health

<p>In 1989-1990 the Valencian Institute of Public Health (IVESP) conducted a survey to better know the attitudes and opinions related to health for the non-expert population. The first question included in the questionnaire "What does health mean to you?" required free and spontaneous answers. A priori, the variables Age group (under 21, 21-35, 36-50 and over 50), Health condition (poor, fair, good and very good health) and Gender were considered as possibly conditioning the respondents' viewpoint on health.</p>

datasets

Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).

Francois Husson

FactoMineR

Multivariate Exploratory Data Analysis and Data Mining

health function

<p>A data frame with 392 rows and 118 columns. Rows represent the individuals (respondents), columns represent the words used at least 10 times to answer the open-ended question (columns 1 to 115) and respondents' characteristics (age, health condition and gender)</p>

health: health (data)

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