Multiple Taxicab Correspondence Analysis of a Survey Related to Health Services

We present an analysis of a health survey data by multiple correspondence analysis (MCA) and multiple taxicab correspondence analysis (MTCA), MTCA being a robust L1 variant of MCA. The survey has one passive item, gender, and 22 active substantive items representing health services offered by municipal authorities; each active item has four answer categories: this service is used, never tried, tried with no access, non response. We show that the rst principal MTCA factor is perfectly characterized by the sum score of the category this service is used over all service items. Further, we prove that such a sum score characterization always exists for any survey data.