Molecular Bias

[1]  J. Ioannidis.  Commentary: grading the credibility of molecular evidence for complex diseases. , 2006, International journal of epidemiology.

[2]  J. Ioannidis.  Differentiating Biases from Genuine Heterogeneity: Distinguishing Artifactual from Substantive Effects , 2006 .

[3]  Paolo Vineis,et al.  A network of investigator networks in human genome epidemiology. , 2005, American journal of epidemiology.

[4]  J. Ioannidis.  Why Most Published Research Findings Are False , 2005, PLoS medicine.

[5]  John P A Ioannidis,et al.  Selective reporting biases in cancer prognostic factor studies. , 2005, Journal of the National Cancer Institute.

[6]  J. Ioannidis.  Contradicted and initially stronger effects in highly cited clinical research. , 2005, JAMA.

[7]  Thomas A Trikalinos,et al.  Early extreme contradictory estimates may appear in published research: the Proteus phenomenon in molecular genetics research and randomized trials. , 2005, Journal of clinical epidemiology.

[8]  R. Horton,et al.  Is this clinical trial fully registered? A statement from the International Committee of Medical Journal Editors , 2005, The Lancet.

[9]  Richard Smith,et al.  Medical Journals Are an Extension of the Marketing Arm of Pharmaceutical Companies , 2005, PLoS medicine.

[10]  D. Ransohoff.  Lessons from controversy: ovarian cancer screening and serum proteomics. , 2005, Journal of the National Cancer Institute.

[11]  J. Ioannidis.  Microarrays and molecular research: noise discovery? , 2005, The Lancet.

[12]  Stefan Michiels,et al.  Prediction of cancer outcome with microarrays: a multiple random validation strategy , 2005, The Lancet.

[13]  D. Ransohoff.  Bias as a threat to the validity of cancer molecular-marker research , 2005, Nature reviews. Cancer.

[14]  Rachel Churchill,et al.  Effect sizes in cumulative meta-analyses of mental health randomized trials evolved over time. , 2004, Journal of clinical epidemiology.

[15]  J. Ioannidis,et al.  Establishment of genetic associations for complex diseases is independent of early study findings , 2004, European Journal of Human Genetics.

[16]  Timothy R. Rebbeck,et al.  Assessing the function of genetic variants in candidate gene association studies , 2004, Nature Reviews Genetics.

[17]  D. Lawlor,et al.  Those confounded vitamins: what can we learn from the differences between observational versus randomised trial evidence? , 2004, The Lancet.

[18]  D. Ransohoff.  Rules of evidence for cancer molecular-marker discovery and validation , 2004, Nature Reviews Cancer.

[19]  Nathaniel Rothman,et al.  Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. , 2004, Journal of the National Cancer Institute.

[20]  J. Ioannidis.  Materializing research promises: opportunities, priorities and conflicts in translational medicine , 2004, Journal of Translational Medicine.

[21]  J. Ioannidis,et al.  Predictive ability of DNA microarrays for cancer outcomes and correlates: an empirical assessment , 2003, The Lancet.

[22]  John P A Ioannidis,et al.  Translation of highly promising basic science research into clinical applications. , 2003, The American journal of medicine.

[23]  John P A Ioannidis,et al.  Genetic associations: false or true? , 2003, Trends in molecular medicine.

[24]  Thomas A Trikalinos,et al.  Genetic associations in large versus small studies: an empirical assessment , 2003, The Lancet.

[25]  John P A Ioannidis,et al.  Commentary: meta-analysis of individual participants' data in genetic epidemiology. , 2002, American journal of epidemiology.

[26]  Charles Kooperberg,et al.  Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial. , 2002, JAMA.

[27]  J. Ioannidis,et al.  Replication validity of genetic association studies , 2001, Nature Genetics.

[28]  J. Ioannidis,et al.  Evolution of treatment effects over time: empirical insight from recursive cumulative metaanalyses. , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[29]  M. Khoury,et al.  Human genome epidemiologic reviews: the beginning of something HuGE. , 2000, American journal of epidemiology.

[30]  J. Ioannidis,et al.  Recursive cumulative meta-analysis: a diagnostic for the evolution of total randomized evidence from group and individual patient data. , 1999, Journal of clinical epidemiology.

[31]  Christopher H Schmid,et al.  Summing up evidence: one answer is not always enough , 1998, The Lancet.

[32]  J. Ioannidis,et al.  Quantitative Synthesis in Systematic Reviews , 1997, Annals of Internal Medicine.

[33]  G. Smith,et al.  Bias in meta-analysis detected by a simple, graphical test , 1997, BMJ.

[34]  I Olkin,et al.  Meta-analysis: reconciling the results of independent studies. , 1995, Statistics in Medicine.

[35]  D. Sackett.  Bias in analytic research. , 1979, Journal of chronic diseases.