This issue of Rheumatic Disease Clinics, guest edited by Dr. Sindhu Johnson, will cover Advances in Epidemiologic Methods to Study Rheumatic Diseases. This unique volume will discuss the following topics, among others: Minimal clinically important difference (MCID) for outcome measures, Alternative longitudinal study designs, Propensity score methods for observational data, Approaches to deal with missing data, Applied Bayesian Methods in Rheumatology, Qualitative methods, Similarity Network Fusion, Systematic reviews/meta-analysis and randomized trials, and Integrated analysis of data obtained in various reading campaigns of images.
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Table of Contents
Advanced Epidemiologic Methods for the Study of Rheumatic Diseases - Table of Contents
Foreword: The Brave New World of Rheumatic Disease Research Today
Preface: Advanced Epidemiologic Methods for the Study of Rheumatic and Musculoskeletal Diseases
Minimal Clinically Important Difference: A Review of Outcome Measure Score Interpretation
Alternative Design and Analytical Techniques for Longitudinal Rheumatology Studies: Improved Understanding of Outcomes
Propensity Score Methods for Bias Reduction in Observational Studies of Treatment Effect
US National Health and Nutrition Examination Survey Arthritis Initiatives, Methodologies and Data
Qualitative Methods to Advance Care, Diagnosis, and Therapy in Rheumatic Diseases
Similarity Network Fusion: A Novel Application to Making Clinical Diagnoses
Randomized Trials, Meta-Analyses, and Systematic Reviews: Using Examples
from Rheumatology
"Big Data" in Rheumatology: Intelligent Data Modeling Improves the Quality of Imaging Data
Strategies for Dealing with Missing Accelerometer Data
Use of Administrative Databases to Assess Reproductive Health Issues in Rheumatic Diseases
Measuring Patient Preferences: An Overview of Methods with a Focus on Discrete Choice Experiments
Cluster and Multiple Correspondence Analyses in Rheumatology: Paths to Uncovering Relationships in a Sea of Data
Applied Bayesian Methods in the Rheumatic Diseases
