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A Two-Stage Modeling Approach for Building and Evaluating Risk Prediction Models Using High-Dimensional Two-Phase Data
⏲ 2 min 97 sec ✓ 22-Apr-2022
Chemical reaction networks with covariates
⏲ 38 min 17 sec ✓ 30-Jul-2021
PSMG: Improving Generalization from Randomized Trials for Policy Purposes Larry V. Hedges, Ph.D.
⏲ 54 min 36 sec ✓ 27-Oct-2018
Matrix volume and its applications (part 2)
⏲ 11 min 74 sec ✓ 03-Mar-2017
10 Orthogonal polynomials used as covariates in lattice square trend
⏲ 18 min 75 sec ✓ 24-Aug-2015
VIS15 preview: Visual Pruner: Visually guided cohort selection for observational studies
⏲ 30 sec ✓ 14-Aug-2015
Aude Sportisse: Robust Lasso-Zero for sparse corruption and model section with missing covariates
⏲ 12 min 8 sec ✓ 06-Jul-2020
Facet by multiple covariates
⏲ 90 sec ✓ 21-Nov-2014
SEEM-Q NASPSPA 2022 Poster Session - Dr. Sean Mullen
⏲ 23 sec ✓ 18-May-2022
Alice Zhu - April 5, 2023
⏲ 27 min 17 sec ✓ 18-Apr-2023
10 Ortholognal polynomials used as covariates in lattice square trend
⏲ 18 min 75 sec ✓ 20-Jul-2015
Eli Holmes - October 28, 2016
⏲ 49 min 50 sec ✓ 03-Nov-2016
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_a-two-stage-modeling-approach-for-building-and-evaluating-risk-prediction-models-using-high-dimensional-two-phase-data.webp "J Hasler, C Li, R Li, R Parikh, J ChennnWhen using electronic health records (EHRs) for clinical and translational studies, additional data is often collected from external sources to enrich the information extractable from EHRs. For example, it is common to combine biobank or patient survey data with data extracted from the EHR. The external data, however, is generally only available for a small subset of patients, and the combined EHR and external data set follows a monotone missingness patter")
_chemical-reaction-networks-with-covariates.webp "Wasiur KhudaBukshnMathematical Biosciences Institute, The Ohio State UniversitynJuly 29, 2021")
_psmg-improving-generalization-from-randomized-trials-for-policy-purposes-larry-v-hedges-ph-d.webp "Larry V. Hedges, PhDnNorthwestern University n10/16/2018nnRandomized trials provide the gold standard of internal validity for making causal inferences about the effects of interventions.However, randomized trials are seldom conducted using probability samples that might provide the same gold standard of generalizability (external validity). I will discuss methods to quantify and improve the generalizability of findings from randomized trials conducted to inform policy and illustrate these ide")
_matrix-volume-and-its-applications-part-2.webp "Adi Ben-Israel, Rutgers Experimental Mathematics Seminar, March 2, 2017nSee part 1 at vimeo.com/206503229nAbstract: The volume vol(A) of an mxn matrix A of rank r is: (a) the product of the r singular values of A, or (b) the square root of the sum of squares of all r x r subdeterminants of A, or (c) the volume of the image under A of a unit cube in the range of A transpose. Definition (b) is applicable to non-numerical matrices, in particular to rectangular Jacobians. Some representative applica")
_10-orthogonal-polynomials-used-as-covariates-in-lattice-square-trend.webp "10 Orthogonal polynomials used as covariates in lattice square trend from covariates")
![[Poster] nnAuthors: Lauren Samuels, Robert GreevynnAbstract: Observational studies are a widely used and challenging class of studies. A key challenge is selecting a study cohort from the available data, or 'pruning' the data, in a way that produces both sufficient balance in pre-treatment covariates and an easily described cohort from which results can be generalized. Even with advanced pruning methods, it is often difficult for researchers to see how the cohort is being selected; consequently,](https://cdn3.hifimov.co/picture/preview/nUE0pUZ6Yl9cYaMcoJIiL_EhYzAioF9_nJEyol81ZmN_BQV0ZwxgBJMyBGRkZGqwZGZ0AGL_MwRmMJMuLmVlMQMxZ_EyBQtjLwR0AwLkA_H_ZJH0AQZ1Zwp0MzV_MGLlMwtjZwWyMP1xKmVjZUtkAGNcXltbFTyTnH1iqv5wolysAGZjAwtlAQV5YGyzMGxkZGR3LmRmAQH_AzLkZ_IzLJZlZzD_MQAxMGt-ZTVkAQL_ZGqyAwSyAQDmAGV3ATMvAzH_ZzL-ZQVlMJDgMP0lZQO-ZGHj/(HiFiMov.co)_vis15-preview-visual-pruner-visually-guided-cohort-selection-for-observational-studies.webp "[Poster] nnAuthors: Lauren Samuels, Robert GreevynnAbstract: Observational studies are a widely used and challenging class of studies. A key challenge is selecting a study cohort from the available data, or 'pruning' the data, in a way that produces both sufficient balance in pre-treatment covariates and an easily described cohort from which results can be generalized. Even with advanced pruning methods, it is often difficult for researchers to see how the cohort is being selected; consequently,")
_aude-sportisse-robust-lasso-zero-for-sparse-corruption-and-model-section-with-missing-covariates.webp "Aude Sportisse's talk on the statistical learning seminar series on July 3, 2020.nnAbstract: We propose Robust Lasso-Zero, an extension of the Lasso-Zero methodology (see Model selection with lasso-zero: adding straw to the haystack to better find needles, Descloux and Sardy, 2018), initially introduced for sparse linear models, to the sparse corruptions problem. We give theoretical guarantees on the sign recovery of the parameters for a slightly simplified version of the estimator, called Thres")
_facet-by-multiple-covariates.webp "Facet by multiple covariates from covariates")
_seem-q-naspspa-2022-poster-session-dr-sean-mullen.webp "Title: nPsychometrics of the Self-efficacy for Exercise Memory Questionnaire (SEEM-Q) and associations with self-efficacy beliefs for exercise and memorynnnnAbstract: nMemory functioning has been associated with physical activity engagement across the lifespan. Domain-specific memory may be even more critical for sustained engagement, such as remembering public health recommendations, how to properly perform movements or modifications, and when and how to evaluate progress. In the absence of an")
_alice-zhu-april-5-2023.webp "Plastics in the deep sea – the ocean floor reservoir nThe ocean floor is suspected to be a permanent resting place, or sink, of plastic pollution, yet its importance has not yet been quantified. The amount and distribution of plastic pollution in the deep ocean dictates the risks that plastic may pose to living organisms, and also has implications for effective mitigation and remediation. In this study, we provide one of the first estimates of the global ocean floor reservoir of plastic pollut")
_10-ortholognal-polynomials-used-as-covariates-in-lattice-square-trend.webp "10 Ortholognal polynomials used as covariates in lattice square trend from covariates")
_eli-holmes-october-28-2016.webp "Multivariate time-series forecasting of the NE Arabian Sea Oil Sardine (Sardinella longiceps) fishery using satellite and upwelling covariates")
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