Literature DB >> 6528136

Why do we need some large, simple randomized trials?

S Yusuf, R Collins, R Peto.   

Abstract

Mesh：

Year:  1984        PMID： 6528136     DOI： 10.1002/sim.4780030421

Source DB:  PubMed          Journal:  Stat Med        ISSN： 0277-6715            Impact factor:   2.373


× No keyword cloud information.
  147 in total

Review 1.  Sifting the evidence-what's wrong with significance tests?

Authors:  J A Sterne; G Davey Smith
Journal:  BMJ       Date:  2001-01-27

Review 2.  Randomised controlled trials in cardiovascular medicine: past achievements, future challenges.

Authors:  S Yusuf
Journal:  BMJ       Date:  1999-08-28

3.  Sample size estimation for the sorcerer's apprentice. Guide for the uninitiated and intimidated.

Authors:  J G Ray; M J Vermeulen
Journal:  Can Fam Physician       Date:  1999-07       Impact factor: 3.275

4.  Joint British recommendations on prevention of coronary heart disease in clinical practice. British Cardiac Society, British Hyperlipidaemia Association, British Hypertension Society, endorsed by the British Diabetic Association.

Authors: 
Journal:  Heart       Date:  1998-12       Impact factor: 5.994

5.  The case for a new system for oversight of research on human subjects.

Authors:  K Jamrozik
Journal:  J Med Ethics       Date:  2000-10       Impact factor: 2.903

6.  Quality of randomised controlled trials in head injury. Trials in head injury are more complex than review suggests.

Authors:  G D Murray; G M Teasdale
Journal:  BMJ       Date:  2000-11-11

7.  Why randomized controlled trials fail but needn't: 2. Failure to employ physiological statistics, or the only formula a clinician-trialist is ever likely to need (or understand!).

Authors:  D L Sackett
Journal:  CMAJ       Date:  2001-10-30       Impact factor: 8.262

8.  For and against: clinical equipoise and not the uncertainty principle is the moral underpinning of the randomised controlled trial.

Authors:  C Weijer; S H Shapiro; K Cranley Glass
Journal:  BMJ       Date:  2000-09-23

9.  Another look at outcomes and outcome measures in psychiatry: cui bono?

Authors:  Cynthia L Arfken; Richard Balon
Journal:  Psychother Psychosom       Date:  2013-11-19       Impact factor: 17.659

10.  Propensity scores for confounder adjustment when assessing the effects of medical interventions using nonexperimental study designs.

Authors:  T Stürmer; R Wyss; R J Glynn; M A Brookhart
Journal:  J Intern Med       Date:  2014-02-13       Impact factor: 8.989
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.