Modeling and Multivariate Methods - SAS

Chapter 3 Fitting Standard Least Squares Models 77
Estimates
7. Replace the Delta values with 3,6, and 1 as shown in Figure 3.17.
8. Replace the Number values with 20, 60, and 10 as shown in Figure 3.17.
9. Select Solve for Power and Solve for Least Significant Number.
10. Click Done.
For details about the power results shown in Figure 3.17, see “Text Reports for Power Analysis” on
page 78. For details about the Power Details options, see “Power Details Window” on page 77.
Power Details Window
In the Alpha, Sigma, Delta, and Number columns, you can enter a single value, two values, or the start,
stop, and increment for a sequence of values. Power calculations are done on all possible combinations of
the values that you specify.
Table 3.9 Description of the Power Details Window
Alpha (α)
Sigma (σ)
Delta (δ)
Number (n)
Solve for Power
Solve for Least
Significant Number
Solve for Least
Significant Value
Represents the significance level between 0 and 1, usually 0.05, 0.01, or
0.10. Initially, Alpha automatically has a value of 0.05. Click in one of the
three boxes to enter one, two, or a sequence of values.
Represents the standard error of the residual error in the model. Initially,
RMSE (the square root of the mean square error) is in the first box. Click in
one of the three boxes to enter one, two, or a sequence of values.
Represents the raw effect size. See “Effect Size” on page 78, for details.
Initially, the square root of the sum of squares for the hypothesis divided by
n is in the first box. Click in one of the three boxes to enter or edit one, two,
or a sequence of values.
Represents the sample size. Initially, the actual sample size is in the first box.
Click in one of the three boxes to enter or edit one, two, or a sequence of
values.
Solves for the power (the probability of a significant result) as a function of
α, σ, δ, and n.
Solves for the number of observations expected to achieve significance alpha
given α, σ, and δ.
Solves for the value of the parameter or linear test that produces a p-value of
alpha. This is a function of α, σ, and n.This option is available only for
one-degree-of-freedom tests and is used for individual parameters.