taste | R Documentation |
The taste example dataset used by Le Roux & Rouanet(2010):
The variables included in the dataset:
Preferred TV program |
(8 categories): news, comedy, police, nature, sport, films, drama, soap operas |
Preferred Film |
(8 categories): action, comedy, costume drama, documentary, horror, musical, romance, SciFi |
Preferred type of Art |
(7 categories): performance, landscape, renaissance, still life, portrait, modern, impressionsism |
Preferred place to Eat out |
(6 categories): fish & chips, pub, Indian restuarant, Italian restaurant, French restaurant, steak house |
Brigitte Le Roux
Le Roux, Brigitte, Henry Rouanet, Mike Savage, og Alan Warde. 2008. "Class and Cultural Division in the UK". Sociology 42(6):1049-1071.
Le Roux, B., og H. Rouanet. 2010. Multiple correspondence analysis. Thousand Oaks: Sage.
## Not run: # The taste example data(taste) data_taste <- taste[which(taste$Isup == 'Active'), ] active <- data.frame(data_taste$TV, data_taste$Film, data_taste$Art, data_taste$Eat) sup <- data.frame(data_taste$Gender, data_taste$Age, data_taste$Income) # Multiple Correspondence Analysis result.mca <- soc.mca(active, sup) str(result.mca) result.mca variance(result.mca) # See p.46 in Le Roux(2010) contribution(result.mca, 1) contribution(result.mca, 2) contribution(result.mca, 1:3, mode = "variable") map.active(result.mca, point.fill = result.mca$variable) map.active(result.mca, map.title="Map of active modalities with size of contribution to 1. dimension", point.size=result.mca$ctr.mod[, 1]) map.active(result.mca, map.title="Map of active modalities with size of contribution to 2. dimension", point.size=result.mca$ctr.mod[, 2]) map.ind(result.mca) map.ind(result.mca, dim=c(1, 2), point.color=result.mca$ctr.ind[, 1], point.shape=18) + scale_color_continuous(low="white", high="black") # Plot of all dublets map.ind(result.mca, map.title="Map of all unique individuals", point.color=duplicated(active)) map.ind(result.mca, map.title="Map with individuals colored by the TV variable", point.color=active$TV) # Ellipse map <- map.ind(result.mca) map.ellipse(result.mca, map, as.factor(data_taste$Age == '55-64')) ##### Specific Multiple Correspondence Analysis options(passive= c("Film: CostumeDrama", "TV: Tv-Sport")) result.smca <- soc.mca(active, sup) result.smca result.smca$names.passive ##### Class Specific Correspondence Analysis options(passive=NULL) class.age <- which(data_taste$Age == '55-64') result.csca <- soc.csa(result.mca, class.age, sup) str(result.csca) # Correlations csa.measures(result.csca) variance(result.csca) contribution(result.csca, 1) contribution(result.csca, 2) contribution(result.csca, 1:3, mode = "variable") # Plots map.ind(result.csca) map.csa.mca(result.csca) map.csa.mca.array(result.csca) ## End(Not run)
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