This is a single imputation of the aze dataset which was
collected on patients carrying a colon adenocarcinoma. It has 104
observations on 33 binary qualitative explanatory variables and one response
variable y representing the cancer stage according to the to
Astler-Coller classification (Astler and Coller, 1954). A microsattelite is
a non-coding DNA sequence.
A data frame with 104 observations on the following 34 variables.
the response: a binary vector (Astler-Coller score).
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
a binary vector that indicates whether this microsatellite is altered or not.
Nicolas Meyer, Myriam Maumy-Bertrand et Frédéric Bertrand (2010). Comparing the linear and the logistic PLS regression with qualitative predictors: application to allelotyping data. Journal de la Société Française de Statistique, 151(2), pages 1-18.
data(aze_compl)
str(aze_compl)
Run the code above in your browser using DataLab