SELECTED SPSS OUTPUT FOR ONEWAY ANCOVA
SELECTED SPSS OUTPUT FOR ONEWAY ANCOVA
Descriptive statistics for each category of the independent variable appear in Table 9.15, labeled "Descriptive
Statistics." The "Tests of Between-Subjects Effects" table (Table 9.16) lists both the independent variable, in
this case, technique, and the covariate, in this case health, as predictors of the dependent variable. The values
used to determine whether changes in heart rate differ significantly with respect to the independent variable
and considering the possible effects of the covariate appear in the top row of this table.
According to results of this analysis, those exposed each of the three relaxation techniques
did not experience significantly different changes in heart rate. The p value of .183 lies
above the standard α of .05 as well as above an elevated α of .10, indicating that one would
accept the null hypothesis of equality at these levels of significance. The analysis
considered differences in the overall health of patients in the three independent-variable
conditions when calculating these results, hence the designation of a Type III Sum of
Squares value in the "Tests of Between-Subjects Effects" table. ▄
The process used to request and analyze SPSS results of an ANCOVA translate easily into a
MANCOVA. Performing a MANCOVA in SPSS requires the same steps, only you would need
to use SPSS's Multivariate, rather than Univariate window. In the Multivariate window, you
can identify as many dependent variables as needed for the analysis. SPSS assembles the
values for the dependent variables into canonical variate scores. By inputting names of
covariates into the "Covariate(s)" box, you tell SPSS to consider the roles of these covariates
upon the relationship between the independent variables and the canonical variate.
The MANCOVA output that results contains a "Multivariate Tests" table. This table
resembles the "Multivariate Tests" table produced for a MANCOVA, however, it also
includes the names of covariates. Assuming you wish to consider results based upon the
Wilks' Lambda procedure for obtaining F, you should focus upon values in this row of the
table. A p-value that exceeds α indicates significant differences between mean canonical
variate values for the covariate-biased independent-variable categories.
Statistics." The "Tests of Between-Subjects Effects" table (Table 9.16) lists both the independent variable, in
this case, technique, and the covariate, in this case health, as predictors of the dependent variable. The values
used to determine whether changes in heart rate differ significantly with respect to the independent variable
and considering the possible effects of the covariate appear in the top row of this table.
According to results of this analysis, those exposed each of the three relaxation techniques
did not experience significantly different changes in heart rate. The p value of .183 lies
above the standard α of .05 as well as above an elevated α of .10, indicating that one would
accept the null hypothesis of equality at these levels of significance. The analysis
considered differences in the overall health of patients in the three independent-variable
conditions when calculating these results, hence the designation of a Type III Sum of
Squares value in the "Tests of Between-Subjects Effects" table. ▄
The process used to request and analyze SPSS results of an ANCOVA translate easily into a
MANCOVA. Performing a MANCOVA in SPSS requires the same steps, only you would need
to use SPSS's Multivariate, rather than Univariate window. In the Multivariate window, you
can identify as many dependent variables as needed for the analysis. SPSS assembles the
values for the dependent variables into canonical variate scores. By inputting names of
covariates into the "Covariate(s)" box, you tell SPSS to consider the roles of these covariates
upon the relationship between the independent variables and the canonical variate.
The MANCOVA output that results contains a "Multivariate Tests" table. This table
resembles the "Multivariate Tests" table produced for a MANCOVA, however, it also
includes the names of covariates. Assuming you wish to consider results based upon the
Wilks' Lambda procedure for obtaining F, you should focus upon values in this row of the
table. A p-value that exceeds α indicates significant differences between mean canonical
variate values for the covariate-biased independent-variable categories.
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