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According to current estimates, type 2 diabetes mellitus (T2DM) affects approximately 21 million Americans. 1 Insulin resistance, the primary defect present in T2DM, is mainly due to genetic and lifestyle factors.
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Estimated Type I error probabilities, (hat {alpha }), were based on 10000 replications.
As such, the objective of this study was to estimate type 1 diabetes mortality in a population-based registry sample in the USVI.
We first estimate type I error rates under a variety of polygenic (ρa) and environmental (ρe) correlations in homogeneous population setting, as listed in Table 1.
The Null-Specific SNPs were intended for estimating type I error rate and the Causal-Specific SNPs for estimating power for a specific allele frequency set in the populations.
We employed 1000 simulations to estimate type I error rates.
Table 1 reports the estimated type I error rates from each method under different conditions.
First, we estimated type 2 diabetes risk in our population using a validated diabetes risk score.
We conducted two types of simulations, one to estimate Type I error and the other to estimate power.
This study aimed to estimate Type 2 diabetes incidence and its associated risk factors in an Iranian urban population.
For each scenario, the simulation data were replicated 1000 times to estimate type I error rate or power.
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