Different result for SPSS ANOVA and UNIANOVA

Posted by kd1 on
URL: http://spssx-discussion.165.s1.nabble.com/Different-result-for-SPSS-ANOVA-and-UNIANOVA-tp5718514.html

I am not sure if the below provides enough information, but why are the values different if I test the same variables using ANOVA or UNIANOVA (e.g. with ANOVA Bonferroni the difference between variable H and S is not significant, but is using UNIANOVA)?

ANOVA
Multiple Comparisons
Dependent Variable: Max Length (mm)
(I) Impactor Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
                                                Lower Bound Upper Bound
Tukey HSD A S 7.1743* 1.2667 .000 4.184 10.165
                H 4.1871* 1.2667 .003 1.197 7.177
        S A -7.1743* 1.2667 .000 -10.165 -4.184
                H -2.9871 1.2667 .050 -5.977 .003
        H A -4.1871* 1.2667 .003 -7.177 -1.197
                S 2.9871 1.2667 .050 -.003 5.977
Bonferroni A S 7.1743* 1.2667 .000 4.117 10.232
                H 4.1871* 1.2667 .003 1.130 7.244
        S A -7.1743* 1.2667 .000 -10.232 -4.117
                H -2.9871 1.2667 .058 -6.044 .070
        H A -4.1871* 1.2667 .003 -7.244 -1.130
                S 2.9871 1.2667 .058 -.070 6.044
*. The mean difference is significant at the 0.05 level.

UNIANOVA
Multiple Comparisons
Dependent Variable: Max Length (mm)
(I) Impactor Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
                                                Lower Bound Upper Bound
Tukey HSD A S 7.174* 1.2226 .000 4.288 10.061
                H 4.187* 1.2226 .002 1.301 7.074
        S A -7.174* 1.2226 .000 -10.061 -4.288
                H -2.987* 1.2226 .041 -5.874 -.101
        H A -4.187* 1.2226 .002 -7.074 -1.301
                S 2.987* 1.2226 .041 .101 5.874
Bonferroni A S 7.174* 1.2226 .000 4.223 10.125
                H 4.187* 1.2226 .002 1.236 7.138
        S A -7.174* 1.2226 .000 -10.125 -4.223
                H -2.987* 1.2226 .046 -5.938 -.036
        H A -4.187* 1.2226 .002 -7.138 -1.236
                S 2.987* 1.2226 .046 .036 5.938
"Based on observed means.
 The error term is Mean Square(Error) = 52.316."
*. The mean difference is significant at the .05 level.