Multiple Taxicab Correspondence Analysis of a Survey Related to Health Services

10.6339/JDS.2013.11(2).1113

Vartan Choulakian；Jacques Allard；Biagio Simonetti

First factor success ； multiple correspondence analysis ； multiple taxicab correspondence analysis ； non response ； outliers ； sum score

Journal of Data Science

11卷2期（2013 / 04 / 01）

205 - 229

英文

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 first 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.