Note : ce billet est encore très incomplet.

Introduction

Extensions

De nombreuses extensions existent permettant de faire ce type d'analyses :

http://cran.r-project.org/web/views/Multivariate.html

On se basera ici sur deux extensions, ade4 et FactoMineR :

http://cran.r-project.org/web/packages/ade4/

http://cran.r-project.org/web/packages/FactoMineR/

library(ade4)
library(FactoMineR)

Données d'exemple

On se base sur l'extrait de l'enquête Histoire de vie de 2003 présent dans l'extension rgrs :

library(rgrs)
data(hdv2003)

On ne conserve que 200 individus de cet échantillon :

tmp <- hdv2003[1:200, ]

Et on se base sur une sélection de variables :

acm.vars <- c("sexe", "qualif", "peche.chasse", "cinema", "cuisine", "bricol", "sport", "lecture.bd")
tmp <- tmp[,acm.vars]

FactoMineR

Fonction de calcul de l'ACM

L'ACM sous FactoMineR se fait à l'aide de la fonction MCA. Son résultat est stocké dans un objet. On peut modifier son comportement avec notamment les paramètres suivants :

  • ncp : nombre d'axes retenus pour l'analyse (5 par défaut)
  • ind.sup : vecteur indiquant les indices (numéros de lignes) des individus supplémentaires éventuels
  • quali.sup : vecteur indiquant les indices (numéros de colonnes) des variables qualitatives supplémentaires
  • quanti.sup vecteur indiquant les indices (numéros de colonnes) des variables quantitatives supplémentaires
  • graph : sortir les graphiques ou non après le calcul

À noter que par défaut FactoMineR transforme les valeurs manquantes dans les variables actives de l'analyse en modalité de la question et les intègre de cette manière à l'analyse. Si on préfère supprimer les individus avec des valeurs manquantes on pourra regarder du côté des fonctions comme complete.cases.

On lance notre ACM :

acm <- MCA(tmp, ncp=4, graph=FALSE)

Histogramme des valeurs propres

FactoMineR ne propose pas de fonctions par défaut pour afficher l'histogramme des valeurs propres. Celles ci sont cependant accessibles via l'élément eig de notre objet acm :

acm$eig[1:10,]
       eigenvalue percentage of variance cumulative percentage of variance
dim 1  0.24064833              13.751333                          13.75133
dim 2  0.20302291              11.601309                          25.35264
dim 3  0.14849774               8.485585                          33.83823
dim 4  0.14029774               8.017014                          41.85524
dim 5  0.13299501               7.599715                          49.45496
dim 6  0.13108757               7.490718                          56.94567
dim 7  0.12584342               7.191053                          64.13673
dim 8  0.12100013               6.914293                          71.05102
dim 9  0.11555042               6.602881                          77.65390
dim 10 0.09775625               5.586072                          83.23997

Ce qu'on peut représenter graphiquement avec :

barplot(acm$eig[1:10,2], main="Histogramme des valeurs propres", names.arg=1:10, xlab="Axe", ylab="Pourcentage d'inertie")

http://alea.fr.eu.org/public/_____________fmeig.png

Coordonnées, contributions

L'objet acm a plusieurs composantes :

names(acm)

eig contient les valeurs propres, var les résultats pour les variables et ind ceux pour les individus. En cas de variables ou individus supllémentaires on a accès à des composantes spécifiques.

Les composantes acm$ind permettent d'accéder aux coordonnées, contributions et cosinus carrés des points correspondants.

acm$ind$coord[1:10,]
acm$var$coord

Les contributions sont données en pourcentages :

acm$var$contrib
acm$var$cos2
                               Dim 1        Dim 2        Dim 3        Dim 4
Femme                    0.562084763 8.731623e-02 2.549378e-02 4.975723e-02
Homme                    0.562084763 8.731623e-02 2.549378e-02 4.975723e-02
Autre                    0.003565469 2.535408e-03 9.670893e-05 1.097874e-01
Cadre                    0.021231777 1.704401e-01 3.885158e-03 4.514553e-02
Employe                  0.189135685 4.477839e-02 6.163631e-03 8.878987e-02
NA                       0.024676713 4.720070e-02 6.350154e-03 1.794810e-01
Ouvrier qualifie         0.364856132 1.619262e-06 1.811601e-01 2.146114e-05
Ouvrier specialise       0.009486554 1.009109e-01 3.647396e-04 1.461048e-03
Profession intermediaire 0.023907733 4.140109e-02 1.783537e-01 1.916305e-01
Technicien               0.002395952 1.221449e-01 4.562204e-02 2.626386e-01
peche.chasse_Non         0.235203699 1.201679e-03 1.827258e-02 2.534052e-01
peche.chasse_Oui         0.235203699 1.201679e-03 1.827258e-02 2.534052e-01
cinema_Non               0.210751330 3.988954e-01 1.193201e-02 2.506972e-02
cinema_Oui               0.210751330 3.988954e-01 1.193201e-02 2.506972e-02
cuisine_Non              0.133987106 1.169398e-03 5.056254e-01 2.799071e-03
cuisine_Oui              0.133987106 1.169398e-03 5.056254e-01 2.799071e-03
bricol_Non               0.107955362 2.265766e-01 2.409109e-01 7.145517e-04
bricol_Oui               0.107955362 2.265766e-01 2.409109e-01 7.145517e-04
sport_Non                0.098841576 4.280178e-01 1.088438e-02 2.253741e-03
sport_Oui                0.098841576 4.280178e-01 1.088438e-02 2.253741e-03
lecture.bd_Non           0.065157036 1.070206e-02 2.694088e-04 1.713235e-03
lecture.bd_Oui           0.065157036 1.070206e-02 2.694088e-04 1.713235e-03

Description des axes

FactoMineR fournit une fonction supplémentaire nommée dimdesc permettant de décrire les axes de l'analyse. On lui fournit en paramètres les axes dont on souhaite obtenir la description et éventuellement un seuil de significativité statistique en-dessous duquel on n'affiche pas les informations.

dimdesc(acm, axes=1)

Pour chaque axe, dimdesc nous donne d'abord des informations sur les variables (composante quali), puis sur les modalités (composante category).

$`Dim 1`
$`Dim 1`$quali
                     R2      p.value
sexe         0.56208476 2.366454e-37
qualif       0.51120576 7.798484e-27
peche.chasse 0.23520370 3.400728e-13
cinema       0.21075133 8.082765e-12
cuisine      0.13398711 9.803483e-08
bricol       0.10795536 2.033807e-06
sport        0.09884158 5.793702e-06
lecture.bd   0.06515704 2.643983e-04

$`Dim 1`$category
                           Estimate      p.value
Homme                     0.3684474 2.366454e-37
Ouvrier qualifie          0.5511168 1.431730e-16
peche.chasse_Oui          0.3728747 3.400728e-13
cinema_Non                0.2303405 8.082765e-12
cuisine_Non               0.1832683 9.803483e-08
bricol_Oui                0.1625604 2.033807e-06
sport_Non                 0.1667347 5.793702e-06
lecture.bd_Non            0.4010235 2.643983e-04
Profession intermediaire  0.2079741 2.715577e-02
lecture.bd_Oui           -0.4010235 2.643983e-04
Cadre                    -0.2694140 6.479938e-05
NA                       -0.2440068 3.453776e-05
sport_Oui                -0.1667347 5.793702e-06
bricol_Non               -0.1625604 2.033807e-06
cuisine_Oui              -0.1832683 9.803483e-08
cinema_Oui               -0.2303405 8.082765e-12
peche.chasse_Non         -0.3728747 3.400728e-13
Employe                  -0.4301683 1.728942e-14
Femme                    -0.3684474 2.366454e-37
dimdesc(acm,axes=1)
acm$ind$coord
tableau = cbind.data.frame(acm$ind$coord[,1], acm$call$X)
tableau
options(contrasts = c("contr.sum", "contr.sum"))

## Analyse de variance sur les coordonnées par la variable
res.aov <- aov(acm$ind$coord[,1] ~ tmp$sexe, na.action = na.exclude)
res <- summary(res.aov)[[1]]
## Variance de la variable sur variance totale : R2
res[1,2]/(res[1,2] + res[2,2])
## Test F à partir de la F-Value de la variable, du ddl de la variable et du ddl total
## Teste si cette part de variance est différente de 0 (?)
pf(res[1,4], res[1,1], res[dim(res)[1],1], lower.tail=FALSE)


acm$var$v.test
dimdesc(acm, axes=1)

summary.aov(res.aov)
summary.lm(res.aov)
options(contrasts = c("contr.sum", "contr.poly"))
lm(acm$ind$coord[,1] ~ tmp$sexe)
tmp$qualif <- as.character(tmp$qualif)
tmp$qualif[is.na(tmp$qualif)] <- "NA"
tmp$qualif <- factor(tmp$qualif)
lm(acm$ind$coord[,1] ~ tmp$qualif, na.action = na.exclude)$coef
acm$var$v.test



condes(tableau, 1, proba=0.05)
$`Dim 1`
$`Dim 1`$quali
                     R2      p.value
sexe         0.56208476 2.366454e-37
qualif       0.51120576 7.798484e-27
peche.chasse 0.23520370 3.400728e-13
cinema       0.21075133 8.082765e-12
cuisine      0.13398711 9.803483e-08
bricol       0.10795536 2.033807e-06
sport        0.09884158 5.793702e-06
lecture.bd   0.06515704 2.643983e-04

$`Dim 1`$category
                           Estimate      p.value
Homme                     0.3684474 2.366454e-37
Ouvrier qualifie          0.5511168 1.431730e-16
peche.chasse_Oui          0.3728747 3.400728e-13
cinema_Non                0.2303405 8.082765e-12
cuisine_Non               0.1832683 9.803483e-08
bricol_Oui                0.1625604 2.033807e-06
sport_Non                 0.1667347 5.793702e-06
lecture.bd_Non            0.4010235 2.643983e-04
Profession intermediaire  0.2079741 2.715577e-02
lecture.bd_Oui           -0.4010235 2.643983e-04
Cadre                    -0.2694140 6.479938e-05
qualif.NA                -0.2440068 3.453776e-05
sport_Oui                -0.1667347 5.793702e-06
bricol_Non               -0.1625604 2.033807e-06
cuisine_Oui              -0.1832683 9.803483e-08
cinema_Oui               -0.2303405 8.082765e-12
peche.chasse_Non         -0.3728747 3.400728e-13
Employe                  -0.4301683 1.728942e-14
Femme                    -0.3684474 2.366454e-37
           Dim 1        Dim 2        Dim 3        Dim 4
1   -0.429034515 -0.559766342 -0.222896681 -0.123388328
2   -0.554452142  0.184739548  0.338477717  0.202663745
3    0.217353048  0.660574875  0.712833598  1.153983115
4   -0.043451213  1.265993202 -0.006659810  1.099928010
5   -0.238644368 -0.540401537  0.247927674 -0.159428431
6   -0.651150015  0.210447970  0.247237502 -0.233262266
7    0.468039319 -0.435872416 -0.619776055 -0.495828290
8    1.019682202 -0.005260798 -0.837155161 -0.328683173
9   -0.381238128 -0.207691189  0.411649975  0.168408168
10  -0.018322069  0.536111192  0.406973591  0.615104314
11  -0.499448628  0.065016790 -0.471565733 -0.213483536
12   0.649493579  0.376390035 -0.302057879  0.196121461
13  -0.429034515 -0.559766342 -0.222896681 -0.123388328
14  -0.163459122 -0.319110402 -0.452807607  0.330531887
15  -0.571628276 -0.227055995 -0.059174380  0.204448271
16  -0.477936001 -0.181982767  0.320409761 -0.267517843
17  -0.206396641  0.998540370 -0.350517629 -0.048313780
18  -0.575964769  0.431739105 -0.453497778  0.256698052
19   0.413773434 -0.617409500  0.415532104  0.098848411
20  -0.141440938  0.304197187 -0.012196685 -0.079113068
21  -0.260156995 -0.293401979 -0.544047821 -0.105394124
22   0.144120995 -0.376154281  0.351699707 -0.010277518
23  -0.841540163  0.191083165 -0.223586853 -0.197222163
24  -0.141946494 -0.566109959  0.339167888  0.276497580
25  -0.571887724 -0.050172054 -0.159754456 -0.088096234
26   0.614986391  0.030836015  0.304702851 -0.555103412
27   0.080674562 -0.466017125 -0.482330869  0.030760869
28   0.801138191 -0.587264791  0.278086918 -0.427740749
29   0.822707593 -0.016040702 -0.228885620  0.161865884
30   0.607176555  0.745588709 -0.837845333 -0.402517009
31   0.312998516 -0.109789919  0.030548568  0.007716686
32   0.133379318  0.390680011 -0.311829645  0.634883044
33   0.797061146 -0.105353632 -0.015656404 -0.082946463
34  -0.366178638 -0.605050083  0.006217867  0.550163648
35  -0.162953565  0.551196744 -0.804172180 -0.025078761
36  -0.477936001 -0.181982767  0.320409761 -0.267517843
37   0.649493579  0.376390035 -0.302057879  0.196121461
38  -0.554452142  0.184739548  0.338477717  0.202663745
39  -0.238644368 -0.540401537  0.247927674 -0.159428431
40   0.396499154  0.267055668  0.120996897 -0.010520048
41  -0.090571244 -0.151838058  0.182964575 -0.794107003
42   0.653830072 -0.282405064  0.092265520  0.143871679
43   0.032894992  0.640121600 -0.422999716  0.059775632
44  -0.328357743  0.228874787  0.265203745 -0.143409588
45  -0.141946494 -0.566109959  0.339167888  0.276497580
46   0.822707593 -0.016040702 -0.228885620  0.161865884
47   0.227982681 -0.770876852 -0.296509471 -0.540851558
48  -0.332336642 -0.585474764 -0.131656467  0.312537683
49  -0.238644368 -0.540401537  0.247927674 -0.159428431
50  -0.155143729 -0.163555950  0.338376003 -0.177665165
51   0.405177308  0.565036531  0.685592207 -0.521102976
52  -0.429034515 -0.559766342 -0.222896681 -0.123388328
53   0.394183579 -0.214738315  0.407663762  0.688938149
54  -0.141946494 -0.566109959  0.339167888  0.276497580
55  -0.021938586  1.018993644  0.785315685  1.045893702
56  -0.159382076 -0.801021561 -0.159064284 -0.014262399
57  -0.141946494 -0.566109959  0.339167888  0.276497580
58  -0.398771856  0.853657920  0.016534693 -0.233504795
59  -0.095170639 -0.017735512  0.424181795 -0.118366931
60  -0.332336642 -0.585474764 -0.131656467  0.312537683
61  -0.433371009  0.099028758 -0.617220079 -0.071138546
62  -0.122785294 -0.028796771 -0.101056692  0.495944172
63   0.822707593 -0.016040702 -0.228885620  0.161865884
64   0.219306241 -0.154863146 -0.349035573  0.479682800
65   0.653830072 -0.282405064  0.092265520  0.143871679
66  -0.841540163  0.191083165 -0.223586853 -0.197222163
67   0.632317445 -0.035405507 -0.699709975  0.197905986
68   1.210072350  0.014104007 -0.366330806 -0.364723276
69  -0.094907737  0.506957042 -0.211358823 -0.741857221
70  -0.571628276 -0.227055995 -0.059174380  0.204448271
71   0.224148291  0.056648900 -0.306076748  0.071822370
72   0.582650955 -0.351045138  0.094380965  0.116842616
73  -0.433371009  0.099028758 -0.617220079 -0.071138546
74  -0.477936001 -0.181982767  0.320409761 -0.267517843
75  -0.499448628  0.065016790 -0.471565733 -0.213483536
76   0.080674562 -0.466017125 -0.482330869  0.030760869
77   0.822707593 -0.016040702 -0.228885620  0.161865884
78  -0.141946494 -0.566109959  0.339167888  0.276497580
79  -0.672662643  0.457447528 -0.544737992 -0.179227959
80  -0.628967966 -0.125149401  0.124601136  0.274877426
81  -1.084933508 -0.385170146 -0.116312294 -0.143002687
82  -0.260156995 -0.293401979 -0.544047821 -0.105394124
83   0.271064710 -0.446652320 -0.011506514 -0.005279233
84   0.223285140  0.659486405  0.047824639  0.023735529
85  -0.193199407  0.595986361 -0.349725745  0.405848965
86  -0.584825510  0.175498014 -0.059966264 -0.249714474
87   0.822707593 -0.016040702 -0.228885620  0.161865884
88   0.783863912  0.297200377 -0.016448289 -0.537109207
89   0.454078794  0.187252956  0.142285765 -0.376973461
90   0.396499154  0.267055668  0.120996897 -0.010520048
91  -0.011670000  0.359110075  0.514630124 -0.136603664
92  -0.567649377  0.587293557  0.337685832 -0.251499000
93   0.632317445 -0.035405507 -0.699709975  0.197905986
94  -0.744842290  0.165374743 -0.132346639  0.238703848
95  -0.163459122 -0.319110402 -0.452807607  0.330531887
96  -0.238644368 -0.540401537  0.247927674 -0.159428431
97   0.970780717  0.372522777 -0.293848719 -0.472812688
98   0.287857625  0.671204297 -0.107586790 -0.592706309
99  -0.159382076 -0.801021561 -0.159064284 -0.014262399
100 -0.499448628  0.065016790 -0.471565733 -0.213483536
101 -0.155143729 -0.163555950  0.338376003 -0.177665165
102  0.046092227  0.237567591 -0.422207832  0.513938377
103 -0.225557842  0.461227182  0.089706951 -0.267760372
104  0.343359321  0.007373632  0.166863052  0.008753204
105  0.231963294  0.957467268  0.612419948 -0.486847399
106 -0.159382076 -0.801021561 -0.159064284 -0.014262399
107 -0.315160509 -0.173679221  0.265995629  0.310753157
108 -0.238644368 -0.540401537  0.247927674 -0.159428431
109 -1.174646883  0.384106178 -0.099036223 -0.126983844
110  0.649493579  0.376390035 -0.302057879  0.196121461
111  0.001527235 -0.043443934  0.515422009  0.317559080
112  0.139784501  0.282640819 -0.042623691  0.041972263
113 -0.011670000  0.359110075  0.514630124 -0.136603664
114  0.559444582  0.534508500  0.464854717  1.137721742
115 -0.319679589  0.526855650  0.829799054 -0.653992516
116  0.437793478 -0.391082800 -0.165329620 -0.064900565
117  0.312998516 -0.109789919  0.030548568  0.007716686
118  0.289800668 -0.213213953  0.222219684 -1.070707738
119  0.394183579 -0.214738315  0.407663762  0.688938149
120  1.210072350  0.014104007 -0.366330806 -0.364723276
121 -0.150802068  0.793220013  0.508647915 -0.635998311
122 -0.477936001 -0.181982767  0.320409761 -0.267517843
123 -0.146465575  0.134424913  0.902971313 -0.688248093
124  0.240818868 -0.401862703  0.442939922  0.425648493
125 -0.841540163  0.191083165 -0.223586853 -0.197222163
126  0.031008071 -0.781656756  0.311760071 -0.050302501
127  0.531485752 -0.346009572  0.214254521 -0.536866678
128 -0.584825510  0.175498014 -0.059966264 -0.249714474
129 -0.238644368 -0.540401537  0.247927674 -0.159428431
130  0.240818868 -0.401862703  0.442939922  0.425648493
131 -0.238644368 -0.540401537  0.247927674 -0.159428431
132 -0.184884014  0.751540813  0.441457866 -0.102348087
133 -0.141946494 -0.566109959  0.339167888  0.276497580
134 -0.212360607  0.058673173  0.090498836  0.186402373
135 -0.655251726 -0.724224111  0.282029974 -0.070953378
136  0.067604854 -0.009431966  0.369767663  0.459904070
137  0.001527235 -0.043443934  0.515422009  0.317559080
138  0.475591421 -0.059746602  0.934261259 -0.431007768
139  1.036858336  0.406534745 -0.439503065 -0.330467699
140  0.320152949  0.892927269  0.537336804  1.029632330
141  0.632317445 -0.035405507 -0.699709975  0.197905986
142  0.649493579  0.376390035 -0.302057879  0.196121461
143  0.323769466  0.410044817  0.158994710  0.598842941
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145  0.063085773  0.691102905  0.933571088 -0.504841603
146  0.582650955 -0.351045138  0.094380965  0.116842616
147 -0.212328734  0.999628839  0.314491330  1.081933805
148 -0.010094411 -0.131986014 -0.488083766  0.593821544
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158  0.792542066  0.595181240  0.548147021 -1.047692136
159  0.144120995 -0.376154281  0.351699707 -0.010277518
160  1.019682202 -0.005260798 -0.837155161 -0.328683173
161 -0.584825510  0.175498014 -0.059966264 -0.249714474
162  0.067604854 -0.009431966  0.369767663  0.459904070
163 -0.415947990  0.441862377 -0.381117404 -0.231720270
164  0.862956179 -0.029601892  0.796816073 -0.957596928
165 -0.602248530 -0.167335605 -0.296068940 -0.089132751
166 -0.029093019  0.016276456  0.278527449  0.023978059
167  0.653830072 -0.282405064  0.092265520  0.143871679
168 -0.575964769  0.431739105 -0.453497778  0.256698052
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170 -0.238644368 -0.540401537  0.247927674 -0.159428431
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172 -0.482272495  0.476812333 -0.073913637 -0.215268061
173  0.219306241 -0.154863146 -0.349035573  0.479682800
174 -0.672662643  0.457447528 -0.544737992 -0.179227959
175 -0.429034515 -0.559766342 -0.222896681 -0.123388328
176 -0.589162004  0.834293114 -0.454289663 -0.197464693
177 -0.122785294 -0.028796771 -0.101056692  0.495944172
178  0.822707593 -0.016040702 -0.228885620  0.161865884
179  0.582650955 -0.351045138  0.094380965  0.116842616
180 -0.758039525  0.567928752 -0.133138523 -0.215458897
181  0.653830072 -0.282405064  0.092265520  0.143871679
182  0.249552082 -0.199652763 -0.803482009  0.048755074
183 -0.672662643  0.457447528 -0.544737992 -0.179227959
184  0.409696389 -0.135498341  0.121788782  0.443642697
185  0.653830072 -0.282405064  0.092265520  0.143871679
186 -0.010094411 -0.131986014 -0.488083766  0.593821544
187 -0.225557842  0.461227182  0.089706951 -0.267760372
188 -0.238644368 -0.540401537  0.247927674 -0.159428431
189 -0.260156995 -0.293401979 -0.544047821 -0.105394124
190 -0.482272495  0.476812333 -0.073913637 -0.215268061
191  0.644468942  0.206617761  0.613110120 -0.413013564
192  0.850804682 -0.271625161 -0.516004022 -0.346677378
193 -0.332336642 -0.585474764 -0.131656467  0.312537683
194 -0.016006494  1.017905175  0.120306726 -0.084353883
195  0.822707593 -0.016040702 -0.228885620  0.161865884
196 -0.381238128 -0.207691189  0.411649975  0.168408168
197 -0.184884014  0.751540813  0.441457866 -0.102348087
198 -0.589162004  0.834293114 -0.454289663 -0.197464693
199  0.544572278  0.655619147  0.056033799 -0.645198620
200 -0.238644368 -0.540401537  0.247927674 -0.159428431
R>     acm$ind$coord[, 1]  sexe                   qualif     peche.chasse
1         -0.429034515 Femme                  Employe peche.chasse_Non
2         -0.554452142 Femme                qualif.NA peche.chasse_Non
3          0.217353048 Homme               Technicien peche.chasse_Non
4         -0.043451213 Homme               Technicien peche.chasse_Non
5         -0.238644368 Femme                  Employe peche.chasse_Non
6         -0.651150015 Femme                  Employe peche.chasse_Non
7          0.468039319 Femme         Ouvrier qualifie peche.chasse_Oui
8          1.019682202 Homme         Ouvrier qualifie peche.chasse_Oui
9         -0.381238128 Femme                qualif.NA peche.chasse_Non
10        -0.018322069 Homme                    Autre peche.chasse_Non
11        -0.499448628 Femme                  Employe peche.chasse_Non
12         0.649493579 Homme         Ouvrier qualifie peche.chasse_Non
13        -0.429034515 Femme                  Employe peche.chasse_Non
14        -0.163459122 Femme                qualif.NA peche.chasse_Non
15        -0.571628276 Femme                qualif.NA peche.chasse_Non
16        -0.477936001 Femme                  Employe peche.chasse_Non
17        -0.206396641 Homme                    Cadre peche.chasse_Non
18        -0.575964769 Femme                qualif.NA peche.chasse_Non
19         0.413773434 Homme       Ouvrier specialise peche.chasse_Non
20        -0.141440938 Femme         Ouvrier qualifie peche.chasse_Non
21        -0.260156995 Femme                  Employe peche.chasse_Non
22         0.144120995 Homme                  Employe peche.chasse_Non
23        -0.841540163 Femme                  Employe peche.chasse_Non
24        -0.141946494 Femme                qualif.NA peche.chasse_Non
25        -0.571887724 Femme       Ouvrier specialise peche.chasse_Non
26         0.614986391 Homme                    Cadre peche.chasse_Oui
27         0.080674562 Femme         Ouvrier qualifie peche.chasse_Non
28         0.801138191 Homme       Ouvrier specialise peche.chasse_Oui
29         0.822707593 Homme         Ouvrier qualifie peche.chasse_Non
30         0.607176555 Homme         Ouvrier qualifie peche.chasse_Oui
31         0.312998516 Homme                  Employe peche.chasse_Non
32         0.133379318 Homme                    Autre peche.chasse_Non
33         0.797061146 Homme                qualif.NA peche.chasse_Oui
34        -0.366178638 Homme                qualif.NA peche.chasse_Non
35        -0.162953565 Femme         Ouvrier qualifie peche.chasse_Non
36        -0.477936001 Femme                  Employe peche.chasse_Non
37         0.649493579 Homme         Ouvrier qualifie peche.chasse_Non
38        -0.554452142 Femme                qualif.NA peche.chasse_Non
39        -0.238644368 Femme                  Employe peche.chasse_Non
40         0.396499154 Homme                    Cadre peche.chasse_Non
41        -0.090571244 Femme                  Employe peche.chasse_Oui
42         0.653830072 Homme         Ouvrier qualifie peche.chasse_Non
43         0.032894992 Homme                    Cadre peche.chasse_Non
44        -0.328357743 Femme                    Cadre peche.chasse_Non
45        -0.141946494 Femme                qualif.NA peche.chasse_Non
46         0.822707593 Homme         Ouvrier qualifie peche.chasse_Non
47         0.227982681 Femme       Ouvrier specialise peche.chasse_Oui
48        -0.332336642 Femme                qualif.NA peche.chasse_Non
49        -0.238644368 Femme                  Employe peche.chasse_Non
50        -0.155143729 Femme                    Cadre peche.chasse_Non
51         0.405177308 Homme Profession intermediaire peche.chasse_Non
52        -0.429034515 Femme                  Employe peche.chasse_Non
53         0.394183579 Homme                    Autre peche.chasse_Non
54        -0.141946494 Femme                qualif.NA peche.chasse_Non
55        -0.021938586 Homme               Technicien peche.chasse_Non
56        -0.159382076 Femme       Ouvrier specialise peche.chasse_Non
57        -0.141946494 Femme                qualif.NA peche.chasse_Non
58        -0.398771856 Femme                    Cadre peche.chasse_Non
59        -0.095170639 Homme                  Employe peche.chasse_Non
60        -0.332336642 Femme                qualif.NA peche.chasse_Non
61        -0.433371009 Femme                  Employe peche.chasse_Non
62        -0.122785294 Homme                qualif.NA peche.chasse_Non
63         0.822707593 Homme         Ouvrier qualifie peche.chasse_Non
64         0.219306241 Homme                qualif.NA peche.chasse_Non
65         0.653830072 Homme         Ouvrier qualifie peche.chasse_Non
66        -0.841540163 Femme                  Employe peche.chasse_Non
67         0.632317445 Homme         Ouvrier qualifie peche.chasse_Non
68         1.210072350 Homme         Ouvrier qualifie peche.chasse_Oui
69        -0.094907737 Femme                  Employe peche.chasse_Oui
70        -0.571628276 Femme                qualif.NA peche.chasse_Non
71         0.224148291 Homme         Ouvrier qualifie peche.chasse_Non
72         0.582650955 Homme       Ouvrier specialise peche.chasse_Non
73        -0.433371009 Femme                  Employe peche.chasse_Non
74        -0.477936001 Femme                  Employe peche.chasse_Non
75        -0.499448628 Femme                  Employe peche.chasse_Non
76         0.080674562 Femme         Ouvrier qualifie peche.chasse_Non
77         0.822707593 Homme         Ouvrier qualifie peche.chasse_Non
78        -0.141946494 Femme                qualif.NA peche.chasse_Non
79        -0.672662643 Femme                  Employe peche.chasse_Non
80        -0.628967966 Femme                qualif.NA peche.chasse_Non
81        -1.084933508 Femme                  Employe peche.chasse_Non
82        -0.260156995 Femme                  Employe peche.chasse_Non
83         0.271064710 Femme         Ouvrier qualifie peche.chasse_Non
84         0.223285140 Homme                    Cadre peche.chasse_Non
85        -0.193199407 Homme                qualif.NA peche.chasse_Non
86        -0.584825510 Femme                    Cadre peche.chasse_Non
87         0.822707593 Homme         Ouvrier qualifie peche.chasse_Non
88         0.783863912 Homme                    Cadre peche.chasse_Oui
89         0.454078794 Homme Profession intermediaire peche.chasse_Non
90         0.396499154 Homme                    Cadre peche.chasse_Non
91        -0.011670000 Homme                    Cadre peche.chasse_Non
92        -0.567649377 Femme                    Cadre peche.chasse_Non
93         0.632317445 Homme         Ouvrier qualifie peche.chasse_Non
94        -0.744842290 Femme                qualif.NA peche.chasse_Non
95        -0.163459122 Femme                qualif.NA peche.chasse_Non
96        -0.238644368 Femme                  Employe peche.chasse_Non
97         0.970780717 Homme         Ouvrier qualifie peche.chasse_Oui
98         0.287857625 Homme                  Employe peche.chasse_Oui
99        -0.159382076 Femme       Ouvrier specialise peche.chasse_Non
100       -0.499448628 Femme                  Employe peche.chasse_Non
101       -0.155143729 Femme                    Cadre peche.chasse_Non
102        0.046092227 Homme                qualif.NA peche.chasse_Non
103       -0.225557842 Femme                    Cadre peche.chasse_Non
104        0.343359321 Homme       Ouvrier specialise peche.chasse_Non
105        0.231963294 Homme Profession intermediaire peche.chasse_Non
106       -0.159382076 Femme       Ouvrier specialise peche.chasse_Non
107       -0.315160509 Femme                qualif.NA peche.chasse_Non
108       -0.238644368 Femme                  Employe peche.chasse_Non
109       -1.174646883 Femme                    Cadre peche.chasse_Non
110        0.649493579 Homme         Ouvrier qualifie peche.chasse_Non
111        0.001527235 Homme                qualif.NA peche.chasse_Non
        cinema     cuisine     bricol     sport     lecture.bd
1   cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
2   cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
3   cinema_Non cuisine_Non bricol_Non sport_Oui lecture.bd_Non
4   cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
5   cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
6   cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
7   cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
8   cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
9   cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
10  cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
11  cinema_Oui cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
12  cinema_Non cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
13  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
14  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
15  cinema_Oui cuisine_Oui bricol_Non sport_Non lecture.bd_Non
16  cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
17  cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
18  cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
19  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
20  cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
21  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
22  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
23  cinema_Oui cuisine_Oui bricol_Non sport_Oui lecture.bd_Non
24  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
25  cinema_Oui cuisine_Oui bricol_Non sport_Oui lecture.bd_Non
26  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
27  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
28  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
29  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
30  cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
31  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
32  cinema_Oui cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
33  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
34  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Oui
35  cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
36  cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
37  cinema_Non cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
38  cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
39  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
40  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
41  cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
42  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
43  cinema_Non cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
44  cinema_Non cuisine_Non bricol_Non sport_Oui lecture.bd_Non
45  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
46  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
47  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
48  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
49  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
50  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
51  cinema_Oui cuisine_Non bricol_Oui sport_Non lecture.bd_Non
52  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
53  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
54  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
55  cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
56  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
57  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
58  cinema_Oui cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
59  cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
60  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
61  cinema_Non cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
62  cinema_Non cuisine_Oui bricol_Non sport_Oui lecture.bd_Non
63  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
64  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
65  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
66  cinema_Oui cuisine_Oui bricol_Non sport_Oui lecture.bd_Non
67  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
68  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
69  cinema_Oui cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
70  cinema_Oui cuisine_Oui bricol_Non sport_Non lecture.bd_Non
71  cinema_Oui cuisine_Oui bricol_Non sport_Non lecture.bd_Non
72  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
73  cinema_Non cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
74  cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
75  cinema_Oui cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
76  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
77  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
78  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
79  cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
80  cinema_Oui cuisine_Non bricol_Oui sport_Non lecture.bd_Oui
81  cinema_Oui cuisine_Oui bricol_Non sport_Non lecture.bd_Oui
82  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
83  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
84  cinema_Non cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
85  cinema_Oui cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
86  cinema_Oui cuisine_Oui bricol_Non sport_Non lecture.bd_Non
87  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
88  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
89  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
90  cinema_Non cuisine_Non bricol_Oui sport_Non lecture.bd_Non
91  cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
92  cinema_Oui cuisine_Non bricol_Non sport_Oui lecture.bd_Non
93  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
94  cinema_Oui cuisine_Oui bricol_Non sport_Oui lecture.bd_Non
95  cinema_Non cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
96  cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
97  cinema_Oui cuisine_Non bricol_Oui sport_Non lecture.bd_Non
98  cinema_Oui cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
99  cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
100 cinema_Oui cuisine_Oui bricol_Oui sport_Non lecture.bd_Non
101 cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
102 cinema_Non cuisine_Oui bricol_Oui sport_Oui lecture.bd_Non
103 cinema_Oui cuisine_Non bricol_Oui sport_Non lecture.bd_Non
104 cinema_Oui cuisine_Non bricol_Oui sport_Non lecture.bd_Non
105 cinema_Oui cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
106 cinema_Non cuisine_Oui bricol_Non sport_Non lecture.bd_Non
107 cinema_Non cuisine_Non bricol_Non sport_Oui lecture.bd_Non
108 cinema_Non cuisine_Non bricol_Non sport_Non lecture.bd_Non
109 cinema_Oui cuisine_Oui bricol_Non sport_Oui lecture.bd_Oui
110 cinema_Non cuisine_Non bricol_Oui sport_Oui lecture.bd_Non
111 cinema_Oui cuisine_Non bricol_Non sport_Non lecture.bd_Non
 [getOption("max.print") est atteint -- 89 lignes omises ]]
R> R> R> R> R> R> [1] 0.5620848
R> R> [1] 2.366454e-37
R> R>                               Dim 1       Dim 2       Dim 3       Dim 4
Femme                    -10.576146 -4.16844461  -2.2523902 -3.14669498
Homme                     10.576146  4.16844461   2.2523902  3.14669498
Autre                      0.842335  0.71031420   0.1387266  4.67415249
Cadre                     -2.055511  5.82387988   0.8792874 -2.99732552
Employe                   -6.134982 -2.98511287  -1.1075028 -4.20347276
Ouvrier qualifie           8.520937  0.01795085  -6.0042361 -0.06535111
Ouvrier specialise         1.373981 -4.48121398   0.2694127 -0.53921103
Profession intermediaire   2.181201  2.87033386   5.9575495 -6.17531113
qualif.NA                 -2.216002 -3.06479031   1.1241355  5.97634642
Technicien                 0.690503  4.93019571   3.0131024  7.22945971
peche.chasse_Non          -6.841457 -0.48901333   1.9068939  7.10124244
peche.chasse_Oui           6.841457  0.48901333  -1.9068939 -7.10124244
cinema_Non                 6.476072 -8.90955533  -1.5409316  2.23357870
cinema_Oui                -6.476072  8.90955533   1.5409316 -2.23357870
cuisine_Non                5.163665  0.48240056  10.0309250 -0.74633448
cuisine_Oui               -5.163665 -0.48240056 -10.0309250  0.74633448
bricol_Non                -4.634988 -6.71481452   6.9239634 -0.37708858
bricol_Oui                 4.634988  6.71481452  -6.9239634  0.37708858
sport_Non                  4.435028 -9.22905976   1.4717305 -0.66969730
sport_Oui                 -4.435028  9.22905976  -1.4717305  0.66969730
lecture.bd_Non             3.600868  1.45935250  -0.2315434 -0.58389535
lecture.bd_Oui            -3.600868 -1.45935250   0.2315434  0.58389535
$`Dim 1`
$`Dim 1`$quali
                     R2      p.value
sexe         0.56208476 2.366454e-37
qualif       0.51120576 7.798484e-27
peche.chasse 0.23520370 3.400728e-13
cinema       0.21075133 8.082765e-12
cuisine      0.13398711 9.803483e-08
bricol       0.10795536 2.033807e-06
sport        0.09884158 5.793702e-06
lecture.bd   0.06515704 2.643983e-04

$`Dim 1`$category
                           Estimate      p.value
Homme                     0.3684474 2.366454e-37
Ouvrier qualifie          0.5511168 1.431730e-16
peche.chasse_Oui          0.3728747 3.400728e-13
cinema_Non                0.2303405 8.082765e-12
cuisine_Non               0.1832683 9.803483e-08
bricol_Oui                0.1625604 2.033807e-06
sport_Non                 0.1667347 5.793702e-06
lecture.bd_Non            0.4010235 2.643983e-04
Profession intermediaire  0.2079741 2.715577e-02
lecture.bd_Oui           -0.4010235 2.643983e-04
Cadre                    -0.2694140 6.479938e-05
qualif.NA                -0.2440068 3.453776e-05
sport_Oui                -0.1667347 5.793702e-06
bricol_Non               -0.1625604 2.033807e-06
cuisine_Oui              -0.1832683 9.803483e-08
cinema_Oui               -0.2303405 8.082765e-12
peche.chasse_Non         -0.3728747 3.400728e-13
Employe                  -0.4301683 1.728942e-14
Femme                    -0.3684474 2.366454e-37
R>              Df Sum Sq Mean Sq F value    Pr(>F)    
tmp$sexe      1 27.053 27.0530  254.14 < 2.2e-16 ***
Residuals   198 21.077  0.1064                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Call:
aov(formula = acm$ind$coord[, 1] ~ tmp$sexe, na.action = na.exclude)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.8493 -0.2318  0.0140  0.2044  0.8195 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.02211    0.02311   0.957     0.34    
tmp$sexe1    0.36845    0.02311  15.942   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.3263 on 198 degrees of freedom
Multiple R-squared: 0.5621,     Adjusted R-squared: 0.5599 
F-statistic: 254.1 on 1 and 198 DF,  p-value: < 2.2e-16
R> 
Call:
lm(formula = acm$ind$coord[, 1] ~ tmp$sexe)

Coefficients:
(Intercept)    tmp$sexe1  
    0.02211      0.36845
R> R> R> (Intercept) tmp$qualif1 tmp$qualif2 tmp$qualif3 tmp$qualif4 tmp$qualif5 
 0.09225230  0.05124884 -0.26941399 -0.43016830 -0.24400685  0.55111680 
tmp$qualif6 tmp$qualif7 
 0.08896297  0.20797413
                              Dim 1       Dim 2       Dim 3       Dim 4
Femme                    -10.576146 -4.16844461  -2.2523902 -3.14669498
Homme                     10.576146  4.16844461   2.2523902  3.14669498
Autre                      0.842335  0.71031420   0.1387266  4.67415249
Cadre                     -2.055511  5.82387988   0.8792874 -2.99732552
Employe                   -6.134982 -2.98511287  -1.1075028 -4.20347276
Ouvrier qualifie           8.520937  0.01795085  -6.0042361 -0.06535111
Ouvrier specialise         1.373981 -4.48121398   0.2694127 -0.53921103
Profession intermediaire   2.181201  2.87033386   5.9575495 -6.17531113
qualif.NA                 -2.216002 -3.06479031   1.1241355  5.97634642
Technicien                 0.690503  4.93019571   3.0131024  7.22945971
peche.chasse_Non          -6.841457 -0.48901333   1.9068939  7.10124244
peche.chasse_Oui           6.841457  0.48901333  -1.9068939 -7.10124244
cinema_Non                 6.476072 -8.90955533  -1.5409316  2.23357870
cinema_Oui                -6.476072  8.90955533   1.5409316 -2.23357870
cuisine_Non                5.163665  0.48240056  10.0309250 -0.74633448
cuisine_Oui               -5.163665 -0.48240056 -10.0309250  0.74633448
bricol_Non                -4.634988 -6.71481452   6.9239634 -0.37708858
bricol_Oui                 4.634988  6.71481452  -6.9239634  0.37708858
sport_Non                  4.435028 -9.22905976   1.4717305 -0.66969730
sport_Oui                 -4.435028  9.22905976  -1.4717305  0.66969730
lecture.bd_Non             3.600868  1.45935250  -0.2315434 -0.58389535
lecture.bd_Oui            -3.600868 -1.45935250   0.2315434  0.58389535
R> R> R> $quali
                     R2      p.value
sexe         0.56208476 2.366454e-37
qualif       0.51120576 7.798484e-27
peche.chasse 0.23520370 3.400728e-13
cinema       0.21075133 8.082765e-12
cuisine      0.13398711 9.803483e-08
bricol       0.10795536 2.033807e-06
sport        0.09884158 5.793702e-06
lecture.bd   0.06515704 2.643983e-04

$category
                           Estimate      p.value
Homme                     0.3684474 2.366454e-37
Ouvrier qualifie          0.5511168 1.431730e-16
peche.chasse_Oui          0.3728747 3.400728e-13
cinema_Non                0.2303405 8.082765e-12
cuisine_Non               0.1832683 9.803483e-08
bricol_Oui                0.1625604 2.033807e-06
sport_Non                 0.1667347 5.793702e-06
lecture.bd_Non            0.4010235 2.643983e-04
Profession intermediaire  0.2079741 2.715577e-02
lecture.bd_Oui           -0.4010235 2.643983e-04
Cadre                    -0.2694140 6.479938e-05
qualif.NA                -0.2440068 3.453776e-05
sport_Oui                -0.1667347 5.793702e-06
bricol_Non               -0.1625604 2.033807e-06
cuisine_Oui              -0.1832683 9.803483e-08
cinema_Oui               -0.2303405 8.082765e-12
peche.chasse_Non         -0.3728747 3.400728e-13
Employe                  -0.4301683 1.728942e-14
Femme                    -0.3684474 2.366454e-37