Page 184 - Applied Statistics Using SPSS, STATISTICA, MATLAB and R
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164      4 Parametric Tests of Hypotheses


              The observed significance values  in  the  last row  of Table 4.23 lead  to the
           rejection of the null hypothesis for all contrasts except contrast (c).

           Example 4.22

           Q: Determine the power for the two-way ANOVA test of previous Example 4.20
           and the minimum number of cases per group that affords a row effect power above
           95%.
           A: Power computations for the two-way ANOVA follow the approach explained in
           section 4.5.2.3.
              First, one has to determine the cell statistics in order to be able to compute the
           standardised effects of the columns, rows and interaction. The cell statistics can be
           easily computed with SPSS, STATISTICA MATLAB or R. The values for this
           example are shown in Table 4.24. With STATISTICA one can fill in these values
           in order to compute the standardised effects as shown in Figure 4.21b. The other
           specifications are entered in the power specification window, as shown in Figure
           4.21a.

           Table 4.24. Cell statistics for the FHR-Apgar dataset used in Example 4.20.
                HOSP       APCLASS          N           Mean        Std. Dev.
                  1            0            6           64.3          4.18
                  1            1            6           64. 7         5.57
                  2            0            6           43.0          6.81
                  2            1            6           41.5          7.50
                  3            0            6           70.3          5.75
                  3            1            6           41.5          8.96



















           Figure 4.21.  Specifying  the parameters for the power computation  with
           STATISTICA in Example  4.22: a) Fixed parameters; b) Standardised effects
           computed with the values of Table 4.24.
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