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Brown et al (1983) gave these data on two signs of toxaemia, an abnormal condition during pregnancy characterized by high blood pressure (hypertension) and high levels of protein in the urine. If untreated, both the mother and baby are at risk of complications or death.

The data frame Toxaemia represents 13384 expectant mothers in Bradford, England in their first pregnancy, who were also classified according to social class and the number of cigarettes smoked per day.

Usage

data(Toxaemia)

Format

A data frame in frequency form representing a 5 x 3 x 2 x 2 contingency table, with 60 observations on the following 5 variables.

class

Social class of mother, a factor with levels 1 2 3 4 5

smoke

Cigarettes smoked per day during pregnancy, a factor with levels 0 1-19 20+

hyper

Hypertension level, a factor with levels Low High

urea

Protein urea level, a factor with levels Low High

Freq

frequency in each cell, a numeric vector

Source

Brown, P. J., Stone, J. and Ord-Smith, C. (1983), Toxaemic signs during pregnancy. JRSS, Series C, Applied Statistics, 32, 69-72

References

Friendly, M. (2000), Visualizing Categorical Data, SAS Institute, Cary, NC, Example 7.15.

Friendly, M. and Meyer, D. (2016). Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Boca Raton, FL: Chapman & Hall/CRC. http://ddar.datavis.ca. Example 10.10.

Examples

data(Toxaemia)

tox.tab <- xtabs(Freq ~ class + smoke + hyper + urea, Toxaemia)
ftable(tox.tab, row.vars=1)
#>       smoke    0                1-19                 20+               
#>       hyper  Low      High       Low      High       Low      High     
#>       urea   Low High  Low High  Low High  Low High  Low High  Low High
#> class                                                                  
#> 1            286   21   82   28   71    5   24    5   13    0    3    1
#> 2            785   34  266   50  284   17   92   13   34    3   15    0
#> 3           3160  164 1101  278 2300  142  492  120  383   32   92   16
#> 4            656   52  213   63  649   46  129   35  163   12   40    7
#> 5            245   23   78   20  321   34   74   22   65    4   14    7


# symptoms by smoking
mosaic(~smoke + hyper + urea, data=tox.tab, shade=TRUE)


# symptoms by social class
mosaic(~class + hyper + urea, data=tox.tab, shade=TRUE)


# predictors
mosaic(~smoke + class, data=tox.tab, shade=TRUE)


# responses
mosaic(~hyper + urea, data=tox.tab, shade=TRUE)


# log odds ratios for urea and hypertension, by class and smoke
if (FALSE) { # \dontrun{
LOR <-loddsratio(aperm(tox.tab))
LOR
} # }