acc_varcomp {dataquieR} | R Documentation |
Utility function to compute model-based ICC depending on the (statistical) data type
Description
This function is still under construction. It is designed to run for any statistical data type as follows:
Variables with only two distinct values will be modeled by mixed effects logistic regression.
Nominal variables will be transformed to binary variables. This can be user-specified using the metadata columns
RECODE_CASES
and/orRECODE_CONTROL
. Otherwise, the most frequent category will be assigned to cases and the remaining categories to control. As for other binary variables, the ICC will be computed using a mixed effects logistic regression.Ordinal variables will be analyzed by linear mixed effects models, if every level of the variable has at least as many observations as specified in the argument
cut_off_linear_model_for_ord
. Otherwise, the data will be modeled by a mixed effects ordered regression, if the packageordinal
is available.Metric variables with integer values are analyzed by linear mixed effects models.
For variables with data type
float
, the existing implementationacc_varcomp
is called, which also uses linear mixed effects models.
Usage
acc_varcomp(
resp_vars = NULL,
group_vars = NULL,
co_vars = NULL,
study_data,
label_col,
item_level = "item_level",
min_obs_in_subgroup = 10,
min_subgroups = 5,
cut_off_linear_model_for_ord = 10,
threshold_value = lifecycle::deprecated(),
meta_data = item_level,
meta_data_v2
)
Arguments
resp_vars |
variable the name of the measurement variable |
group_vars |
variable the name of the examiner, device or reader variable |
co_vars |
variable list a vector of covariables, e.g. age and sex, for adjustment |
study_data |
data.frame the data frame that contains the measurements |
label_col |
variable attribute the name of the column in the metadata with labels of variables |
item_level |
data.frame the data frame that contains metadata attributes of study data |
min_obs_in_subgroup |
integer from=0. This optional argument specifies
the minimum number of observations that is
required to include a subgroup (level) of the
|
min_subgroups |
integer from=0. This optional argument specifies
the minimum number of subgroups (level) of the
|
cut_off_linear_model_for_ord |
integer from=0. This optional argument
specifies the minimum number of observations for
individual levels of an ordinal outcome
( |
threshold_value |
Deprecated. |
meta_data |
data.frame old name for |
meta_data_v2 |
character path to workbook like metadata file, see
|
Details
Not yet described
Value
The function returns two data frames, 'SummaryTable' and 'SummaryData', that differ only in the names of the columns.