. C:N and ,13C were significantly affected by lipid extraction, proportional to initial tissue lipid content. For both variables, rates of change with lipid content (,C:N and ,,13C) were species specific. All tested lipid normalization and correction models produced biased estimates of fish tissue ,13C, probably due to a non-representative database and incorrect assumptions and generalizations the models were based on. Improved models need a priori more extensive and detailed studies of the relationships between lipid content, C:N and ,13C, as well as of the underlying biochemical processes. [source] Movement patterns and study area boundaries: influences on survival estimation in capture,mark,recapture studiesOIKOS, Issue 8 2008Gregg E. Horton The inability to account for the availability of individuals in the study area during capture,mark,recapture (CMR) studies and the resultant confounding of parameter estimates can make correct interpretation of CMR model parameter estimates difficult. Although important advances based on the Cormack,Jolly,Seber (CJS) model have resulted in estimators of true survival that work by unconfounding either death or recapture probability from availability for capture in the study area, these methods rely on the researcher's ability to select a method that is correctly matched to emigration patterns in the population. If incorrect assumptions regarding site fidelity (non-movement) are made, it may be difficult or impossible as well as costly to change the study design once the incorrect assumption is discovered. Subtleties in characteristics of movement (e.g. life history-dependent emigration, nomads vs territory holders) can lead to mixtures in the probability of being available for capture among members of the same population. The result of these mixtures may be only a partial unconfounding of emigration from other CMR model parameters. Biologically-based differences in individual movement can combine with constraints on study design to further complicate the problem. Because of the intricacies of movement and its interaction with other parameters in CMR models, quantification of and solutions to these problems are needed. Based on our work with stream-dwelling populations of Atlantic salmon Salmo salar, we used a simulation approach to evaluate existing CMR models under various mixtures of movement probabilities. The Barker joint data model provided unbiased estimates of true survival under all conditions tested. The CJS and robust design models provided similarly unbiased estimates of true survival but only when emigration information could be incorporated directly into individual encounter histories. For the robust design model, Markovian emigration (future availability for capture depends on an individual's current location) was a difficult emigration pattern to detect unless survival and especially recapture probability were high. Additionally, when local movement was high relative to study area boundaries and movement became more diffuse (e.g. a random walk), local movement and permanent emigration were difficult to distinguish and had consequences for correctly interpreting the survival parameter being estimated (apparent survival vs true survival). [source] | ||||||||||