![]() The required sample size is calculated as shown in cell G7 of Figure 2.Īs we can see, the minimum sample size is 74. 1 with power 95% if the experiment in Example 1 of MANOVA Basic Concepts is repeated? The power for Example 1 can be calculated by any of the following formulas (with reference to Figure 1).Įxample 2: What sample size would be required to detect a partial eta-square effect size of. 05), iter = the maximum number of iterations used in calculating the answer (default 1000) up to a precision of prec (default 0.000000001), the default for pow is. MANOVA_SIZE( f, k, g, pow, ttype, alpha, iter, prec) = the minimum sample size to obtain statistical power of pow for one-way MANOVA where f, k, g and ttype are as for MANOVA_POWER.Īlpha is the significance level (default. MANOVA_POWER( f n, k, g, ttype, alpha, iter, prec) = the statistical power for one-way MANOVA where the sample size is n, the number of dependent variables is k, the number of groups is g and the effect size is f, where f = the partial eta-square effect size if ttype = 1, f = eta-square if ttype = 2 and f = Pillai’s V if ttype = 3. Real Statistics Functions: The Real Statistics Resource Pack provides the following functions. Note that ‘Manova 1k’ is the name of the worksheet that contains the calculations in Figure 1 and 9 of MANOVA Basic Concepts. The power is 88% as calculated in cell B15 of Figure 1. ![]() This is the same approach used by G*Power.Įxample 1: What is the power for the one-way MANOVA in Example 1 of MANOVA Basic Concepts. Restricting our attention to the Pillai-Bartlett test, note too that the eta-square effect size can be expressed in terms of the Pillai-Bartlett Trace V or partial eta-square effect size h as follows:Īnd g = number of groups and k = number of dependent variables. Where η 2 = eta-square effect size, n = the sample size and s is as described in MANOVA Basic Concepts. We can calculate the power and minimum sample size in the same manner as described for one-way ANOVA based on the partial eta-square or eta-square effect size of Pillai’s V statistic and the noncentrality parameter equal to
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