Table 3.

Simulation Results for Sample Analysis Method (1000 Iterations)

Sampling Design	Survey Size	Relative Biasa	Variance	MSEb	Coverage
Simple Random	20,000	−0.57%	2.5×10−3	2.7×10−3	94.5%
Simple Random	15,000	−0.49%	2.9×10−3	2.9×10−3	92.4%
Simple Random	5,000	−0.55%	5.0×10−3	5.2×10−3	83.9%
Simple Random	1,000	0.05%	2.1×10−2	2.1×10−2	53.2%
Random Probability	20,000	−0.57%	4.6×10−3	4.7×10−3	86.8%
Random Probability	15,000	−0.14%	5.8×10−3	5.8×10−3	82.8%
Random Probability	5,000	−0.20%	1.3×10−2	1.3×10−2	61.7%
Random Probability	1,000	0.61%	4.7×10−2	4.7×10−2	38.0%
Biased Probability	20,000	−0.55%	1.7×10−3	1.8×10−3	97.9%
Biased Probability	15,000	−0.59%	1.9×10−3	2.0×10−3	97.6%
Biased Probability	5,000	−0.66%	2.6×10−3	2.7×10−3	94.0%
Biased Probability	1,000	−1.18%	7.8×10−3	8.4×10−3	71.4%
Biased Stratified	20,000	−0.64%	2.2×10−3	2.4×10−3	96.2%
Biased Stratified	15,000	−0.53%	2.7×10−3	2.8×10−3	93.3%
Biased Stratified	5,000	−0.47%	4.9×10−3	4.9×10−3	84.6%
Biased Stratified	1,000	−0.19%	2.1×10−2	2.1×10−2	49.4%

MSE, mean squared error

^aRelative $\text{Bias}=\left(\overline{{\mathit{\text{IDR}}}_{\mathit{\text{Est}}}}-{\mathit{\text{IDR}}}_{\mathit{\text{True}}}\right)/{\mathit{\text{IDR}}}_{\mathit{\text{True}}}\times 100\%$

^bMSE = Bias² + Variance