MANCOVAMultivariate Analysis of Covariance
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For data analysis two MANCOVA were performed, one for the primary dimensions and the other for the global indexes.
However, the analysed populations had significant sexual dimorphism in body shape--including mean head width, trunk length and tail length (Table 1, P < 0.001)--combined with geographical variation; however, there was no interaction between these two factors (MANCOVA: geographical area, [F.sub.1,51] = 0.689, P = 0.038; sex, [F.sub.151] = 0.076, P < 0.001; interaction, [F.sub.151] = 0.743, P = 0.127).
MANCOVA showed that there were no significant interactions among the three independent variables.
Taken together, the mean comparisons and MANCOVA results suggest history of similar incidents is an important factor that influences directors' recommendations in terms of types of sanctions, with fine recommended if there is suspicion of prior incidents and warning recommended if there are no prior incidents suspected.
Results of the repeated measures MANCOVA indicated a significant multivariate main effect for time (pretest vs.
A MANCOVA was conducted to determine whether there were differences among the language-brokering groups for the parenting measures (i.e., nurturanee, connection, disrespect, and psychological control) with gender, ethnicity, and nativity as covariates.
Based on Wilks' lambda multivariate test, MANCOVA results showed an overall effect of gender [[lambda]= 0.92, [F.sub.(7, 426)] = 5.43, p< .001] and country [[lambda] = 0.89, [F.sub.7, 426)] = 7.77, p< .001], but not for the interaction term [[lambda] = 0.99, [F.sub.7, 426)] = 0.75, p= .629].
To explore the study hypothesis that dancers with high shame would experience less self-esteem, greater anxiety, and more cumulative ACEs than low shame dancers, a MANCOVA (with age and gender as covariates) was conducted.
Sin embargo, se encontraron diferencias significativas en el MANOVA postest-pretest, F(1,74)=2.31, p<.01, al igual que en el MANCOVA postest-pretest, F(1,74)=3.45, p<.01.
Therefore, MANCOVA analysis was used for analyzing inferential statistics which pre-test values were used as covariance variable, and after the significance of this test, Shidak post-test was used as a complementary test for two by two comparisons.