validate_adam

Validates a data frame against a specific ADaM dataset specification. Similar to
<code>validate_sdtm()</code> but uses ADaM metadata and treats Conditional variables differently.

internal

A general-purpose toolkit for comparing any two data frames
with optional 'CDISC' (Clinical Data Interchange Standards Consortium)
validation for clinical trial data. Core comparison functions work on
arbitrary datasets: variable-level and observation-level comparison, data
type checking, metadata attribute analysis (types, labels, lengths,
formats), missing value handling, key-based row matching, tolerance-based
numeric comparisons, and group-wise comparisons. Optional z-score
outlier detection is available when enabled. When working with clinical
data, the package additionally
validates 'SDTM' (Study Data Tabulation Model) and 'ADaM' (Analysis Data
Model) datasets against CDISC standards (SDTM IG 3.3/3.4, ADaM IG
1.1/1.2/1.3), automatically detecting domains and flagging non-conformant
variables. Generates unified comparison reports in text or HTML format
with interactive dashboards. For CDISC standards, see
<https://www.cdisc.org/standards>.

Siddharth Lokineni

clinCompare

Dataset Comparison with 'CDISC' Validation for Clinical Trial
Data

validate_adam function

<dl><dt>df</dt>
<dd>A data frame to validate.</dd>
<dt>domain</dt>
<dd>Character string specifying the ADaM dataset name (e.g., "ADSL", "ADAE").</dd></dl>

Arguments

Validate ADaM Compliance — validate_adam

<dl>

<dt>df</dt>
<dd>A data frame to validate.</dd>


<dt>domain</dt>
<dd>Character string specifying the ADaM dataset name (e.g., "ADSL", "ADAE").</dd>

</dl>

validate_adam: Validate ADaM Compliance

Description

Usage

Value

Arguments

Details