The function check_ancova() fits an ANalysis of COVAriance (ANCOVA)
model to figure out which kind of linear regression model suits the
(historical) data best.
check_ancova(data, response_vbl, time_vbl, batch_vbl, alpha = 0.05)A list of two elements is returned that specifies which model, based
on the ANCOVA analysis, suits best. The first element (type.spec)
is a numeric vector of length 2 that specifies the best model accepted at
the significance level specified by alpha. It has the form
c(ci, cs), where ci specifies if a common intercept is
appropriate (ci = 1) or not (ci = 0) and cs specifies
if a common slope is appropriate (cs = 1) or not (cs = 0).
The second element (type.acronym) is an acronym representing the
first item. In case of a linear model including only a single batch,
all elements are NA.
A data frame with the columns specified by response_vbl,
time_vbl and batch_vbl.
A character string that specifies the response variable
name that must be a column of data.
A character string that specifies the time variable name
that must be a column of data.
A character string that specifies the column in data
with the grouping information (i.e. a factorial variable) for the
differentiation of the observations of the various batches.
A numeric value that specifies the significance level for the
decision which model is appropriate, i.e. if the assumption of
common slope or common intercept is appropriate or not.
The default is 0.05.
The function check_ancova() fits an ANCOVA (ANalyis of
COVAriance) model to the data contained in the provided data frame. Based
on alpha, it checks if the intercepts and/or slopes between the
groups differ significantly or not.
expirest_osle, expirest_wisle,
aov.