Noncentrality Interval Estimation and the Evaluation of Statistical Models

Select the Quick
tab of the 1-Way
ANOVA: Interval Estimation dialog box to access options to implement
the procedure (Fleishman, 1980; Steiger & Fouladi, 1997) for computing
a confidence interval for RMSSE, the root mean square standardized effect
size . Note that STATISTICA can
also compute exact post hoc confidence intervals on power, and the sample
size necessary to achieve a power goal, based on results from a study
that has already been performed (see discussion below).

Observed F. In the Observed F box, enter the observed value of the F-statistic.

No. of Groups. In
the No. of Groups box, enter
the number of independent samples on which the analysis is based.

N per Group. In the N per Group box, enter the sample size per group.

Alpha. In the Alpha field, enter the type I error rate used as a target in calculating post hoc confidence intervals on power and required sample size.

Conf. Level. In the Conf. Level box, enter the confidence level for the confidence interval calculation. Note that confidence limits are given for the following quantities:

Delta. These confidence limits are for the noncentrality parameter of the noncentral F-distribution.

RMSSE. These confidence limits are for the RMSSE.

Power. These confidence limits
are post hoc statistical bounds on power.

Required N. Given an observed F-statistic, the program calculates a confidence interval on the sample size necessary to achieve a particular level of power, and reports the confidence limits here.

Power Goal. In the Power Goal box, enter the power goal used as a target in calculating post hoc confidence intervals on sample size.