Aliases: svyfactanal
Keywords: survey multivariate
### ** Examples data(api) dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) svyfactanal(~api99+api00+hsg+meals+ell+emer, design=dclus1, factors=2)
Call: svyfactanal(~api99 + api00 + hsg + meals + ell + emer, design = dclus1, factors = 2) Uniquenesses: api99 api00 hsg meals ell emer 0.009 0.058 0.978 0.230 0.005 0.865 Loadings: Factor1 Factor2 api99 -0.990 0.108 api00 -0.959 0.151 hsg -0.143 meals 0.877 ell 0.727 0.683 emer 0.367 Factor1 Factor2 SS loadings 3.333 0.521 Proportion Var 0.556 0.087 Cumulative Var 0.556 0.642 The degrees of freedom for the model is 4 and the fit was 0.0898
svyfactanal(~api99+api00+hsg+meals+ell+emer, design=dclus1, factors=2, n="effective")
Call: svyfactanal(~api99 + api00 + hsg + meals + ell + emer, design = dclus1, factors = 2, n = "effective") Uniquenesses: api99 api00 hsg meals ell emer 0.009 0.058 0.978 0.230 0.005 0.865 Loadings: Factor1 Factor2 api99 -0.990 0.108 api00 -0.959 0.151 hsg -0.143 meals 0.877 ell 0.727 0.683 emer 0.367 Factor1 Factor2 SS loadings 3.333 0.521 Proportion Var 0.556 0.087 Cumulative Var 0.556 0.642 Test of the hypothesis that 2 factors are sufficient. The chi square statistic is 2.94 on 4 degrees of freedom. The p-value is 0.567
##Population dat for comparison factanal(~api99+api00+hsg+meals+ell+emer, data=apipop, factors=2)
Call: factanal(x = ~api99 + api00 + hsg + meals + ell + emer, factors = 2, data = apipop) Uniquenesses: api99 api00 hsg meals ell emer 0.024 0.023 0.799 0.005 0.392 0.732 Loadings: Factor1 Factor2 api99 0.839 -0.522 api00 0.864 -0.480 hsg -0.272 0.357 meals -0.471 0.879 ell -0.468 0.623 emer -0.433 0.284 Factor1 Factor2 SS loadings 2.152 1.872 Proportion Var 0.359 0.312 Cumulative Var 0.359 0.671 Test of the hypothesis that 2 factors are sufficient. The chi square statistic is 580.89 on 4 degrees of freedom. The p-value is 2.12e-124