quantsccs | R Documentation |
This function fits the starndard SCCS model where the exposures are measured on a continuous scale.
quantsccs(formula, indiv, event, data)
formula |
model formula. The dependent variale should always be "event" e.g. event ~ expo, where expo is an exposure measured at each time unit. |
indiv |
a vector of individual identifiers of cases |
event |
number of events occuring at each time unit. |
data |
a data frame containing the input data. Data are assembled one line per time unit of observation. |
In this method exposures are measured at successive time points within the observation period for each case. And number of events experienced by each case at each time point are recorded.
Relative incidence estimates along with their 95% confidence intervals.
Yonas Ghebremichael-Weldeselassie, Heather Whitaker, Paddy Farrington.
Farrington P., Whitaker H., and Ghebremichael-Weldeselassie Y. (2018). Self-controlled Case Series Studies: A modelling Guide with R. Boca Raton: Chapman & Hall/CRC Press.
semisccs
# Headaches and blood pressure data. sys and dia (continuoous exposures) are systolic and
# diastolic blood pressure measurements respectively
bp.mod <- quantsccs(event~sys+dia, indiv=case, event=head,
data=bpdat)
bp.mod
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