J Ludbrook

Summary

Country: Australia

Publications

  1. ncbi Multiple comparison procedures updated
    J Ludbrook
    University of Melbourne Department of Surgery, Royal Melbourne Hospital, Parkville, Victoria, Australia
    Clin Exp Pharmacol Physiol 25:1032-7. 1998
  2. ncbi Multiple inferences using confidence intervals
    J Ludbrook
    Carlton North, Victoria, Australia
    Clin Exp Pharmacol Physiol 27:212-5. 2000
  3. ncbi Statistics in physiology and pharmacology: a slow and erratic learning curve
    J Ludbrook
    Carlton North, Victoria, Australia
    Clin Exp Pharmacol Physiol 28:488-92. 2001
  4. ncbi Statistical techniques for comparing measurers and methods of measurement: a critical review
    John Ludbrook
    The University of Melbourne, Parkville, Victoria, Australia
    Clin Exp Pharmacol Physiol 29:527-36. 2002
  5. ncbi Interim analyses of data as they accumulate in laboratory experimentation
    John Ludbrook
    Department of Surgery, The University of Melbourne, Parkville, Victoria, Australia
    BMC Med Res Methodol 3:15. 2003
  6. ncbi Statistics in biomedical laboratory and clinical science: applications, issues and pitfalls
    John Ludbrook
    Department of Surgery, The University of Melbourne, Melbourne, Australia
    Med Princ Pract 17:1-13. 2008
  7. ncbi Outlying observations and missing values: how should they be handled?
    John Ludbrook
    Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia
    Clin Exp Pharmacol Physiol 35:670-8. 2008

Detail Information

Publications7

  1. ncbi Multiple comparison procedures updated
    J Ludbrook
    University of Melbourne Department of Surgery, Royal Melbourne Hospital, Parkville, Victoria, Australia
    Clin Exp Pharmacol Physiol 25:1032-7. 1998
    ..5. Despite the corrective abilities of the new step-wise MCP, investigators should try to design their experiments and analyses to test a single, global hypothesis rather than multiple ones...
  2. ncbi Multiple inferences using confidence intervals
    J Ludbrook
    Carlton North, Victoria, Australia
    Clin Exp Pharmacol Physiol 27:212-5. 2000
    ..This can be done for differences between group means in the case of continuous variables and for odds ratios or relative risks in the case of categorical variables set out as 2 x 2 tables...
  3. ncbi Statistics in physiology and pharmacology: a slow and erratic learning curve
    J Ludbrook
    Carlton North, Victoria, Australia
    Clin Exp Pharmacol Physiol 28:488-92. 2001
    ..It follows that research groups, national grant-giving agencies and academic institutions must make provision for the proper training and subsequent employment of biostatisticians...
  4. ncbi Statistical techniques for comparing measurers and methods of measurement: a critical review
    John Ludbrook
    The University of Melbourne, Parkville, Victoria, Australia
    Clin Exp Pharmacol Physiol 29:527-36. 2002
    ..Simple techniques for detecting bias in the case of ordered categorical variables are described and commended to investigators...
  5. ncbi Interim analyses of data as they accumulate in laboratory experimentation
    John Ludbrook
    Department of Surgery, The University of Melbourne, Parkville, Victoria, Australia
    BMC Med Res Methodol 3:15. 2003
    ..But in the setting of laboratory experiments such analyses are usually conducted secretly and with no provisions for the necessary adjustments of the Type I error-rate...
  6. ncbi Statistics in biomedical laboratory and clinical science: applications, issues and pitfalls
    John Ludbrook
    Department of Surgery, The University of Melbourne, Melbourne, Australia
    Med Princ Pract 17:1-13. 2008
    ..Finally, the educational value to investigators of interaction with a biostatistician, before, during and after a study, cannot be overemphasized...
  7. ncbi Outlying observations and missing values: how should they be handled?
    John Ludbrook
    Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia
    Clin Exp Pharmacol Physiol 35:670-8. 2008
    ..If the missing values have not occurred at random, but are associated with some property of the individuals being studied, the subsequent analysis may be biased...