Description Usage Arguments Value Author(s) References See Also Examples

View source: R/functions_analysis.r

Specific Multiple Correspondence Analysis

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`active` |
Defines the active modalities in a data.frame with rows of individuals and columns of factors, without NA's'. Active can also be a named list of data.frames. The data.frames will correspond to the analytical headings. |

`sup` |
Defines the supplementary modalities in a data.frame with rows of individuals and columns of factors, without NA's |

`identifier` |
A single vector containing a single value for each row/individual in x and sup. Typically a name or an id.number. |

`passive` |
A single character vector with the full or partial names of the passive modalities. All names that have a full or partial match will be set as passive. |

`weight` |
a numeric vector with the weights for the individual rows. The weight is normalized afterwardsds. |

`Moschidis` |
If TRUE adjusts contribution values for rare modalities. see moschidis. |

`detailed.results` |
If FALSE the result object is trimmed to reduce its memory footprint. |

`nd` |
Number of active dimensions |

`n.ind` |
The number of active individuals |

`n.mod` |
The number of active modalities |

`eigen` |
Eigenvectors |

`total.inertia` |
The sum of inertia |

`adj.inertia` |
A matrix with all active dimensions, adjusted and unadjusted inertias. See variance |

`freq.mod` |
Frequencies for the active modalities. See add.to.label |

`freq.sup` |
Frequencies for the supplementary modalities. See add.to.label |

`ctr.mod` |
A matrix with the contribution values of the active modalities per dimension. See contribution |

`ctr.ind` |
A matrix with the contribution values of the individuals per dimension. |

`cor.mod` |
The correlation or quality of each modality per dimension. |

`cor.ind` |
The correlation or quality of each individual per dimension. |

`mass.mod` |
The mass of each modality |

`coord.mod` |
A matrix with the principal coordinates of each active modality per dimension. |

`coord.ind` |
A matrix with the principal coordinates of each individual per dimension. |

`coord.sup` |
A matrix with the principal coordinates of each supplementary modality per dimension. |

`names.mod` |
The names of the active modalities |

`names.ind` |
The names of the individuals |

`names.sup` |
The names of the supplementary modalities |

`names.passive` |
The names of the passive modalities |

`modal` |
A matrix with the number of modalities per variable and their location |

`variable` |
A character vector with the name of the variable of the active modalities |

`Rosenlund.tresh` |
A numeric vector with the contribution values adjusted with the Rosenlund threshold, see: see p 92 in: Rosenlund, Lennart. Exploring the City with Bourdieu: Applying Pierre Bourdieu’s Theories and Methods to Study the Community. Saarbrücken: VDM Verlag Dr. Müller, 2009. |

`t.test.sup` |
A matrix with a the student t-test of the coordinates of the supplementary variables |

`Share.of.var` |
A matrix the share of variance for each variable |

Anton Grau Larsen

Jacob Lunding

Stefan Bastholm Andrade

Christoph Ellersgaard

Le Roux, B., og H. Rouanet. 2010. Multiple correspondence analysis. Thousand Oaks: Sage.

soc.csa, contribution

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
# Loads the "taste" dataset included in this package
data(taste)
# Create a data frame of factors containing all the active variables
taste <- taste[which(taste$Isup == 'Active'), ]
attach(taste)
active <- data.frame(TV, Film, Art, Eat)
sup <- data.frame(Gender, Age, Income)
detach(taste)
# Runs the analysis
result <- soc.mca(active, sup)
# Prints the results
result
# A specific multiple correspondence analysis
# options defines what words or phrases that are looked for in the labels of the active modalities.
options(passive = c("Film: CostumeDrama", "TV: Tv-Sport"))
soc.mca(active, sup)
options(passive = NULL)
``` |

```
Loading required package: ggplot2
Specific Multiple Correspondence Analysis:
Statistics Scree plot
Active dimensions: 12 | 1. 47.6% ************************
Dimensions explaining 80% of inertia: 3 | 2. 21.5% ***********
Active modalities: 29 | 3. 11.8% ******
Supplementary modalities: 14 | 4. 7.1% ****
Individuals: 1215 | 5. 5.0% **
Share of passive mass: 0 | 6. 3.0% **
Number of passive modalities: 0 | 7. 1.7% *
The 4 active variables: [No. modalities - share of variance]
TV [8 - 28%] Film [8 - 28%] Art [7 - 24%]
Eat [6 - 20%]
Specific Multiple Correspondence Analysis:
Statistics Scree plot
Active dimensions: 11 | 1. 45.8% ***********************
Dimensions explaining 80% of inertia: 3 | 2. 27.9% **************
Active modalities: 27 | 3. 8.8% ****
Supplementary modalities: 14 | 4. 6.5% ***
Individuals: 1215 | 5. 4.2% **
Share of passive mass: 0.06 | 6. 3.4% **
Number of passive modalities: 2 | 7. 1.5% *
The 4 active variables: [No. modalities - share of variance]
TV [7 - 24%] Film [7 - 24%] Art [7 - 24%]
Eat [6 - 20%]
```

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