- outcome
An object of class character containing the name of the
outcome variable. The outcome variable can be continuous, categorical,
or count.
- age
An object of class character representing the age group index
taking on a small number of distinct values in the data. Usually, the vector
should be converted to a factor (or the terms of "category" and "enumerated
type").
- period
An object of class character, similar to the argument of age,
representing the time period index in the data.
- cohort
An optional object of class character representing cohort
membership index in the data. Usually, the cohort index can be generated
from the age group index and time period index in the data because of the
intrinsic relationship among these three time-related indices.
- weight
An optional vector of sample weights to be used in the model
fitting process. If non-NULL, the weights will be used in the first step to
estimate the model. Observations with negative weights will be automatically
dropped in modeling.
- covariate
An optional vector of characters, representing the name(s)
of the user-specified covariate(s) to be used in the model. If the
variable(s) are not found in data, there will be an error message reminding
the users to check the data again.
- data
A data frame containing the outcome variable, age group
indicator, period group indicator, and covariates to be used in the model.
If the variable(s) are not found in data, there will be an error message
reminding the users to check the input data again.
- family
Used to specify the statistical distribution of the error
term and link function to be used in the model. Usually, it is a character
string naming a family function. For example, family can be "binomial",
"multinomial"", or "gaussian". Users could also check R package glm for
more details of family functions.
- dev.test
Logical, specifying if the global F test should be
implemented before fitting the APC-I model. If TRUE, apci will first run the
global F test and report the test results; otherwise, apci will skip this
step and return NULL. The default setting is TRUE. However, users should be
aware that the algorithm will not automatically stop even if there is no
significant age-by-period interactions based on the global F test.
- print
Logical, specifying if the intermediate results should be
displayed in the console when fitting the model. The default setting is
TRUE to display the results of each procedure.
- gee
Logical, indicating if the data is cross-sectional data or
longitudinal/panel data. If TRUE, the generalized estimating equation
will be used to correct the standard error estimates. The default is
FALSE, indicating that the data are cross-sectional.
- id
A vector of character, specifying the cluster index in longitudinal
data. It is required when gee is TRUE. The length of the vector
should be the same as the number of observations.
- corstr
A character string, specifying a possible correlation
structure in the error terms when gee is TRUE. The following
are allowed: independence, fixed, stat\_M\_dep,
non\_stat\_M\_dep, exchangeable, AR-M and
unstructured. The default value is exchangeable.
- unequal_interval
Logical, indicating if age and period groups are
of the same interval width. The default is set as TRUE.
- age_range, period_range
Numeric vector indicating the actual
age and period range (e.g., 10 to 59 years old from 2000 to 2019).
- age_interval, period_interval, age_group, period_group
Numeric
values or character vectors indicating how age and period are
grouped. age_interval and period_interval are numbers
indicating the width of age and period groups respectively.
age_group and period_group are character vectors
explicitly listing all potential age and period groups. Either
age_interval(period_interval) or age_group
(period_group) have to be defined when unequal_interval
is TRUE.
- ...
Additional arguments to be passed to the function.