Example of Power and Sample Size for 2-Sample Poisson Rate

A traffic safety consultant wants to compare the number of cars per hour that travel on two different streets. Before collecting the data for a 2-sample Poisson rate test, the consultant uses a power and sample size calculation. The consultant wants to determine how large of a sample size the test needs to obtain a power of 0.9 and detect a comparison rate of 32 or 38 (a difference of 3 from the baseline rate of 35).

  1. Choose Stat > Power and Sample Size > 2-Sample Poisson Rate.
  2. In Comparison rates (R1), enter 32 38.
  3. In Power values, enter 0.9.
  4. In Baseline rate (R2), enter 35.
  5. Click OK.

Interpret the results

To detect a comparison rate of 32 with a power value of 0.9, the consultant needs a sample size of 79. To detect a comparison rate of 38 with a power value of 0.9, the consultant needs a sample size of 86. The analyst decides to collect a sample size of 86 to give the test a power value of at least 0.9 for both comparison rates. Because the target power value of 0.9 results in a sample size that is not an integer, Minitab also displays the power (Actual Power) for the rounded sample size.

Power and Sample Size

Test for 2-Sample Poisson Rate Testing comparison rate = baseline rate (versus ≠) Calculating power for baseline rate = 35 α = 0.05 “Lengths” of observation for sample 1, sample 2 = 1, 1
Results Comparison Sample Target Rate Size Power Actual Power 32 79 0.9 0.902793 38 86 0.9 0.902550 The sample size is for each group.

Power Curve for 2-Sample Poisson Rate

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