enseignement de base au niger :quel bilan - CONFEMEN
enseignement de base au niger :quel bilan - CONFEMEN
enseignement de base au niger :quel bilan - CONFEMEN
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Prob > F = 0.0000<br />
R-squared = 0.4327<br />
Number of clusters (NUMECOLE) = 98 Root MSE = .77099<br />
------------------------------------------------------------------------------<br />
| Robust<br />
STFIN2FM | Coef. Std. Err. t P>|t| [95% Conf. Interval]<br />
-------------+----------------------------------------------------------------<br />
STINI2FM | .5000686 .0428839 11.66 0.000 .4149559 .5851813<br />
FILLE | -.046239 .0475089 -0.97 0.333 -.1405309 .048053<br />
AGEPLUS | -.1000632 .0827297 -1.21 0.229 -.2642589 .0641324<br />
ENFTCONFIE | -.0474796 .0704778 -0.67 0.502 -.1873585 .0923993<br />
NIVEAUVIE3 | .1053471 .0911249 1.16 0.250 -.0755107 .2862049<br />
REDAN2 | -.1549328 .0738232 -2.10 0.038 -.3014514 -.0084142<br />
LIV_FR | .2787436 .0657268 4.24 0.000 .1482941 .4091931<br />
LIV_MT | .057408 .063431 0.91 0.368 -.068485 .1833009<br />
MAITRFEM | -.0698933 .1716306 -0.41 0.685 -.4105324 .2707459<br />
VOLONTAIRE | -.1979687 .130331 -1.52 0.132 -.4566396 .0607022<br />
DIPCYCLB | -.2234136 .1179513 -1.89 0.061 -.4575142 .0106871<br />
MTMOBILE | -.2648033 .1993705 -1.33 0.187 -.6604985 .1308919<br />
MTPRECENS | .172686 .1144439 1.51 0.135 -.0544534 .3998255<br />
MTAUTREACT | -.1028946 .1110093 -0.93 0.356 -.3232173 .1174282<br />
MTRESTENS | -.1717478 .1175985 -1.46 0.147 -.4051482 .0616526<br />
MTCONCOUR | .1957818 .1392905 1.41 0.163 -.0806713 .472235<br />
ABSMT | .0024499 .0146108 0.17 0.867 -.0265484 .0314482<br />
DOUBLFLX | -.3670539 .1739406 -2.11 0.037 -.7122779 -.0218299<br />
BANCO | .0175197 .1172443 0.15 0.882 -.2151778 .2502171<br />
UTILIVRFR | .2038334 .1318465 1.55 0.125 -.0578454 .4655123<br />
UTILIVMT | -.3160901 .1379073 -2.29 0.024 -.5897979 -.0423824<br />
APEACTIV | -.1505483 .1124551 -1.34 0.184 -.3737406 .072644<br />
CONSULCOLL | -.0506765 .107439 -0.47 0.638 -.2639131 .1625602<br />
INSPECTEUR | -.2566933 .1481191 -1.73 0.086 -.5506687 .0372821<br />
CONSPEDAG | .1634801 .1203998 1.36 0.178 -.0754802 .4024403<br />
MTCHANGECO | .0126954 .1243921 0.10 0.919 -.2341884 .2595792<br />
DIRENSEIG | .3716039 .1390972 2.67 0.009 .0955344 .6476734<br />
RURAL | -.2699656 .1398595 -1.93 0.056 -.547548 .0076168<br />
_cons | .173648 .3278261 0.53 0.598 -.4769961 .8242921<br />
------------------------------------------------------------------------------<br />
Les variables CONSPEDAG et NIVCYCLB ont dû être enlevées du modèle pour c<strong>au</strong>se <strong>de</strong><br />
multicolinéarités, mais cela n’influence pas le résultat <strong>de</strong> la variable volontaire.<br />
Ce modèle confirme qu’il n’y a pas <strong>de</strong> différence significative entre enseignants<br />
contractuels et titulaires <strong>au</strong> CP.<br />
Affinons la regression précé<strong>de</strong>nte en distingant les contractuels diplômlés <strong>de</strong> ceux qui ne le<br />
sont pas.<br />
Modèle IV.12<br />
reg STFIN2FM STINI2FM FILLE AGEPLUS ENFTCONFIE NIVEAUVIE3 REDAN2 LIV_FR LIV_<br />
> MT MAITRFEM VOLDPF VOLNDPF DIPCYCLB MTMOBILE MTAUTREACT MTRESTENS MTCONCOUR AB<br />
> SMT DOUBLFLX BANCO UTILIVRFR UTILIVMT APEACTIV CONSULCOLL INSPECTEUR CONSPEDAG<br />
> MTCHANGECO DIRENSEIG RURAL if SERVICE < 10, cluster(NUMECOLE)<br />
Regression with robust standard errors Number of obs = 1178<br />
F( 28, 97) = 15.84<br />
Prob > F = 0.0000<br />
R-squared = 0.4406<br />
Number of clusters (NUMECOLE) = 98 Root MSE = .76557<br />
------------------------------------------------------------------------------<br />
| Robust<br />
STFIN2FM | Coef. Std. Err. t P>|t| [95% Conf. Interval]<br />
100
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