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- Universal kriging (2)
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- Biomarker; logistic regression; receiver operating characteristic curve; risk factors; risk reclassification (1)
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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
A Regionalized National Universal Kriging Model Using Partial Least Squares Regression For Estimating Annual Pm2.5 Concentrations In Epidemiology, Paul D. Sampson, Mark Richards, Adam A. Szpiro, Silas Bergen, Lianne Sheppard, Timothy V. Larson, Joel Kaufman
A Regionalized National Universal Kriging Model Using Partial Least Squares Regression For Estimating Annual Pm2.5 Concentrations In Epidemiology, Paul D. Sampson, Mark Richards, Adam A. Szpiro, Silas Bergen, Lianne Sheppard, Timothy V. Larson, Joel Kaufman
UW Biostatistics Working Paper Series
Many cohort studies in environmental epidemiology require accurate modeling and prediction of fine scale spatial variation in ambient air quality across the U.S. This modeling requires the use of small spatial scale geographic or “land use” regression covariates and some degree of spatial smoothing. Furthermore, the details of the prediction of air quality by land use regression and the spatial variation in ambient air quality not explained by this regression should be allowed to vary across the continent due to the large scale heterogeneity in topography, climate, and sources of air pollution. This paper introduces a regionalized national universal kriging …
A National Model Built With Partial Least Squares And Universal Kriging And Bootstrap-Based Measurement Error Correction Techniques: An Application To The Multi-Ethnic Study Of Atherosclerosis, Silas Bergen, Lianne Sheppard, Paul D. Sampson, Sun-Young Kim, Mark Richards, Sverre Vedal, Joel Kaufman, Adam A. Szpiro
A National Model Built With Partial Least Squares And Universal Kriging And Bootstrap-Based Measurement Error Correction Techniques: An Application To The Multi-Ethnic Study Of Atherosclerosis, Silas Bergen, Lianne Sheppard, Paul D. Sampson, Sun-Young Kim, Mark Richards, Sverre Vedal, Joel Kaufman, Adam A. Szpiro
UW Biostatistics Working Paper Series
Studies estimating health effects of long-term air pollution exposure often use a two-stage approach, building exposure models to assign individual-level exposures which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of carefully accounting for exposure model characteristics in two-stage air pollution studies, we consider a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We present national spatial exposure models that use partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), …
Decline In Health For Older Adults: 5-Year Change In 13 Key Measures Of Standardized Health, Paula H. Diehr, Stephen M. Thielke, Anne B. Newman, Calvin H. Hirsch, Russell Tracy
Decline In Health For Older Adults: 5-Year Change In 13 Key Measures Of Standardized Health, Paula H. Diehr, Stephen M. Thielke, Anne B. Newman, Calvin H. Hirsch, Russell Tracy
UW Biostatistics Working Paper Series
Introduction
The health of older adults declines over time, but there are many ways of measuring health. We examined whether all measures declined at the same rate, or whether some aspects of health were less sensitive to aging than others.
Methods
We compared the decline in 13 measures of physical, mental, and functional health from the Cardiovascular Health Study: hospitalization, bed days, cognition, extremity strength, feelings about life as a whole, satisfaction with the purpose of life, self-rated health, depression, digit symbol substitution test, grip strength, ADLs, IADLs, and gait speed. Each measure was standardized against self-rated health. We compared …
Methods For Evaluating Prediction Performance Of Biomarkers And Tests, Margaret Pepe, Holly Janes
Methods For Evaluating Prediction Performance Of Biomarkers And Tests, Margaret Pepe, Holly Janes
UW Biostatistics Working Paper Series
This chapter describes and critiques methods for evaluating the performance of markers to predict risk of a current or future clinical outcome. We consider three criteria that are important for evaluating a risk model: calibration, benefit for decision making and accurate classification. We also describe and discuss a variety of summary measures in common use for quantifying predictive information such as the area under the ROC curve and R-squared. The roles and problems with recently proposed risk reclassification approaches are discussed in detail.
Borrowing Information Across Populations In Estimating Positive And Negative Predictive Values, Ying Huang, Youyi Fong, John Wei, Ziding Feng
Borrowing Information Across Populations In Estimating Positive And Negative Predictive Values, Ying Huang, Youyi Fong, John Wei, Ziding Feng
UW Biostatistics Working Paper Series
A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population …
Fitting And Interpreting Continuous-Time Latent Markov Models For Panel Data, Jane M. Lange, Vladimir N. Minin
Fitting And Interpreting Continuous-Time Latent Markov Models For Panel Data, Jane M. Lange, Vladimir N. Minin
UW Biostatistics Working Paper Series
Multistate models are used to characterize disease processes within an individual. Clinical studies often observe the disease status of individuals at discrete time points, making exact times of transitions between disease states unknown. Such panel data pose considerable modeling challenges. Assuming the disease process progresses according a standard continuous-time Markov chain (CTMC) yields tractable likelihoods, but the assumption of exponential sojourn time distributions is typically unrealistic. More flexible semi-Markov models permit generic sojourn distributions yet yield intractable likelihoods for panel data in the presence of reversible transitions. One attractive alternative is to assume that the disease process is characterized by …
Transitions Among Health States Using 12 Measures Of Successful Aging: Results From The Cardiovascular Health Study, Stephen Thielke, Paula Diehr
Transitions Among Health States Using 12 Measures Of Successful Aging: Results From The Cardiovascular Health Study, Stephen Thielke, Paula Diehr
UW Biostatistics Working Paper Series
Introduction
Successful aging has many dimensions, which may manifest differently in men and women and at different ages. We sought to characterize one-year transitions in 12 measures of successful aging among a large cohort of older adults.
Methods
We analyzed twelve different measures of health in the Cardiovascular Health Study: self-rated health, ADLs, IADLs, depression, cognition, timed walk, number of days spent in bed, number of blocks walked, extremity strength, recent hospitalizations, feelings about life as a whole, and life satisfaction. We dichotomized responses for each variable into “healthy” or “sick”, and estimated the prevalence of the healthy state and …
Testing For Improvement In Prediction Model Performance, Margaret S. Pepe Phd, Kathleen F. Kerr, Gary M. Longton, Zheyu Wang
Testing For Improvement In Prediction Model Performance, Margaret S. Pepe Phd, Kathleen F. Kerr, Gary M. Longton, Zheyu Wang
UW Biostatistics Working Paper Series
New methodology has been proposed in recent years for evaluating the improvement in prediction performance gained by adding a new predictor, Y, to a risk model containing a set of baseline predictors, X, for a binary outcome D. We prove theoretically that null hypotheses concerning no improvement in performance are equivalent to the simple null hypothesis that the coefficient for Y is zero in the risk model, P(D = 1|X, Y ). Therefore, testing for improvement in prediction performance is redundant if Y has already been shown to be a risk factor. We investigate properties of tests through simulation studies, …