load("~/Dropbox/odontologia/maestria_anunziatta/BancoUnidoBrasUru/BRASURU(07112013).RData")
library(survey)
##
## Attaching package: 'survey'
##
## The following object(s) are masked from 'package:graphics':
##
## dotchart
summary(disenio_urubra)
## Stratified 1 - level Cluster Sampling design (with replacement)
## With (83) clusters.
## svydesign(id = ~numer_esc, strata = ~pais, weights = ~round(weight.rec,
## 1), data = brasuru, nest = TRUE)
## Probabilities:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00754 0.05620 0.07520 0.07610 0.07690 0.25600
## Stratum Sizes:
## Bra Uru
## obs 1528 1154
## design.PSU 42 41
## actual.PSU 42 41
## Data variables:
## [1] "id" "pais" "ficha"
## [4] "eta" "tipoesc" "sexoinv"
## [7] "weight" "weight.rec" "numesc"
## [10] "numer_esc" "idade" "socioecon4cat"
## [13] "socioecon3cat" "escolmae" "escolmae13cat"
## [16] "escolmaerecat23cat" "freqescov" "freqescovacat"
## [19] "usofio" "freqfio" "usocreme"
## [22] "idadcreme" "visidentcatonde" "visiquando"
## [25] "fluorprof" "idadefluor" "isg."
## [28] "isg45" "isg20" "cposoms"
## [31] "cpodoms" "prevoms" "cposbere"
## [34] "cpodbere" "prevbere" "cposicdas"
## [37] "cpodicdas" "previcdas"
names(disenio_urubra$variables)
## [1] "id" "pais" "ficha"
## [4] "eta" "tipoesc" "sexoinv"
## [7] "weight" "weight.rec" "numesc"
## [10] "numer_esc" "idade" "socioecon4cat"
## [13] "socioecon3cat" "escolmae" "escolmae13cat"
## [16] "escolmaerecat23cat" "freqescov" "freqescovacat"
## [19] "usofio" "freqfio" "usocreme"
## [22] "idadcreme" "visidentcatonde" "visiquando"
## [25] "fluorprof" "idadefluor" "isg."
## [28] "isg45" "isg20" "cposoms"
## [31] "cpodoms" "prevoms" "cposbere"
## [34] "cpodbere" "prevbere" "cposicdas"
## [37] "cpodicdas" "previcdas"
# prevoms,prevbere,cpodoms,cpodbere
summary(disenio_urubra$variables[, c(32, 35, 31, 34)])
## prevoms prevbere cpodoms cpodbere
## 1-SinCavi:1105 0-NTL: 932 Min. : 0.00 Min. : 0.00
## 2-conCavi:1577 1-LC :1750 1st Qu.: 0.00 1st Qu.: 0.00
## Median : 1.00 Median : 2.00
## Mean : 1.56 Mean : 2.41
## 3rd Qu.: 3.00 3rd Qu.: 4.00
## Max. :15.00 Max. :26.00
tablas prevalencia
round(svyby(~prevoms, ~pais, disenio_urubra, svymean, na.rm = TRUE)[, 2:5] *
100, 1)
## prevoms1-SinCavi prevoms2-conCavi se.prevoms1-SinCavi
## Bra 44.6 55.4 2.4
## Uru 38.5 61.5 2.5
## se.prevoms2-conCavi
## Bra 2.4
## Uru 2.5
round(confint(svyby(~prevoms, ~pais, disenio_urubra, svymean, na.rm = TRUE)) *
100, 1)
## 2.5 % 97.5 %
## Bra:prevoms1-SinCavi 40.0 49.2
## Uru:prevoms1-SinCavi 33.6 43.4
## Bra:prevoms2-conCavi 50.8 60.0
## Uru:prevoms2-conCavi 56.6 66.4
round(svyby(~prevbere, ~pais, disenio_urubra, svymean, na.rm = TRUE)[, 2:5] *
100, 1)
## prevbere0-NTL prevbere1-LC se.prevbere0-NTL se.prevbere1-LC
## Bra 36.5 63.5 2.1 2.1
## Uru 33.7 66.3 2.8 2.8
round(confint(svyby(~prevbere, ~pais, disenio_urubra, svymean, na.rm = TRUE)) *
100, 1)
## 2.5 % 97.5 %
## Bra:prevbere0-NTL 32.4 40.5
## Uru:prevbere0-NTL 28.3 39.1
## Bra:prevbere1-LC 59.5 67.6
## Uru:prevbere1-LC 60.9 71.7
tablas extension
round(svyby(~cpodoms, ~pais, disenio_urubra, svymean, na.rm = TRUE)[, 2:3] *
1, 1)
## cpodoms se
## Bra 1.4 0.1
## Uru 1.6 0.1
round(confint(svyby(~cpodoms, ~pais, disenio_urubra, svymean, na.rm = TRUE)) *
1, 1)
## 2.5 % 97.5 %
## Bra 1.2 1.6
## Uru 1.4 1.9
svyboxplot(cpodoms ~ pais, disenio_urubra, all.outliers = TRUE, horizontal = TRUE,
main = "Cpodoms", cex.main = 1, col = c("lightsalmon", "skyblue"))
media_cpodoms <- svyby(~cpodoms, ~pais, disenio_urubra, svymean, na.rm = TRUE)
abline(v = media_cpodoms[1, 2], col = c("red4"), lwd = 2)
abline(v = media_cpodoms[2, 2], col = c("blue4"), lwd = 2)
round(svyby(~cpodbere, ~pais, disenio_urubra, svymean, na.rm = TRUE)[, 2:3] *
1, 1)
## cpodbere se
## Bra 2.0 0.1
## Uru 2.8 0.2
round(confint(svyby(~cpodbere, ~pais, disenio_urubra, svymean, na.rm = TRUE)) *
1, 1)
## 2.5 % 97.5 %
## Bra 1.8 2.2
## Uru 2.4 3.2
svyboxplot(cpodbere ~ pais, disenio_urubra, all.outliers = TRUE, horizontal = TRUE,
main = "Cpodbere", cex.main = 1, col = c("lightsalmon", "skyblue"))
media_cpodbere <- svyby(~cpodbere, ~pais, disenio_urubra, svymean, na.rm = TRUE)
abline(v = media_cpodbere[1, 2], col = c("red4"), lwd = 2)
abline(v = media_cpodbere[2, 2], col = c("blue4"), lwd = 2)
disenio_uru <- subset(disenio_urubra, pais == "Uru")
svyttest(I(cpodbere - cpodoms) ~ 0, disenio_uru)
##
## Design-based one-sample t-test
##
## data: I(cpodbere - cpodoms) ~ 0
## t = 8.379, df = 40, p-value = 2.441e-10
## alternative hypothesis: true mean is not equal to 0
## sample estimates:
## mean
## 1.164
disenio_bra <- subset(disenio_urubra, pais == "Bra")
svyttest(I(cpodbere - cpodoms) ~ 0, disenio_bra)
##
## Design-based one-sample t-test
##
## data: I(cpodbere - cpodoms) ~ 0
## t = 17.24, df = 41, p-value < 2.2e-16
## alternative hypothesis: true mean is not equal to 0
## sample estimates:
## mean
## 0.5625