Designing longitudinal studies in epidemiology. Donna Spiegelman Professor of Epidemiologic Methods Departments of Epidemiology and Biostatistics email@example.com Xavier Basagana Doctoral Student Department of Biostatistics, Harvard School of Public Health . Background.
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Professor of Epidemiologic Methods
Departments of Epidemiology and Biostatistics
Doctoral StudentDepartment of Biostatistics,
Harvard School of Public Health
Based on clinical trials:
When is not fixed, is defined at time s instead of at time
When , will be defined as the percent change from baseline (or from the mean initial time) to the end of follow-up (or to the mean final time) in the exposed group, i.e.
= 0: CS
= 0.3: CS
= 1: AR(1)
model tics=grad age gradage/s;
model tics=grad age gradage/s ddfm=bw;
Random intercept age/type=un subject=id;
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Constant mean difference (CMD) or Linearly divergent difference (LDD)? ldd
The alternative is LDD.
Enter the total sample size (N): 15000
Enter the number of post-baseline measures (r>0): 1
Enter the time between repeated measures (s): 2
Enter the exposure prevalence (pe) (0<=pe<=1): 0.062
Enter the variance of the time variable at baseline, V(t0)
(enter 0 if all participants begin at the same time): 4
Enter the correlation between the time variable at baseline and exposure, rho[e,t0]
(enter 0 if all participants begin at the same time): -0.01
Will you specify the alternative hypothesis on the absolute (beta coefficient) scale (1)
or the relative (percent) scale (2)? 2
The alternative hypothesis will be specified on the relative (percent) change scale.
Enter the percent change from baseline to end of follow-up among unexposed (p2)
(e.g. enter 0.10 for a 10% change): -0.006
Enter the percent difference between the change from baseline to
end of follow-up in the exposed group and the unexposed group (p3) (e.g. enter 0.10 for a 10% difference): 0.7
Which covariance matrix are you assuming: compound symmetry (1),
damped exponential (2) or random slopes (3)? 2
You are assuming DEX covariance
Enter the residual variance of the response given the assumed model covariates (sigma2): 12
Enter the correlation between two measures of the same subject separated by one unit (rho): 0.3
Enter the damping coefficient (theta): 0.10
Power = 0.4206059
N=15,000 for these calculations
70% difference in cognitive
decline by GRAD with 90%
± 20% difference in cognitive
decline by current hormone
use with 90% power?