(0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L), perdidos = c(0, 0, 0, 1, 0, 4, 0, 0,
1, 0), usaprots = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), usaproti =
structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c(Não Usa,
Uma Ponte Fixa, Mais de 1 PF, Prótese Parcial Removível,
Prótese Fixa + Removível, Prótese Total, Sem Informação
), class = factor), necprots = structure(c(1L, 1L, 3L,
1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c(Não necessita,
Prótese 1 elemento, Mais de 1 elemento, Combinação de próteses,
Prótese Total, Sem Informação), class = factor), necproti =
structure(c(1L,
1L, 4L, 2L, 1L, 3L, 1L, 1L, 2L, 1L), .Label = c(Não necessita,
Prótese 1 elemento, Mais de 1 elemento, Combinação de próteses,
Prótese Total, Sem Informação), class = factor), necprot =
structure(c(1L,
1L, 3L, 2L, 1L, 2L, 1L, 1L, 2L, 1L), .Label = c(Não necessita,
Parcial 1 maxilar, Parcial 2 maxilar, Total 1 maxilar,
Parcial + Total, Total 2 maxilar, Sem Informação), class = factor),
oidp = c(0L, 0L, 0L, 0L, 0L, 2L, 1L, 0L, 0L, 1L), f1 = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1), f2 = c(0.051897009506, 0.051897009506,
0.051897009506, 0.051897009506, 0.051897009506,
0.051897009506, 0.051897009506, 0.051897009506,
0.106059998273849, 0.106059998273849), f3 = c(0.066220653992,
0.066220653992, 0.066220653992, 0.066220653992,
0.066220653992, 0.066220653992, 0.066220653992,
0.066220653992, 0.138889998197556, 0.138889998197556),
f = c(0.0034388399446, 0.0034388399446, 0.0034388399446,
0.0034388399446, 0.0034388399446, 0.0034388399446,
0.0034388399446, 0.0034388399446, 0.014729371171,
0.014729371171), bwgr_et = c(291.019989013672, 291.019989013672,
291.019989013672, 291.019989013672, 291.019989013672, 291.019989013672,
291.019989013672, 291.019989013672, 67.879997253418, 67.879997253418
), cluster = c(12004010556, 12004010556, 12004010556,
12004010556, 12004010556, 12004010556, 12004010556,
12004010556, 12004010562, 12004010562), cluster2 =
c(01120308,
01120308, 01120308, 01120308, 01120308, 01120308,
01120308, 01120308, 01120309, 01120309), getni = c(1L,
4L, 4L, 4L, 2L, 4L, 4L, 4L, 4L, 4L), q04 = c(2L, 3L, 3L,
4L, NA, 2L, 1L, NA, 3L, 3L), q06 = c(2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L), q07 = c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 1L), q08 = c(0, 0, 0, 0, 0, 0, 0, 0, 3, 0), q10 = c(NA,
NA, 2L, 3L, 3L, 2L, 2L, 3L, 3L, 3L), q11 = c(NA, NA, 1L,
1L, 2L, 1L, 1L, 1L, 1L, 1L), q12 = c(NA, NA, 2L, 4L, 1L,
3L, 1L, 4L, 2L, 1L), q13 = structure(c(NA, NA, 2L, 3L, 2L,
3L, 2L, 2L, 2L, 2L), .Label = c(1, 2, 3, 4, 5), class =
factor),
q14 = c(3L, 2L, 3L, 4L, 2L, 2L, 4L, 3L, 4L, 2L), q15 = c(1L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), edcat = c(3, 1, 4, 2,
3, 3, 2, 4, 2, 2), peso = c(291, 291, 291, 291, 291, 291,
291, 291, 68, 68), cariado = c(3L, 0L, 6L, 2L, 0L, 2L, 1L,
4L, 5L, 3L), getar = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1)), .Names = c(regiao,
estado, cod_mun, setor, cap_int, idade, getario,
sexo, grp_etni, quest_01, quest_02, density, quest_03,
quest_04, inc_percapita1, inc_percapita2, inc_sqrt1,
inc_sqrt2, q05, quest_06, quest_07, quest_08, quest_09,
quest_10, quest_11, quest_12, quest_13, quest_14, quest_15,
exame, cpod, p_sang, p_calc, cpi_max, dai, trauma,
n_higido, n_cariado, n_restcar, n_restaur, n_perdcar,
n_perdout, perdidos, usaprots, usaproti, necprots,
necproti, necprot, oidp, f1, f2, f3, f, bwgr_et,
cluster, cluster2, getni, q04, q06, q07, q08, q10,
q11, q12, q13, q14, q15, edcat, peso, cariado,
getar), row.names = c(1241, 1242, 1243, 1244, 1245,
1246, 1247, 1248, 1256, 1268), class = data.frame)
id3$q13-as.factor(id3$q13)
m1 - polr(q13 ~ q11 + q10 + q12 + edcat + q08 + q06 + q14, data=id3,
Hess=TRUE)
summary(m1)
ordinal.or.display(m1)
fm1 - clm(q13 ~ q11 + q10 + q12 + edcat + q08 + q06 + q14, data=id3)
summary(fm1)
exp(coef(fm1))
[[elided Yahoo spam]]
(ci - confint(fm1))
exp(cbind(OR = coef(fm1), ci))
nominal_test(fm1)# test partial proportional odds assumption
##clm2 - partial proprotional odds
fm.nom - clm2(q13 ~ q11 + q10 + q12 + q08 + q06 + q14, data=id3, nominal=~
edcat)
summary(fm.nom)
exp(coef(fm.nom))
[[elided Yahoo spam]]
exp(cbind(OR = coef(fm.nom), ci))
Thanks,
Luciane
Em qui, 9/7/15, Kevin Wright kw.s...@gmail.com escreveu:
Assunto: Re: [R] clm funtion and CI
Data: Quinta-feira, 9 de Julho de 2015, 11:44
You need a reproducible
example.
On Wed, Jul 8
