R: Maternal Drinking and Congenital Sex Organ Malformation
malformations
R Documentation
Maternal Drinking and Congenital Sex Organ Malformation
Description
A subset of data from a study on the relationship between maternal alcohol
consumption and congenital malformations.
Usage
malformations
Format
A data frame with 32574 observations on 2 variables.
consumption
alcohol consumption, an ordered factor with levels "0",
"<1", "1-2", "3-5" and ">=6".
malformation
congenital sex organ malformation, a factor with levels "Present"
and "Absent".
Details
Data from a prospective study undertaken to determine whether moderate or
light drinking during the first trimester of pregnancy increases the risk for
congenital malformations (Mills and Graubard, 1987). The subset given here
concerns only sex organ malformation (Mills and Graubard, 1987, Tab. 4).
Graubard and Korn (1987) used this data set to illustrate that different
choices of scores for ordinal variables can lead to conflicting conclusions.
Source
Mills, J. L. and Graubard, B. I. (1987). Is moderate drinking during
pregnancy associated with an increased risk for malformations?
Pediatrics80(3), 309–314.
References
Graubard, B. I. and Korn, E. L. (1987). Choice of column scores for testing
independence in ordered 2 x K contingency tables.
Biometrics43(2), 471–476.
Examples
## Graubard and Korn (1987, Tab. 3)
## One-sided approximative (Monte Carlo) Cochran-Armitage test
## Note: midpoint scores (p < 0.05)
midpoints <- c(0, 0.5, 1.5, 4.0, 7.0)
chisq_test(malformation ~ consumption, data = malformations,
distribution = approximate(B = 1000), alternative = "greater",
scores = list(consumption = midpoints))
## One-sided approximative (Monte Carlo) Cochran-Armitage test
## Note: midrank scores (p > 0.05)
midranks <- c(8557.5, 24375.5, 32013.0, 32473.0, 32555.5)
chisq_test(malformation ~ consumption, data = malformations,
distribution = approximate(B = 1000), alternative = "greater",
scores = list(consumption = midranks))
## One-sided approximative (Monte Carlo) Cochran-Armitage test
## Note: equally spaced scores (p > 0.05)
chisq_test(malformation ~ consumption, data = malformations,
distribution = approximate(B = 1000), alternative = "greater")