1.
Radar plots: a useful way for presenting multivariate health care data
by Saary, M. Joan
Journal of clinical epidemiology, 2008, Vol.61 (4), p.311-317

2.
Attention should be given to multiplicity issues in systematic reviews
by Bender, Ralf
Journal of clinical epidemiology, 2008, Vol.61 (9), p.857-865

3.
[11C]Metomidate Positron Emission Tomography of Adrenocortical Tumors in Correlation with Histopathological Findings
by Hennings, Joakim
The journal of clinical endocrinology and metabolism, 2006-04, Vol.91 (4), p.1410-1414

4.
A Randomized Comparison of Patients’ Understanding of Number Needed to Treat and Other Common Risk Reduction Formats
by Sheridan, Stacey L.
Journal of general internal medicine : JGIM, 2003-11, Vol.18 (11), p.884-892

5.
Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis
by Twisk, Jos
Journal of clinical epidemiology, 2013, Vol.66 (9), p.1022-1028

6.
In meta-analyses of proportion studies, funnel plots were found to be an inaccurate method of assessing publication bias
by Hunter, James P
Journal of clinical epidemiology, 2014, Vol.67 (8), p.897-903

7.
Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial
by Salanti, Georgia
Journal of clinical epidemiology, 2011, Vol.64 (2), p.163-171

8.
False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
by Glickman, Mark E
Journal of clinical epidemiology, 2014, Vol.67 (8), p.850-857

9.
Failure rates of stemmed metal-on-metal hip replacements: analysis of data from the National Joint Registry of England and Wales
by Smith, Alison J, MSc
The Lancet (British edition), 2012, Vol.379 (9822), p.1199-1204

10.
Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry
by Peters, Jaime L
Journal of clinical epidemiology, 2008, Vol.61 (10), p.991-996

11.
A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions
by Latouche, Aurelien
Journal of clinical epidemiology, 2013, Vol.66 (6), p.648-653

12.
The statistical significance of randomized controlled trial results is frequently fragile: a case for a Fragility Index
by Walsh, Michael
Journal of clinical epidemiology, 2014, Vol.67 (6), p.622-628

13.
Optimal Unified Approach for Rare-Variant Association Testing with Application to Small-Sample Case-Control Whole-Exome Sequencing Studies
by Lee, Seunggeun
American journal of human genetics, 2012-08-10, Vol.91 (2), p.224-237

14.
The size of a pilot study for a clinical trial should be calculated in relation to considerations of precision and efficiency
by Sim, Julius
Journal of clinical epidemiology, 2012, Vol.65 (3), p.301-308

15.
The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes
by Mokkink, Lidwine B
Journal of clinical epidemiology, 2010, Vol.63 (7), p.737-745

16.
Validation of the Addenbrooke's Cognitive Examination III in Frontotemporal Dementia and Alzheimer's Disease
by Hsieh, Sharpley
Dementia and geriatric cognitive disorders, 2013-09, Vol.36 (3-4), p.242-250

17.
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
by Westreich, Daniel
Journal of clinical epidemiology, 2010, Vol.63 (8), p.826-833

18.
The Impact of Excision of Ovarian Endometrioma on Ovarian Reserve: A Systematic Review and Meta-Analysis
by Raffi, Francesca
The journal of clinical endocrinology and metabolism, 2012-09, Vol.97 (9), p.3146-3154

19.
Correspondence analysis is a useful tool to uncover the relationships among categorical variables
by Sourial, Nadia
Journal of clinical epidemiology, 2010, Vol.63 (6), p.638-646

20.
Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses
by Brok, Jesper
Journal of clinical epidemiology, 2008, Vol.61 (8), p.763-769
