There are a few vacancies at the 1.5 HECS course Qantile Regression to be given 20 April – 8 May, 2015, at the University of Gothenburg. The application dead-line has expired but PhD students can send late applications to firstname.lastname@example.org.
Skewed data, ordinal or nominal data is common in medical research. For example when measurements are not following a Normal distribution or questionnaire based scales is used. One way to adjust for the skewness is to transform the variable (e.g. logarithm). This can lead to problems with the interpretation of the estimate. For example is a median of a log-transformed variable equal to the log of the median of the un-transformed variable (invariance). For a mean this is not true. In these situations quantile regression can be an option. Another area of use for quantile regression is calculation of reference intervals (an interval describing a normal population) or for analyzing quantiles of the response (e.g. analyzing how the relation between HbA1b and explanatory variables can differ for high and low HbA1c values).