Journal of the American Statistical Association

最新文章

• Coding and compression: A happy union of theory and practice AI翻译
  作者：Rissanen, J; Yu, B
  作者单位：University of California System; University of California Berkeley
• Seismology - A statistical vignette AI翻译
  作者：Vere-Jones, D
  作者单位：Victoria University Wellington
• Likelihood AI翻译
  作者：Reid, N
  作者单位：University of Toronto
• A class of weighted log-rank tests for survival data when the event is rare AI翻译
  作者：Buyske, S; Fagerstrom, R; Ying, ZL
  作者单位：Rutgers University System; Rutgers University New Brunswick; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
  摘要：In many epidemiological and medical follow-up studies, a majority of study subjects do not experience the event of interest during the follow-up period. An important example is the ongoing prostate, lung, colorectal, and ovarian cancer screening trial of the National Cancer Institute. In such a situation, the widely used G(rho) family of weighted log-rank statistics essentially reduces to the special case of the (unweighted) log-rank statistics. We propose a simple modification to the G(rho) f...
• Capture-recapture models AI翻译
  作者：Pollock, KH
  作者单位：North Carolina State University
• Bayesian analysis: A look at today and thoughts of tomorrow AI翻译
  作者：Berger, JO
  作者单位：Duke University
• The end of time series AI翻译
  作者：Solo, V
  作者单位：University of New South Wales Sydney
• Statistics in preclinical pharmaceutical research and development AI翻译
  作者：Gunter, B; Holder, D
  作者单位：Merck & Company; Merck & Company
• Estimation of the causal effect of a time-varying exposure on the marginal mean of a repeated binary outcome - Comment AI翻译
  作者：Rubin, DB; Frangakis, CE
  作者单位：Harvard University; Johns Hopkins University
• Prediction intervals, factor analysis models, and high-dimensional empirical linear prediction AI翻译
  作者：Ding, AA; Hwang, JTG
  作者单位：Northeastern University; Cornell University
  摘要：We discuss a technique that provides prediction intervals based on a model called an empirical linear model. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. In fact, a special case of the empirical model is the factor analysis model. A factor analysis model does not generally aim at prediction, however. Therefore, HELP can be viewed as a technique that provides prediction (and confidence) intervals ...