Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps

We compare two approaches for estimating the distribution of consumers' willingness to pay (WTP) in discrete choice models. The usual procedure is to estimate the distribution of the utility coefficients and then derive the distribution of WTP, which is the ratio of coefficients. The alternative is to estimate the distribution of WTP directly. We apply both approaches to data on site choice in the Alps. We find that the alternative approach fits the data better, reduces the incidence of exceedingly large estimated WTP values, and provides the analyst with greater control in specifying and testing the distribution of WTP. © 2008 Agricultural and Applied Economics Association.

It's not that I don't care, I just don't care very much: confounding between attribute non-attendance and taste heterogeneity

With the growing interest in the topic of attribute non-attendance, there is now widespread use of latent class (LC) structures aimed at capturing such behaviour, across a number of different fields. Specifically, these studies rely on a confirmatory LC model, using two separate values for each coefficient, one of which is fixed to zero while the other is estimated, and then use the obtained class probabilities as an indication of the degree of attribute non-attendance. In the present paper, we argue that this approach is in fact misguided, and that the results are likely to be affected by confounding with regular taste heterogeneity. We contrast the confirmatory model with an exploratory LC structure in which the values in both classes are estimated. We also put forward a combined latent class mixed logit model (LC-MMNL) which allows jointly for attribute non-attendance and for continuous taste heterogeneity. Across three separate case studies, the exploratory LC model clearly rejects the confirmatory LC approach and suggests that rates of non-attendance may be much lower than what is suggested by the standard model, or even zero. The combined LC-MMNL model similarly produces significant improvements in model fit, along with substantial reductions in the implied rate of attribute non-attendance, in some cases even eliminating the phenomena across the sample population. Our results thus call for a reappraisal of the large body of recent work that has implied high rates of attribute non-attendance for some attributes. Finally, we also highlight a number of general issues with attribute non-attendance, in particular relating to the computation of willingness to pay measures.

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Oxygenation-sensitive cardiovascular magnetic resonance imaging (OS-CMR) : potential confounding factors in use of OS-CMR

La résonance magnétique cardiovasculaire sensible à l'oxygénation (OS-CMR) est devenue une modalité d'imagerie diagnostique pour la surveillance de changements dans l'oxygénation du myocarde. Cette technique offre un grand potentiel en tant qu'outil diagnostic primaire pour les maladies cardiovasculaires, en particulier la détection non-invasive d'ischémie. Par contre, il existe plusieurs facteurs potentiellement confondants de cette technique, quelques-uns d'ordre méthodologique comme les paramètres de séquençage et d'autres de nature physiologiques qui sont peut compris. En raison des effets causés par le contenu tissulaire d'eau, l'état d'hydratation peut avoir un impact sur l'intensité du signal. Ceci est un des aspects physiologiques en particulier dont nous voulions quantifier l'effet confondant par la manipulation de l'état d'hydratation chez des humains et l'observation des changements de l'intensité du signal dans des images OS-CMR. Méthodes: In vitro: Du sang artériel et veineux de huit porcs a été utilisé pour évaluer la dilution en série du sang et son effet correspondant sur l'intensité du signal de la séquence OS. In vivo: Vingt-deux volontaires en santé ont subi OS-CMR. Les concentrations d'hémoglobine (Hb) ont été mesurées au niveau de base et immédiatement après une l'infusion cristalloïde rapide de 1000 mL de solution Lactate Ringer's (LRS). Les images OS-CMR ont été prises dans une vue mid-ventriculaire court axe. L'intensité du signal myocardique a été mesurée durant une rétention respiratoire volontaire maximale, suite à une période d'hyperventilation de 60 secondes. Les changements dans l'intensité du signal entre le début et la fin de la rétention de la respiration ont été exprimés relativement au niveau de base (% de changement). Résultats: L'infusion a résulté en une diminution significative de l'Hb mesurée (142.5±3.3 vs. 128.8±3.3 g/L; p<0.001), alors que l'IS a augmenté de 3.2±1.2% entre les images du niveau de base en normo- et hypervolémie (p<0.05). L'IS d'hyperventilation ainsi que les changements d'IS induits par l'apnée ont été attenués après hémodilution (p<0.05). L'évaluation quantitative T2* a démontré une corrélation négative entre le temps de T2* et la concentration d'hémoglobine (r=-0.46, p<0.005). Conclusions: Il existe plusieurs éléments confondants de la technique OS-CMR qui requièrent de l'attention et de l'optimisation pour une future implémentation clinique à grande échelle. Le statut d'hydratation en particulier pourrait être un élément confondant dans l'imagerie OS-CMR. L'hypervolémie mène à une augmentation en IS au niveau de base et atténue la réponse IS durant des manoeuvres de respiration vasoactives. Cette atténuation de l'intensité du signal devrait être tenue en compte et corrigée dans l'évaluation clinique d'images OS-CMR.

High blood pressure and sedentary behavior in adolescents are associated even after controlling for confounding factors

The aim of this study was to determine whether high blood pressure (HBP) is associated with sedentary behavior in young people even after controlling for potential confounders (gender, age, socioeconomic level, tobacco, alcohol, obesity and physical activity). In this epidemiological study, 1231 adolescents were evaluated. Blood pressure was measured with an oscillometric device and waist circumference with an inextensible tape. Sedentary behavior (watching television, computer use and playing video games) and physical activity were assessed by a questionnaire. We used mean and standard deviation to describe the statistical analysis, and the association between HBP and sedentary behavior was assessed by the chi-squared test. Binary logistic regression was used to observe the magnitude of association and cluster analyses (sedentary behavior and abdominal obesity; sedentary behavior and physical inactivity). HBP was associated with sedentary behaviors [odds ratio (OR) = 2.21, 95% confidence interval (CI) = 1.41-3.96], even after controlling for various confounders (OR = 1.68, CI = 1.03-2.75). In cluster analysis the combination of sedentary behavior and elevated abdominal obesity contributed significantly to an increased likelihood of having HBP (OR = 13.51, CI 7.21-23.97). Sedentary behavior was associated with HBP, and excess fat in the abdominal region contributed to the modulation of this association.

A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study

When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.

Multibranched acquired periungual fibrokeratomas with confounding histopathologic findings resembling papillomavirus infection: a report of two cases

Acquired periungual fibrokeratomas are benign fibrous tissue tumors and are considered as the topographical variant of acquired digital fibrokeratoma. They usually present as solitary tumors. In some instance, the entity may appear in multibranched fashion. The main histopathologic features consist of acanthosis, thick collagen bundles mainly oriented in a vertical axis forming a central core, and numerous proliferating fibroblasts. In this article, we present two cases of acquired multibranched periungual fibrokeratoma and depict their varying clinical features over time. Binucleation and perinuclear halos of keratinocytes mimicking human papillomavirus (HPV) infection were detected microscopically, but there was no reactivity with HPV immunostaining. In context, anti-HPV immunostaining may be helpful in the differentiation of fibrokeratomas from HPV infection. On the other hand, it should be kept in mind that these histopathologic findings may be found in acral biopsies independent of viral effects.

The confounding of Camelia /

Mode of access: Internet.

Confounding physiologic parameters in pulse transit time monitoring of children

Pulse Transit Time (PTT) measurement has showed potential in non-invasive monitoring of changes in blood pressure. In children, the common peripheral sites used for these studies are a finger or toe. Presently, there are no known studies conducted to investigate any possible physiologic parameters affecting PTT measurement at these sites for children. In this study, PTT values of both peripheral sites were recorded from 64 children in their sitting posture. Their mean age with standard deviation (SD) was 8.2 2.6years (ranged 3 to 12years). Subjects' peripheries path length, heart rate (HR), systolic (SBP) and diastolic blood pressure (DBP) were measured to investigate any contributions to PTT measurement. The peripheral pulse timing characteristic measured by photoplethysmography (PPG) shows a 59.5 8.5ms (or 24.8 0.4%) difference between the two peripheries (p

Methods for Confounding Adjustment and High-Dimensional Environmental Exposures

Thesis (Ph.D.)--University of Washington, 2016-08