Natalie Stickle

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All published works

Action	Title	Year	Authors
+	Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies	2021	Samantha Brown Jessica A. Lavery Ronglai Shen Axel Martin Kenneth L. Kehl Shawn M. Sweeney Eva M. Lepisto Hira Rizvi Caroline G. McCarthy Nikolaus Schultz
+	Additional file 2: Table S2. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 9: Table S9. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 4: Table S4. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 8: Table S8. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 3: Table S3. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 5: Table S5. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 6: Table S6. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 1: Table S1. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni
+	Additional file 7: Table S7. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine	2016	Nazleen Lobo Craig Gedye Anthony Apostoli Kevin R. Brown Joshua Paterson Natalie Stickle Michael Robinette Neil Fleshner Robert J. Hamilton Girish S. Kulkarni

Common Coauthors

Coauthor	Papers Together
Neil Fleshner	9
Nazleen Lobo	9
Alexandre R. Zlotta	9
Girish S. Kulkarni	9
Craig Gedye	9
Robert J. Hamilton	9
Joshua Paterson	9
Michael A.S. Jewett	9
Kevin R. Brown	9
Michael Robinette	9
Anthony Apostoli	9
Laurie Ailles	9
Jason Moffat	9
Antonio Finelli	9
Andrew Evans	9
Laura MacConnaill	1
Victor E. Velculescu	1
Wanjari Pankhuri	1
Hira Rizvi	1
Zhibin Lu	1
Lucy Lu Wang	1
Cynthia Chu	1
Harm van Tinteren	1
Ahmet Zehir	1
Angela J. Waanders	1
Mariska Bierkens	1
Stuart M. Gardos	1
Julia E. Rudolph	1
Priyanka Shivdasani	1
Julie R. Brahmer	1
Samantha Brown	1
Natasha B. Leighl	1
Neil A. Bailey	1
Christopher D. Gocke	1
Moung Christine	1
Katherine S. Panageas	1
Ari Caroline	1
Dilrini Silva	1
Walter J. Urba	1
E. Alejandro Sweet‐Cordero	1
Nitthusha Singaravelan	1
Benjamin Groß	1
Caroline G. McCarthy	1
Eric Talevich	1
Francesco M. Mancuso	1
Daniel Fabbri	1
Priti Kumari	1
Jean Abraham	1
Helen Chow	1
Ümit Topaloğlu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Modeling Survival Data: Extending the Cox Model	2000	Terry M. Therneau Patricia M. Grambsch	1
+	Nonparametric tests of the Markov model for survival data	1992	Michael P. Jones John Crowley	1
+	A simple test of independence for truncated data with applications to redshift surveys	1992	Bradley Efron V. Petrosian	1
+	Testing Quasi-Independence of Failure and Truncation Times via Conditional Kendall's Tau	2005	Emily C. Martin Rebecca A. Betensky	1
+ PDF Chat	Eliminating bias due to censoring in Kendall’s tau estimators for quasi-independence of truncation and failure	2013	Matthew Austin Rebecca A. Betensky	1
+ PDF Chat	Rank Regression Methods for Left-Truncated and Right-Censored Data	1991	Tze Leung Lai Zhiliang Ying	1
+	Hazards regression analysis for length-biased data	1996	MC Wang	1
+	Testing the assumption of independence of truncation time and failure time	1990	Wei Yann Tsai	1
+ PDF Chat	Survival Analysis Using SAS: A Practical Guide. Second Edition By Paul D. Allison	2011	Nora E. Rosenberg L. Sirkus	1
+ PDF Chat	Threats to Validity of Nonrandomized Studies of Postdiagnosis Exposures on Cancer Recurrence and Survival	2013	Jessica Chubak Denise M. Boudreau Heidi S. Wirtz Barbara McKnight Noel S. Weiss	1
+	Bias Due to Left Truncation and Left Censoring in Longitudinal Studies of Developmental and Disease Processes	2011	Kevin C. Cain Sioḃán D. Harlow Roderick J. A. Little Bin Nan Matheos Yosef John Taffe Michael R. Elliott	1
+ PDF Chat	Survival Analysis Techniques for Censored and Truncated Data	1998	Marepalli B. Rao John P. Klein Melvin L. Moeschberger	1
+ PDF Chat	Accuracy Loss Due to Selection Bias in Cohort Studies with Left Truncation	2013	Enrique F. Schisterman Stephen R. Cole Aijun Ye Robert W. Platt	1
+ PDF Chat	Recognizing the problem of delayed entry in time‐to‐event studies: Better late than never for clinical neuroscientists	2015	Rebecca A. Betensky Micha Mandel	1
+ PDF Chat	A General Framework for Considering Selection Bias in EHR-Based Studies: What Data are Observed and Why?	2016	Sebastien Haneuse Michael J. Daniels	1
+ PDF Chat	Transformation model estimation of survival under dependent truncation and independent censoring	2018	Sy Han Chiou Matthew Austin Jing Qian Rebecca A. Betensky	1
+	Transformation Model Based Estimation of Survival and Regression Under Dependent Truncation and Independent Censoring [R package tranSurv version 1.2.2]	2021	Sy Han Chiou Jing Qian	1