Article Figures & Data
Figures
- Figure 1.
Two-level nesting, or clustering.
- Figure 2.
Three-level nesting.
Tables
Number of Physicians Number of Patients Total Number ρ= 0.017 Power k m (mk) DE ESS tTest* *Power to detect a minimum effect size of 0.5 when one half the clusters is randomly assigned to treatment and the other half to placebo, and mean responses are compared using a 2-sample t test made at the .05 level of significance. m = number of subjects in a cluster; k= number of clusters; mk = total number of subjects in a clustered study; DE = design effect; and ESS = effective sample size. 4 32 128 1.527 84 61 8 16 128 1.255 102 70 16 8 128 1.119 114 75 32 4 128 1.051 122 78 64 2 128 1.017 126 79 128 1 128 1.000 128 80 Number of Physicians Number of Patients Total Number ρ= 0.017 Power k m (mk) DE ESS tTest* *Power to detect a minimum effect size of 0.5 when one half the clusters is randomly assigned to treatment and the other half to placebo, and mean responses are compared using a 2-sample t test made at the .05 level of significance. m = number of subjects in a cluster; k= number of clusters; mk = total number of subjects in a clustered study; DE = design effect; and ESS = effective sample size. 4 10 40 1.153 34 29 4 20 80 1.323 60 47 4 40 160 1.663 96 67 4 80 320 2.343 136 82 Number of Physicians Number of Patients Total Number ρ= 0.017 Power k m (mk) DE ESS tTest* *Power to detect a minimum effect size of 0.5 when one half the clusters is randomly assigned to treatment and the other half to placebo, and mean responses are compared using a 2-sample t test made at the .05 level of significance. m = number of subjects in a cluster; k= number of clusters; mk = total number of subjects in a clustered study; DE = design effect; and ESS = effective sample size. 2 10 20 1.153 18 16 4 10 40 1.153 36 30 8 10 80 1.153 70 50 16 10 160 1.153 138 83
Supplemental Appendix
Basic Statistical Ideas
Files in this Data Supplement:
- Supplemental data: Appendix - PDF file, 1 page, .44 MB.
The Article in Brief
A primary care research study can involve data at both group and individual levels. It is important for researchers to recognize and understand the ways in which this "clustering" can affect their analyses of data.
In this issue
Jump to section
- Article
- Abstract
- INTRODUCTION
- DEFINITION AND EXPLANATION OF CLUSTERED DESIGNS
- ADVANTAGES AND DISADVANTAGES OF CLUSTERED DESIGNS
- THE INTRACLUSTER CORRELATION COEFFICIENT, OR ρ
- EFFECTIVE SAMPLE SIZE AND THE DESIGN EFFECT
- THE EFFECT OF ρ AND THE DESIGN EFFECT ON POWER AND SAMPLE SIZE CALCULATIONS
- SUMMARY
- Footnotes
- REFERENCES
- For Further Reading:
- Figures & Data
- eLetters
- Info & Metrics
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