## Adds a Parameter Computed from the Analysis Value of Other Parameters

### Description

Adds a parameter computed from the analysis value of other parameters. It is expected that the analysis value of the new parameter is defined by an expression using the analysis values of other parameters. For example mean arterial pressure (MAP) can be derived from systolic (SYSBP) and diastolic blood pressure (DIABP) with the formula

MAP = \frac{SYSBP + 2 DIABP}{3}

### Usage

derive_param_computed(
dataset,
by_vars,
parameters,
analysis_value,
set_values_to,
filter = NULL,
constant_by_vars = NULL,
constant_parameters = NULL
)


### Arguments

 dataset Input dataset The variables specified by the by_vars parameter, PARAMCD, and AVAL are expected. The variable specified by by_vars and PARAMCD must be a unique key of the input dataset after restricting it by the filter condition (filter parameter) and to the parameters specified by parameters. by_vars Grouping variables For each group defined by by_vars an observation is added to the output dataset. Only variables specified in by_vars will be populated in the newly created records. Permitted Values: list of variables parameters Required parameter codes It is expected that all parameter codes (PARAMCD) which are required to derive the new parameter are specified for this parameter or the constant_parameters parameter. Permitted Values: A character vector of PARAMCD values analysis_value Definition of the analysis value An expression defining the analysis value (AVAL) of the new parameter is expected. The analysis values of the parameters specified by parameters can be accessed using ⁠AVAL.⁠, e.g., AVAL.SYSBP. Permitted Values: An unquoted expression set_values_to Variables to be set The specified variables are set to the specified values for the new observations. For example vars(PARAMCD = "MAP") defines the parameter code for the new parameter. Permitted Values: List of variable-value pairs filter Filter condition The specified condition is applied to the input dataset before deriving the new parameter, i.e., only observations fulfilling the condition are taken into account. Permitted Values: a condition constant_by_vars By variables for constant parameters The constant parameters (parameters that are measured only once) are merged to the other parameters using the specified variables. (Refer to Example 2) Permitted Values: list of variables constant_parameters Required constant parameter codes It is expected that all the parameter codes (PARAMCD) which are required to derive the new parameter and are measured only once are specified here. For example if BMI should be derived and height is measured only once while weight is measured at each visit. Height could be specified in the constant_parameters parameter. (Refer to Example 2) Permitted Values: A character vector of PARAMCD values

### Details

For each group (with respect to the variables specified for the by_vars parameter) an observation is added to the output dataset if the filtered input dataset contains exactly one observation for each parameter code specified for parameters.

For the new observations AVAL is set to the value specified by analysis_value and the variables specified for set_values_to are set to the provided values. The values of the other variables of the input dataset are set to NA.

### Value

The input dataset with the new parameter added. Note, a variable will only be populated in the new parameter rows if it is specified in by_vars.

### Author(s)

Stefan Bundfuss

BDS-Findings Functions for adding Parameters/Records: default_qtc_paramcd(), derive_extreme_records(), derive_param_bmi(), derive_param_bsa(), derive_param_doseint(), derive_param_exist_flag(), derive_param_exposure(), derive_param_first_event(), derive_param_framingham(), derive_param_map(), derive_param_qtc(), derive_param_rr(), derive_param_wbc_abs(), derive_summary_records()

### Examples

# Example 1: Derive MAP
~USUBJID, ~PARAMCD, ~PARAM, ~AVAL, ~AVALU, ~VISIT,
"01-701-1015", "DIABP", "Diastolic Blood Pressure (mmHg)", 51, "mmHg", "BASELINE",
"01-701-1015", "DIABP", "Diastolic Blood Pressure (mmHg)", 50, "mmHg", "WEEK 2",
"01-701-1015", "SYSBP", "Systolic Blood Pressure (mmHg)", 121, "mmHg", "BASELINE",
"01-701-1015", "SYSBP", "Systolic Blood Pressure (mmHg)", 121, "mmHg", "WEEK 2",
"01-701-1028", "DIABP", "Diastolic Blood Pressure (mmHg)", 79, "mmHg", "BASELINE",
"01-701-1028", "DIABP", "Diastolic Blood Pressure (mmHg)", 80, "mmHg", "WEEK 2",
"01-701-1028", "SYSBP", "Systolic Blood Pressure (mmHg)", 130, "mmHg", "BASELINE",
"01-701-1028", "SYSBP", "Systolic Blood Pressure (mmHg)", 132, "mmHg", "WEEK 2"
)

derive_param_computed(
by_vars = vars(USUBJID, VISIT),
parameters = c("SYSBP", "DIABP"),
analysis_value = (AVAL.SYSBP + 2 * AVAL.DIABP) / 3,
set_values_to = vars(
PARAMCD = "MAP",
PARAM = "Mean Arterial Pressure (mmHg)",
AVALU = "mmHg"
)
)

# Example 2: Derive BMI where height is measured only once
~USUBJID, ~PARAMCD, ~PARAM, ~AVAL, ~AVALU, ~VISIT,
"01-701-1015", "HEIGHT", "Height (cm)", 147, "cm", "SCREENING",
"01-701-1015", "WEIGHT", "Weight (kg)", 54.0, "kg", "SCREENING",
"01-701-1015", "WEIGHT", "Weight (kg)", 54.4, "kg", "BASELINE",
"01-701-1015", "WEIGHT", "Weight (kg)", 53.1, "kg", "WEEK 2",
"01-701-1028", "HEIGHT", "Height (cm)", 163, "cm", "SCREENING",
"01-701-1028", "WEIGHT", "Weight (kg)", 78.5, "kg", "SCREENING",
"01-701-1028", "WEIGHT", "Weight (kg)", 80.3, "kg", "BASELINE",
"01-701-1028", "WEIGHT", "Weight (kg)", 80.7, "kg", "WEEK 2"
)

derive_param_computed(
by_vars = vars(USUBJID, VISIT),
parameters = "WEIGHT",
analysis_value = AVAL.WEIGHT / (AVAL.HEIGHT / 100)^2,
set_values_to = vars(
PARAMCD = "BMI",
PARAM = "Body Mass Index (kg/m^2)",
AVALU = "kg/m^2"
),
constant_parameters = c("HEIGHT"),
constant_by_vars = vars(USUBJID)
)