This sort of analysis is definitely not in my field but I think you could use Missing Value Codes for this.
Using Consumer Preferences example dataset. First example without Missing Value Codes:
Categorical analysis as follows:
Categorical(
X(:Age Group),
Responses(:Job Satisfaction),
Crosstab Transposed(1),
Legend(0),
Test Response Homogeneity(1)
)
jthi_0-1629127980364.png
Then set Not at all satisfied as missing value code and rerun analysis:
jthi_1-1629128032784.png
Missing Value Codes can be set from Column Properties:
jthi_2-1629128088783.png
Or if you don't need those rows at all, you could exclude them totally by first selecting one of the values you want to exclude and choosing Select Matching Cells:
jthi_3-1629128160913.png
Then from the left side select one of the rows which you have selected and choose Hide and Exclude:
jthi_4-1629128191293.png
and analysis to show how it affects the results:
jthi_5-1629128228283.png
-Jarmo