Tablas bivariadas para muestra unificada
library(car)
# 28 de octubre 2013
#
# load('~/Dropbox/odontologia/maestria_anunziatta/BancoUnidoBrasUru/BRASURU(28102013).RData')
load("~/Dropbox/odontologia/maestria_anunziatta/BancoUnidoBrasUru/BRASURU(07112013).RData")
library(survey)
##
## Attaching package: 'survey'
##
## The following object(s) are masked from 'package:graphics':
##
## dotchart
levels(disenio_urubra$variables$prevoms)
## [1] "1-SinCavi" "2-conCavi"
table(disenio_urubra$variables$cpodoms, disenio_urubra$variables$prevoms)
##
## 1-SinCavi 2-conCavi
## 0 1105 0
## 1 0 495
## 2 0 404
## 3 0 259
## 4 0 217
## 5 0 108
## 6 0 38
## 7 0 22
## 8 0 14
## 9 0 12
## 10 0 3
## 11 0 3
## 14 0 1
## 15 0 1
tabla2p <- svyby(~sexoinv, ~pais, disenio_urubra, svymean, keep.var = TRUE,
na.rm = TRUE, deff = TRUE)
round(tabla2p[, 2:4] * 100, 1)
## sexoinv1-M sexoinv2-F se.sexoinv1-M
## Bra 50.8 49.2 1.3
## Uru 51.8 48.2 1.8
svychisq(~sexoinv + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~sexoinv + pais, disenio_urubra, statistic = "Wald")
## F = 0.1911, ndf = 1, ddf = 81, p-value = 0.6631
tabla3p <- svyby(~socioecon4cat, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla3p[, 2:4] * 100, 1)
## socioecon4cat1-alto socioecon4cat2-medio-alto
## Bra 11 24.4
## Uru 17 41.6
## socioecon4cat3-medio-bajo
## Bra 54.9
## Uru 21.4
svychisq(~socioecon4cat + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~socioecon4cat + pais, disenio_urubra, statistic = "Wald")
## F = 27.79, ndf = 3, ddf = 81, p-value = 1.864e-12
tabla4p <- svyby(~socioecon3cat, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla4p[, 2:4] * 100, 1)
## socioecon3cat1-alto socioecon3cat2-medio socioecon3cat3-bajo
## Bra 11.0 79.3 9.7
## Uru 31.4 48.6 20.0
svychisq(~socioecon3cat + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~socioecon3cat + pais, disenio_urubra, statistic = "Wald")
## F = 31, ndf = 2, ddf = 81, p-value = 1.005e-10
tabla5p <- svyby(~escolmaerecat23cat, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla5p[, 2:4] * 100, 1)
## escolmaerecat23cat1-college-university escolmaerecat23cat2-high school
## Bra 16.6 34.3
## Uru 25.3 50.6
## escolmaerecat23cat3-elementary school
## Bra 49.1
## Uru 24.2
svychisq(~escolmaerecat23cat + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~escolmaerecat23cat + pais, disenio_urubra, statistic = "Wald")
## F = 12.43, ndf = 2, ddf = 81, p-value = 1.965e-05
tabla5ap <- svyby(~escolmae13cat, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla5ap[, 2:4] * 100, 1)
## escolmae13cat1-college-university escolmae13cat2-high school
## Bra 9.7 32.0
## Uru 16.7 23.3
## escolmae13cat3-Elementary School
## Bra 58.3
## Uru 59.9
svychisq(~escolmae13cat + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~escolmae13cat + pais, disenio_urubra, statistic = "Wald")
## F = 2.732, ndf = 2, ddf = 81, p-value = 0.07107
tabla6p <- svyby(~freqescovacat, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla6p[, 2:4] * 100, 1)
## freqescovacat1-menos de 1 vez al d<ed>a freqescovacat2-veces al d<ed>a
## Bra 21.4 44.9
## Uru 18.1 34.0
## freqescovacat3-veces al d<ed>a
## Bra 33.7
## Uru 47.9
svychisq(~freqescovacat + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~freqescovacat + pais, disenio_urubra, statistic = "Wald")
## F = 10.06, ndf = 2, ddf = 81, p-value = 0.0001256
tabla7p <- svyby(~usocreme, ~pais, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla7p[, 2:4] * 100, 1)
## usocreme1-Si usocreme2-No se.usocreme1-Si
## Bra 98.2 1.8 0.4
## Uru 98.2 1.8 0.6
svychisq(~usocreme + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~usocreme + pais, disenio_urubra, statistic = "Wald")
## F = 3e-04, ndf = 1, ddf = 81, p-value = 0.9857
tabla8p <- svyby(~visidentcatonde, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla8p[, 2:4] * 100, 1)
## visidentcatonde1-Convenio particular visidentcatonde2-Publico
## Bra 49.0 30.4
## Uru 61.8 26.5
## visidentcatonde3-Nunca fue al dentista
## Bra 20.6
## Uru 11.8
svychisq(~visidentcatonde + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~visidentcatonde + pais, disenio_urubra, statistic = "Wald")
## F = 3.583, ndf = 2, ddf = 81, p-value = 0.03227
tabla9p <- svyby(~visiquando, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla9p[, 2:4] * 100, 1)
## visiquando1- menos de 1 a<f1>o visiquando2- m<e1>s de 2 a<f1>os
## Bra 56.6 22.8
## Uru 74.4 14.0
## visiquando3- nunca fue
## Bra 20.6
## Uru 11.6
svychisq(~visiquando + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~visiquando + pais, disenio_urubra, statistic = "Wald")
## F = 6.084, ndf = 2, ddf = 81, p-value = 0.003455
tabla10p <- svyby(~fluorprof, ~pais, disenio_urubra, svymean, na.rm = TRUE,
deff = TRUE)
round(tabla10p[, 2:4] * 100, 1)
## fluorprof1-Si fluorprof2-No se.fluorprof1-Si
## Bra 64.9 35.1 2.3
## Uru 62.7 37.3 3.2
svychisq(~fluorprof + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~fluorprof + pais, disenio_urubra, statistic = "Wald")
## F = 0.3345, ndf = 1, ddf = 81, p-value = 0.5646
tabla11p <- svyby(~isg20, ~pais, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla11p[, 2:4] * 100, 1)
## isg201- <=20 isg202- 20 a 60 isg203- >=60
## Bra 2.1 66.6 31.4
## Uru 48.0 44.7 7.3
svychisq(~isg20 + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~isg20 + pais, disenio_urubra, statistic = "Wald")
## F = 58.68, ndf = 2, ddf = 81, p-value < 2.2e-16
tabla12p <- svyby(~isg45, ~pais, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla12p[, 2:4] * 100, 1)
## isg451- <=45 isg452- 45 a 60 isg453- >=60
## Bra 34.5 34.1 31.4
## Uru 79.7 13.0 7.3
svychisq(~isg45 + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~isg45 + pais, disenio_urubra, statistic = "Wald")
## F = 38.26, ndf = 2, ddf = 81, p-value = 2.003e-12
tabla13p <- svyby(~tipoesc, ~pais, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla13p[, 2:4] * 100, 1)
## tipoesc1-Particular tipoesc2-Publica se.tipoesc1-Particular
## Bra 22.0 78.0 7.4
## Uru 26.8 73.2 8.6
svychisq(~tipoesc + pais, disenio_urubra, statistic = "Wald")
##
## Design-based Wald test of association
##
## data: svychisq(~tipoesc + pais, disenio_urubra, statistic = "Wald")
## F = 0.1797, ndf = 1, ddf = 81, p-value = 0.6728