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T
he journals Circulation and BMJ have periodically published statistical notes that are accessible for clinician researchers. We have arranged them here by topic.
1. Basic Statistical Concepts
2. Philosophical issues in interpretation
3. Descriptive Data Analysis
4. Transformation of Data
5. Measurement Issues
6. Basic measures of statistical association
7. Correlation
8. Survival Analysis
9. Interaction
10. Issues related to Diagnostic Testing
11. Clinical Trials
(includes
Cluster randomized trials
)
12. Statistical synthesis of evidence
1. Basic Statistical Concepts
Variables and parameters
The normal distribution
Units of analysis
Estimation From Samples
2. Philosophical issues in interpretation
Bayesians and frequentists
Generalisation and extrapolation
Absence of evidence is not evidence of absence
One and two sided tests of significance
Multiple significance tests: the Bonferroni method
Regression towards the mean
Some examples of regression towards the mean
3. Descriptive Data Analysis
Presentation of numerical data
Quartiles, quintiles, centiles, and other quantiles
Descriptive Statistics and Graphical Displays
Detecting skewness from summary information
4. Transformation of Data
Transforming data
Logarithms
The use of transformation when comparing two means
Transformations, means, and confidence intervals
5. Measurement Issues
Measurement error I
Measurement error II
Measurement error and correlation coefficients
Measurement error proportional to the mean
Validating scales and indexes
Cronbach's alpha
6. Basic measures of statistical association
Hypothesis Testing: Means
Weighted comparison of means
Hypothesis Testing: Proportions
Rank Score Tests
Comparing several groups using analysis of variance
The odds ratio
7. Correlation
Calculating correlation coefficients with repeated observations: Part 1--correlation within subjects
Calculating correlation coefficients with repeated observations: Part 2--correlation between subjects
Correlation, regression, and repeated data
Correlation and Regression
8. Survival Analysis
Survival probability (Kaplan-Meier method)
Time to event (survival) data
Survival Methods
9. Interaction
Interaction 1: heterogeneity of effects
Interaction 2: compare effect sizes not P values
Interaction 3: How to examine heterogeneity
Interaction revisited: the difference between two estimates
10. Issues related to Diagnostic Testing
Diagnostic tests 1: sensitivity and specificity
Diagnostic tests 2: predictive values
Diagnostic tests 3: receiver operating characteristic plots
Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models
11. Clinical Trials
Design of Randomized Controlled Trials
Treatment allocation in controlled trials: why randomise?
How to randomize
Blinding in clinical trials and other studies
Concealing treatment allocation in randomised trials
Analysing controlled trials with baseline and follow up measurements
Evaluation of Randomized Controlled Trials
Matching*
Propensity Scores in Cardiovascular Research*
Cluster randomized trials
Trials randomised in clusters
Sample size in cluster randomization
The intracluster correlation coefficient in cluster randomization
*Also relates to observational studies
12. Statistical synthesis of evidence
Meta-Analysis
Core Faculty
Nae-Yuh Wang, PhD
Dhananjay Vaidya, MD, PhD
Bionutrition
|
Biostatistics
|
Exercise
|
Informatics
|
Laboratory
|
Nursing
|
Sleep
|
Cardiovascular
Copyright © 2009 Clinical Research Unit
Johns Hopkins Bayview Medical Campus 410.550.1850
