R
Robert Tibshirani
Researcher at Stanford University
Publications - 620
Citations - 359457
Robert Tibshirani is an academic researcher from Stanford University. The author has contributed to research in topics: Lasso (statistics) & Gene expression profiling. The author has an hindex of 147, co-authored 593 publications receiving 326580 citations. Previous affiliations of Robert Tibshirani include University of Toronto & University of California.
Papers
More filters
Journal ArticleDOI
Implications of Measurement Error in Exposure for the Sample Sizes of Case-Control Studies
TL;DR: Models of the relation between true exposure and a surrogate exposure measure assessed with error are used to derive equations for sample size determination and show that the sample size of a study based on an exposure variable which is measured with error must be larger than if exposure were measured without error.
Journal ArticleDOI
Post-infusion CAR TReg cells identify patients resistant to CD19-CAR therapy
Zina Good,Jay Y. Spiegel,Bita Sahaf,Meena Malipatlolla,Zach Ehlinger,Sreevidya Kurra,Moksha Desai,Warren D. Reynolds,Anita Wong Lin,Panayiotis Vandris,Fang Wu,Snehit Prabhu,Mark P. Hamilton,John S. Tamaresis,Paul Hanson,Shabnum Patel,Steven R. Feldman,Matthew J. Frank,John H. Baird,Lori Muffly,Gursharan K. Claire,Juliana Craig,Katherine A. Kong,Dhananjay A. Wagh,John A. Coller,Sean C. Bendall,Robert Tibshirani,Sylvia K. Plevritis,David B. Miklos,Crystal L. Mackall +29 more
TL;DR: In this paper , a single-cell proteomic profiling of circulating CAR T cells in 32 patients treated with CD19-CAR identified that CD4+Helios+ CART cells on day 7 after infusion are associated with progressive disease and less severe neurotoxicity.
Posted Content
LassoNet: A Neural Network with Feature Sparsity
TL;DR: This work introduces LassoNet, a neural network framework with global feature selection that uses a modified objective function with constraints, and so integrates feature selection with the parameter learning directly, and delivers an entire regularization path of solutions with a range of feature sparsity.
Journal ArticleDOI
DR-Integrator
TL;DR: DNA/RNA-Integrator is introduced, a statistical software tool to perform integrative analyses on paired DNA copy number and gene expression data and implements a supervised analysis that captures genes with significant alterations in both DNAcopy number and Gene expression between two sample classes.
Journal ArticleDOI
Flexible covariate effects in the proportional hazards model.
TL;DR: A class of semiparametric models is outlined that allows one to model prognostic factors nonlinearly, and have the data suggest the form of their effect.