37. SPSS AMOS - Moderation Analysis with Categorical Moderator using Multi-Group Analysis

Moderation with a categorical variable in IBM SPSS AMOS can be tested using multi-group analysis by constraining a single path and checking whether its fit changes across groups. In the example, “type of bank” (public vs. private) is treated as the moderator of the relationship between organizational commitment (OC) and collaborative culture (CC). The core question is whether OC predicts CC differently in public-sector banks compared with private-sector banks—and whether that difference is statistically meaningful.

The workflow starts by setting up a multi-group model in AMOS. The model is split into two groups corresponding to the categorical moderator levels (public bank and private bank). AMOS automatically labels parameters across groups once multi-group analysis is enabled, allowing the same structural relationship to be estimated separately for each group.

To test moderation, the analysis then constrains one specific regression path to be equal across groups. The transcript focuses on constraining the OC → CC path (labeled as B3 in the group-specific parameter notation). In practice, this means creating a new constraint (e.g., “constrain 1”) and setting the path coefficient for Group 1 equal to the corresponding coefficient for Group 2 (written as equality between the two group-specific parameters). This constrained model represents the null idea that the OC → CC relationship is identical across public and private banks.

After running the constrained model and comparing it to the unconstrained baseline, AMOS provides a “model comparison” output with a chi-square difference statistic. The key result is a chi-square difference of 5.4 with a significant p-value (p < .05) for the “constrain 1” comparison. That significance indicates the OC → CC relationship is not the same across the two bank categories: the moderator (bank type) meaningfully changes how organizational commitment relates to collaborative culture.

Significance alone doesn’t reveal whether the relationship is stronger or weaker in one category. To determine direction and magnitude, the analysis shifts to the parameter estimates for each group. The transcript compares the unstandardized regression coefficients for the OC → CC path: the coefficient is 0.446 in public-sector banks and 0.695 in private-sector banks, with both remaining significant within each group. Because the private-sector coefficient is larger, the moderation effect is interpreted as strengthening: organizational commitment has a stronger influence on collaborative culture in private banks than in public banks.

In short, the method uses multi-group analysis plus a single-path constraint to test whether a categorical moderator changes a specific relationship, then uses group-specific regression estimates to judge whether the effect is stronger or weaker for each category. The approach mirrors earlier two-group moderation logic, but AMOS handles the mechanics through constraints and chi-square difference model comparisons.