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To make these power calculations, we performed a limited simulation study using the paradigm of risk set sampling: for each case, two controls would be selected from those at risk at the time of the case's second (contralateral) breast cancer diagnosis who matched the case on all factors (for example, race, age at diagnosis, and registry region).
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The precision of the method was estimated by analysing two test set samples for six times each.
Transcripts were filtered by their signal intensity values, selecting transcripts with intensity values between 20 and 100 percentile in at least 1 out of each set samples for differential analysis.
All the parameter sets sampled for the Fig. 4 belong to the mixed mode.
Several calculations were performed using the tool STATCALC of Epi-Info to set sample size for ECCAGE in the baseline.
Only the training set samples were classified for training the Biomarker Pattern Software 5.0.2 (Ciphergen).
for validation set samples (914 cases and 967 controls).
Using risk-set sampling for control selection renders the OR interpretable as an estimate of the corresponding rate ratio (RR).
To assist in setting sample size and for filter quality evaluation, the Cramer Rao bound is used.
Al-Saleh and Al-Kadiri (2000) suggested double ranked set sampling (DRSS) method for estimating the population mean.
Therefore the set sample size for this study was 825.
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