PRINT Subcommand (UNIANOVA command)

PRINT controls the display of optional output.

  • Some PRINT output applies to the entire UNIANOVA procedure and is displayed only once.
  • Additional output can be obtained on the EMMEANS, PLOT, and SAVE subcommands.
  • Some optional output may greatly increase the processing time. Request only the output you want to see.
  • If no PRINT command is specified, default output for a univariate analysis includes a factor information table and a Univariate Tests table (ANOVA) for all effects in the model.
  • If more than one PRINT subcommand is specified, only the last one is in effect.

The following keywords are available for UNIANOVA univariate analyses.

DESCRIPTIVES. Basic information about each cell in the design. Observed means, standard deviations, and counts for the dependent variable in all cells. The cells are constructed from the highest-order crossing of the factors. If the number of factors plus the number of split variables exceeds 18, the Descriptive Statistics table is not printed.

HOMOGENEITY. Test(s) of homogeneity of variance. Levene’s test for equality of variances for the dependent variable across all level combinations of the factors. For full-factorial models without covariates, Levene statistics based on the mean, median, and trimmed mean, and with adjusted degrees of freedom for the test using the median are displayed. For other models only the original Levene statistic based on the mean is displayed.

PARAMETER. Parameter estimates. Parameter estimates, standard errors, t tests, and confidence intervals for each test.

OPOWER. Observed power. The observed power for each test.

LOF. Lack of fit. Lack of fit test that allows you to determine if the current model adequately accounts for the relationship between the response variable and the predictors.

ETASQ. Partial eta-squared (η2 ). This value is an overestimate of the actual effect size in an F test.

GEF. General estimable function table. This table shows the general form of the estimable functions.

TEST(LMATRIX). Set of contrast coefficients (L) matrices. The transpose of the L matrix (L') is displayed. This set always includes one matrix displaying the estimable function for each effect appearing or implied in the DESIGN subcommand. Also, any L matrices generated by the LMATRIX or CONTRAST subcommands are displayed. TEST(ESTIMABLE) can be used in place of TEST(LMATRIX).

MBP. Modified Breusch-Pagan test for heteroskedasticity. Tests the null hypothesis that the variance of the errors does not depend on the values of the independent variables. You can use the MBPDESIGN subcommand to specify the model on which the test is based. If the MBP keyword is specified without MBPDESIGN, then the model consists of a constant term, a term that is linear in the predicted values, a term that is quadratic in the predicted values, and an error term. For a multivariate model, tests are displayed for each dependent variable.

BP. Breusch-Pagan test for heteroskedasticity. Tests the null hypothesis that the variance of the errors does not depend on the values of the independent variables. You can use the BPDESIGN subcommand to specify the model on which the test is based. If the BP keyword is specified without BPDESIGN, then the model consists of a constant term, a term that is linear in the predicted values, a term that is quadratic in the predicted values, and an error term. For a multivariate model, tests are displayed for each dependent variable.

F. F test for heteroskedasticity. Tests the null hypothesis that the variance of the errors does not depend on the values of the independent variables. You can use the FDESIGN subcommand to specify the model on which the test is based. If the F keyword is specified without FDESIGN, then the model consists of a constant term, a term that is linear in the predicted values, a term that is quadratic in the predicted values, and an error term. For a multivariate model, tests are displayed for each dependent variable.

WHITE. White's test for heteroskedasticity. Tests the null hypothesis that the variance of the errors does not depend on the values of the independent variables. For a multivariate model, tests are displayed for each dependent variable.

Example

UNIANOVA DEP BY A B WITH COV
  /PRINT=DESCRIPTIVE, TEST(LMATRIX), PARAMETER
  /DESIGN.
  • Because the design in the DESIGN subcommand is set as blank, the default design is used. In this case, the design includes the intercept term, the covariate COV, and the full factorial terms of A and B, which are A, B, and A*B.
  • For each combination of levels of A and B, the descriptive statistics of DEP are displayed.
  • The set of L matrices that generates the sums of squares for testing each effect in the design is displayed.
  • The parameter estimates, their standard errors, t tests, confidence intervals, and the observed power for each test are displayed.