Input Formats in Correspondence Analysis - Frequencies with Grouping Variables
If the
Frequencies with grouping variables option button is selected [from the
Input group box on either the
Correspondence Analysis (CA): Table Specifications - Correspondence Analysis (CA) Multiple Correspondence Analysis (MCA): Table Specifications - Multiple Correspondence Analysis (MCA)
STAFFGRP | SMOKING | FREQUENCY |
Sr.Manag | None | 4 |
Sr.Manag | Light | 2 |
Sr.Manag | Medium | 3 |
Sr.Manag | Heavy | 2 |
Jr.Manag | None | 4 |
Jr.Manag | Light | 3 |
Jr.Manag | Medium | 7 |
Jr.Manag | Heavy | 4 |
Sr.Empl | None | 25 |
Sr.Empl | Light | 10 |
Sr.Empl | Medium | 12 |
....... | ....... | ....... |
....... | ....... | ....... |
....... | ....... | ....... |
If you selected variables StaffGrp and Smoking for the analysis, and variable Frequency as the Variable with frequencies/counts, then Statistica would assign the respective value for variable Frequency to each cell in the table identified by the grouping variables.
Raw data (requires tabulation)
, except that in addition, you will be prompted to select the Variable with frequencies/counts (that is, the variable containing the measure of correspondence, similarity, confusion, association). Note that only positive values or zero are allowed in that variable (example, Statistica does not permit negative frequencies).GENDER | INCOME | FREQUENCY |
MALE | HIGH | 4 |
MALE | HIGH | 6 |
MALE | LOW | 3 |
FEMALE | HIGH | 2 |
FEMALE | LOW | 4 |
There are two references to the cell Male-High (that is, the first two cases in the listing above). Thus, the frequency assigned to that cell will be 4+6=10. This way of handling multiple references enables you to analyze subsets of tables that are coded in this manner. For example, suppose you had three grouping variables Gender, Income, and Occupation, and a fourth variable containing the frequencies for each cell in the three-way table. If you now only selected Gender and Income for the analysis, then Statistica would sum up all the frequencies in the two-way table defined by those two variables, and, in effect, compute the Gender by Income marginal frequency table, collapsing across the levels of the variable Occupation.