Statistical Analysis
Sample size calculations and power analysis
120
Sample Size
80%
Statistical Power
r=0.45
Effect Size
96
Expected Completers
Power Curve
Statistical power vs sample size (r=0.45, α=0.05)
Sample Size Justification
Primary Analysis
With n=120 and expected effect size r=0.45, we achieve >80% power for the primary correlation analysis.
Subgroup Analyses
With ~60 patients per sex and ~60 per intervention, we maintain ~90% power for sex-stratified and intervention-stratified analyses.
Dropout Adjustment
Assuming 2400% dropout, we expect 96 completers from 120 enrolled.
Statistical Parameters
| Parameter | Value | Description |
|---|---|---|
| Sample Size (n) | 120 | Total enrolled participants |
| Effect Size (r) | 0.45 | Expected correlation coefficient (conservative estimate) |
| Alpha (α) | 0.05 | Type I error rate (two-sided) |
| Power (1-β) | >80% | Probability of detecting true effect |
| Expected Dropout | 2400% | Anticipated loss to follow-up |
| Recruitment Rate | 2.2 pts/mo/center | Expected enrollment rate per center |
Primary Endpoint
Correlation between baseline DIT (from LPMT) and % total body weight loss at 12 months
Discussion: Statistics
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