Runze Li

Summary

Affiliation: Pennsylvania State University
Country: USA

Publications

  1. pmc Variable Selection in Semiparametric Regression Modeling
    Runze Li
    Department of Statistics, Pennsylvania State University, University Park, PA16802 2111
    Ann Stat 36:261-286. 2008
  2. pmc Local Linear Regression for Data with AR Errors
    Runze Li
    Department of Statistics and The Methodology Center, Pennsylvania State University, University Park, PA 16802 2111, USA
    Acta Math Appl Sin 25:427-444. 2009
  3. pmc Efficient statistical inference procedures for partially nonlinear models and their applications
    Runze Li
    Department of Statistics and The Methodology Center, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biometrics 64:904-11. 2008
  4. pmc A dynamic model for functional mapping of biological rhythms
    Guifang Fu
    Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA
    J Biol Dyn 5:84-101. 2011
  5. pmc The Bayesian lasso for genome-wide association studies
    Jiahan Li
    Department of Statistics, Pennsylvania State University, State College, PA 16802, USA
    Bioinformatics 27:516-23. 2011
  6. pmc Quadratic inference functions for varying-coefficient models with longitudinal data
    Annie Qu
    Department of Statistics, Oregon State University, Corvallis, Oregon 97331, USA
    Biometrics 62:379-91. 2006
  7. pmc How to cluster gene expression dynamics in response to environmental signals
    Yaqun Wang
    Department of Statistics, Pennsylvania State University, Hershey, PA 17033, USA
    Brief Bioinform 13:162-74. 2012
  8. pmc Time-varying processes involved in smoking lapse in a randomized trial of smoking cessation therapies
    Sara A Vasilenko
    Methodology Center, Pennsylvania State University, University Park, PA
    Nicotine Tob Res 16:S135-43. 2014
  9. pmc Developmental changes in anger expression and attention focus: learning to wait
    Pamela M Cole
    Department of Psychology, The Pennsylvania State University, University Park, PA 16802, USA
    Dev Psychol 47:1078-89. 2011
  10. pmc Design of experiments with multiple independent variables: a resource management perspective on complete and reduced factorial designs
    Linda M Collins
    The Methodology Center, Department of Human Development and Family Studies, Pennsylvania State University, PA 16801, USA
    Psychol Methods 14:202-24. 2009

Collaborators

Detail Information

Publications18

  1. pmc Variable Selection in Semiparametric Regression Modeling
    Runze Li
    Department of Statistics, Pennsylvania State University, University Park, PA16802 2111
    Ann Stat 36:261-286. 2008
    ..Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedures...
  2. pmc Local Linear Regression for Data with AR Errors
    Runze Li
    Department of Statistics and The Methodology Center, Pennsylvania State University, University Park, PA 16802 2111, USA
    Acta Math Appl Sin 25:427-444. 2009
    ..We illustrate the proposed methodology by an analysis of real data set...
  3. pmc Efficient statistical inference procedures for partially nonlinear models and their applications
    Runze Li
    Department of Statistics and The Methodology Center, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biometrics 64:904-11. 2008
    ..Finite sample performance of the proposed inference procedures are assessed by Monte Carlo simulation studies. An application in ecology is used to illustrate the proposed methods...
  4. pmc A dynamic model for functional mapping of biological rhythms
    Guifang Fu
    Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA
    J Biol Dyn 5:84-101. 2011
    ..The new model will find its implications for understanding the interplay between gene interactions and developmental pathways in complex biological rhythms...
  5. pmc The Bayesian lasso for genome-wide association studies
    Jiahan Li
    Department of Statistics, Pennsylvania State University, State College, PA 16802, USA
    Bioinformatics 27:516-23. 2011
    ..A simultaneous analysis of a large number of SNPs, although statistically challenging, especially with a small number of samples, is crucial for genetic modeling...
  6. pmc Quadratic inference functions for varying-coefficient models with longitudinal data
    Annie Qu
    Department of Statistics, Oregon State University, Corvallis, Oregon 97331, USA
    Biometrics 62:379-91. 2006
    ..We evaluate the finite sample performance of the proposed procedures with Monte Carlo simulation studies. The proposed methodology is illustrated by the analysis of an acquired immune deficiency syndrome (AIDS) data set...
  7. pmc How to cluster gene expression dynamics in response to environmental signals
    Yaqun Wang
    Department of Statistics, Pennsylvania State University, Hershey, PA 17033, USA
    Brief Bioinform 13:162-74. 2012
    ..We provide a set of computational tools that are applicable to modeling and analysis of dynamic gene expression data measured in multiple environments...
  8. pmc Time-varying processes involved in smoking lapse in a randomized trial of smoking cessation therapies
    Sara A Vasilenko
    Methodology Center, Pennsylvania State University, University Park, PA
    Nicotine Tob Res 16:S135-43. 2014
    ..In this paper, we use a new technique, the logistic time-varying effect model (logistic TVEM), to examine the odds of smoking in the 2 weeks after a quit attempt...
  9. pmc Developmental changes in anger expression and attention focus: learning to wait
    Pamela M Cole
    Department of Psychology, The Pennsylvania State University, University Park, PA 16802, USA
    Dev Psychol 47:1078-89. 2011
    ....
  10. pmc Design of experiments with multiple independent variables: a resource management perspective on complete and reduced factorial designs
    Linda M Collins
    The Methodology Center, Department of Human Development and Family Studies, Pennsylvania State University, PA 16801, USA
    Psychol Methods 14:202-24. 2009
    ..Although relatively unfamiliar to behavioral scientists, fractional factorial designs merit serious consideration because of their economy and versatility...
  11. pmc A dynamic model for genome-wide association studies
    Kiranmoy Das
    Department of Statistics, The Pennsylvania State University, University Park, PA, USA
    Hum Genet 129:629-39. 2011
    ..In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data...
  12. pmc Advancing the understanding of craving during smoking cessation attempts: a demonstration of the time-varying effect model
    Stephanie T Lanza
    Methodology Center, Pennsylvania State University, University Park, PA
    Nicotine Tob Res 16:S127-34. 2014
    ..Coefficients are expressed dynamically over time and are represented as smooth functions of time...
  13. pmc A time-varying effect model for intensive longitudinal data
    Xianming Tan
    The Methodology Center, The Pennsylvania State University, 204 East Calder Way, Suite 400, State College, PA 16801, USA
    Psychol Methods 17:61-77. 2012
    ....
  14. pmc Understanding the role of cessation fatigue in the smoking cessation process
    Xiaoyu Liu
    The Methodology Center, The Pennsylvania State University, United States Department of Statistics, The Pennsylvania State University, United States Electronic address
    Drug Alcohol Depend 133:548-55. 2013
    ..e., the tiredness of trying to quit smoking) with respect to its average trend, effect on relapse, time-varying relations with craving and negative affect, and differences among genders and treatment groups...
  15. pmc Model and algorithm for linkage disequilibrium analysis in a non-equilibrium population
    Jingyuan Liu
    Department of Statistics, The Pennsylvania State University State College, PA, USA
    Front Genet 3:78. 2012
    ..An MCMC method was implemented to estimate genetic parameters that define these associations. Simulation studies were used to validate the statistical behavior of the new model...
  16. pmc A Bayesian Framework for Functional Mapping through Joint Modeling of Longitudinal and Time-to-Event Data
    Kiranmoy Das
    Department of Statistics, Temple University, Philadelphia, PA 19122, USA
    Int J Plant Genomics 2012:680634. 2012
    ..Results show that this model should be broadly useful for detecting genes controlling physiological and pathological processes and other events of interest in biomedicine...
  17. pmc A statistical model for mapping morphological shape
    Guifang Fu
    Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA
    Theor Biol Med Model 7:28. 2010
    ..Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine...
  18. pmc How spacing of data collection may impact estimates of substance use trajectories
    Xianming Tan
    The Methodology Center, The Pennsylvania State University, State College, Pennsylvania, USA
    Subst Use Misuse 46:758-68. 2011
    ..However, there were notable differences in individual trajectory assignments on the basis of contiguous and snapshot measurements...