Tablas bivariadas para muestra unificada

Pais vs resto de variables independientes

library(car)


# 28 de octubre 2013

load("~/Dropbox/odontologia/maestria_anunziatta/BancoUnidoBrasUru/BRASURU(28102013).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(~pais, ~sexoinv, disenio_urubra, svymean, keep.var = TRUE, 
    na.rm = TRUE, deff = TRUE)
round(tabla2p[, 2:4] * 100, 1)
##     paisBra paisUru se.paisBra
## 1-M    42.6    57.4        4.2
## 2-F    43.6    56.4        4.1
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(~pais, ~socioecon4cat, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla3p[, 2:4] * 100, 1)
##              paisBra paisUru se.paisBra
## 1-alto          33.0    67.0        9.4
## 2-medio-alto    31.0    69.0        4.6
## 3-medio-bajo    66.2    33.8        4.4
## 4-bajo          27.2    72.8        4.7
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(~pais, ~socioecon3cat, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla4p[, 2:4] * 100, 1)
##         paisBra paisUru se.paisBra
## 1-alto     21.1    78.9        6.2
## 2-medio    55.5    44.5        4.5
## 3-bajo     27.2    72.8        4.7
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(~pais, ~escolmaerecat23cat, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla5p[, 2:4] * 100, 1)
##                      paisBra paisUru se.paisBra
## 1-college-university    33.6    66.4        8.3
## 2-high school           34.3    65.7        4.4
## 3-elementary school     61.0    39.0        5.4
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(~pais, ~escolmae13cat, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla5ap[, 2:4] * 100, 1)
##                      paisBra paisUru se.paisBra
## 1-college-university    30.9    69.1        9.2
## 2-high school           51.4    48.6        7.6
## 3-Elementary School     42.8    57.2        4.8
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(~pais, ~freqescovacat, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla6p[, 2:4] * 100, 1)
##                            paisBra paisUru se.paisBra
## 1-menos de 1 vez al d\xeda    47.9    52.1        4.5
## 2-veces al d\xeda             50.7    49.3        4.6
## 3-veces al d\xeda             35.4    64.6        4.4
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(~pais, ~usocreme, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla7p[, 2:4] * 100, 1)
##      paisBra paisUru se.paisBra
## 1-Si    43.2    56.8        4.1
## 2-No    43.0    57.0       10.1
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(~pais, ~visidentcatonde, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla8p[, 2:4] * 100, 1)
##                         paisBra paisUru se.paisBra
## 1-Convenio particular      38.0    62.0        5.1
## 2-Publico                  47.0    53.0        5.9
## 3-Nunca fue al dentista    57.5    42.5        5.0
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(~pais, ~visiquando, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla9p[, 2:4] * 100, 1)
##                        paisBra paisUru se.paisBra
## 1- menos de 1 a\xf1o      37.1    62.9        4.6
## 2- m\xe1s de 2 a\xf1os    55.8    44.2        4.8
## 3- nunca fue              57.9    42.1        5.1
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(~pais, ~fluorprof, disenio_urubra, svymean, na.rm = TRUE, 
    deff = TRUE)
round(tabla10p[, 2:4] * 100, 1)
##      paisBra paisUru se.paisBra
## 1-Si    45.8    54.2        4.8
## 2-No    43.4    56.6        4.3
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(~pais, ~isg20, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla11p[, 2:4] * 100, 1)
##            paisBra paisUru se.paisBra
## 1- <=20        3.1    96.9        0.9
## 2- 20 a 60    53.0    47.0        4.8
## 3- >=60       76.5    23.5        4.0
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(~pais, ~isg45, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla12p[, 2:4] * 100, 1)
##            paisBra paisUru se.paisBra
## 1- <=45       24.7    75.3        3.4
## 2- 45 a 60    66.5    33.5        4.6
## 3- >=60       76.5    23.5        4.0
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(~pais, ~tipoesc, disenio_urubra, svymean, na.rm = TRUE, deff = TRUE)
round(tabla13p[, 2:4] * 100, 1)
##              paisBra paisUru se.paisBra
## 1-Particular    38.3    61.7       11.7
## 2-Publica       44.6    55.4        5.5
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