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Connection

Debashis Ghosh to Data Interpretation, Statistical

This is a "connection" page, showing publications Debashis Ghosh has written about Data Interpretation, Statistical.

 
Connection Strength
 
 
 
4.801
 
  1. Ghosh D. Relaxed covariate overlap and margin-based causal effect estimation. Stat Med. 2018 12 10; 37(28):4252-4265.
    View in: PubMed
    Score: 0.534
  2. Daniels M, Frangakis C, Charu V, Ghosh D. University of Pennsylvania 7th annual conference on statistical issues in clinical trials: Current issues regarding the use of biomarkers and surrogate endpoints in clinical trials (morning panel discussion). Clin Trials. 2015 Aug; 12(4):323-32.
    View in: PubMed
    Score: 0.427
  3. Ghosh D. Genomic outlier detection in high-throughput data analysis. Methods Mol Biol. 2013; 972:141-53.
    View in: PubMed
    Score: 0.361
  4. Ghosh D. Incorporating the empirical null hypothesis into the Benjamini-Hochberg procedure. Stat Appl Genet Mol Biol. 2012 Jul 26; 11(4).
    View in: PubMed
    Score: 0.350
  5. Ghosh D. Semiparametric analysis of recurrent events: artificial censoring, truncation, pairwise estimation and inference. Lifetime Data Anal. 2010 Oct; 16(4):509-24.
    View in: PubMed
    Score: 0.294
  6. Ghosh D. On assessing surrogacy in a single trial setting using a semicompeting risks paradigm. Biometrics. 2009 Jun; 65(2):521-9.
    View in: PubMed
    Score: 0.282
  7. Ghosh D, Poisson LM. "Omics" data and levels of evidence for biomarker discovery. Genomics. 2009 Jan; 93(1):13-6.
    View in: PubMed
    Score: 0.268
  8. Liu D, Lin X, Ghosh D. Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models. Biometrics. 2007 Dec; 63(4):1079-88.
    View in: PubMed
    Score: 0.254
  9. Ghosh D. Semiparametric inference for surrogate endpoints with bivariate censored data. Biometrics. 2008 Mar; 64(1):149-56.
    View in: PubMed
    Score: 0.248
  10. Ghosh D, Chinnaiyan AM. Empirical Bayes identification [correction of identication] of tumor progression genes from microarray data. Biom J. 2007 Feb; 49(1):68-77.
    View in: PubMed
    Score: 0.240
  11. Ghosh D. Modelling tumour biology-progression relationships in screening trials. Stat Med. 2006 Jun 15; 25(11):1872-84.
    View in: PubMed
    Score: 0.229
  12. Ghosh D. Resampling methods for variance estimation of singular value decomposition analyses from microarray experiments. Funct Integr Genomics. 2002 Aug; 2(3):92-7.
    View in: PubMed
    Score: 0.170
  13. Ghosh T, Zhang W, Ghosh D, Kechris K. Predictive Modeling for Metabolomics Data. Methods Mol Biol. 2020; 2104:313-336.
    View in: PubMed
    Score: 0.147
  14. Cho Y, Hu C, Ghosh D. Covariate adjustment using propensity scores for dependent censoring problems in the accelerated failure time model. Stat Med. 2018 02 10; 37(3):390-404.
    View in: PubMed
    Score: 0.126
  15. Hua WY, Ghosh D. Equivalence of kernel machine regression and kernel distance covariance for multidimensional phenotype association studies. Biometrics. 2015 Sep; 71(3):812-20.
    View in: PubMed
    Score: 0.106
  16. Cho Y, Ghosh D. Weighted estimation of the accelerated failure time model in the presence of dependent censoring. PLoS One. 2015; 10(4):e0124381.
    View in: PubMed
    Score: 0.106
  17. Ghosh D, Zhu Y, Coffman DL. Penalized regression procedures for variable selection in the potential outcomes framework. Stat Med. 2015 May 10; 34(10):1645-58.
    View in: PubMed
    Score: 0.104
  18. Hua WY, Nichols TE, Ghosh D. Multiple comparison procedures for neuroimaging genomewide association studies. Biostatistics. 2015 Jan; 16(1):17-30.
    View in: PubMed
    Score: 0.100
  19. Ghosh D. Discrete nonparametric algorithms for outlier detection with genomic data. J Biopharm Stat. 2010 Mar; 20(2):193-208.
    View in: PubMed
    Score: 0.074
  20. Yuan Z, Ghosh D. Combining multiple biomarker models in logistic regression. Biometrics. 2008 Jun; 64(2):431-9.
    View in: PubMed
    Score: 0.065
  21. Ghosh D. On the Plackett distribution with bivariate censored data. Int J Biostat. 2008; 4(1):Article 7.
    View in: PubMed
    Score: 0.064
  22. Choi H, Shen R, Chinnaiyan AM, Ghosh D. A latent variable approach for meta-analysis of gene expression data from multiple microarray experiments. BMC Bioinformatics. 2007 Sep 27; 8:364.
    View in: PubMed
    Score: 0.063
  23. Ghosh D. Proportional hazards regression for cancer studies. Biometrics. 2008 Mar; 64(1):141-8.
    View in: PubMed
    Score: 0.061
  24. Ghosh D. Shrunken p-values for assessing differential expression with applications to genomic data analysis. Biometrics. 2006 Dec; 62(4):1099-106.
    View in: PubMed
    Score: 0.059
  25. Tseng GC, Ghosh D, Feingold E. Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Res. 2012 May; 40(9):3785-99.
    View in: PubMed
    Score: 0.021
  26. Begum F, Ghosh D, Tseng GC, Feingold E. Comprehensive literature review and statistical considerations for GWAS meta-analysis. Nucleic Acids Res. 2012 May; 40(9):3777-84.
    View in: PubMed
    Score: 0.021
  27. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R, Yu J, Briggs BB, Barrette TR, Anstet MJ, Kincead-Beal C, Kulkarni P, Varambally S, Ghosh D, Chinnaiyan AM. Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia. 2007 Feb; 9(2):166-80.
    View in: PubMed
    Score: 0.015
  28. Shedden K, Chen W, Kuick R, Ghosh D, Macdonald J, Cho KR, Giordano TJ, Gruber SB, Fearon ER, Taylor JM, Hanash S. Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data. BMC Bioinformatics. 2005 Feb 10; 6:26.
    View in: PubMed
    Score: 0.013
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.

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