How To Fix /SAPAPO/MLR_IN_UNIV003 - Causal variable &1 considered (t-test disregarded)

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/MLR_IN_UNIV -

• Message number: 003

• Message text: Causal variable &1 considered (t-test disregarded)

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /SAPAPO/MLR_IN_UNIV003 - Causal variable &1 considered (t-test disregarded) ?

  The SAP error message /SAPAPO/MLR_IN_UNIV003 Causal variable &1 considered (t-test disregarded) typically occurs in the context of SAP Advanced Planning and Optimization (APO) when performing regression analysis or model building for forecasting. This message indicates that a specific causal variable (denoted by &1) has been included in the model, but the t-test for its significance has been disregarded.
  Cause:
  
  Insufficient Data: The t-test may have been disregarded due to insufficient data points for the causal variable. If there are not enough observations, the statistical test cannot be reliably performed.
  Multicollinearity: If the causal variable is highly correlated with other variables in the model, it may lead to unreliable estimates, causing the t-test to be disregarded.
  Model Specification Issues: The model may not be correctly specified, leading to issues in estimating the significance of the causal variable.
  Data Quality Issues: Missing values, outliers, or incorrect data types can affect the analysis and lead to the t-test being disregarded.
  
  Solution:
  
  Check Data Quality: Ensure that the data for the causal variable is complete, accurate, and free from outliers. Clean the data if necessary.
  Increase Data Points: If possible, gather more historical data to provide a larger sample size for the analysis.
  Review Multicollinearity: Analyze the correlation between the causal variable and other variables. If multicollinearity is present, consider removing or combining variables.
  Model Re-specification: Review the model specification to ensure that it is appropriate for the data and the relationships being analyzed. Adjust the model as needed.
  Consult Documentation: Refer to SAP documentation or help resources for specific guidelines on handling causal variables and regression analysis in APO.
  
  Related Information:
  
  Statistical Significance: Understanding the importance of t-tests in regression analysis is crucial. A t-test assesses whether the coefficients of the variables are significantly different from zero.
  APO Documentation: SAP provides extensive documentation on APO functionalities, including regression analysis and causal forecasting. Reviewing this documentation can provide insights into best practices and troubleshooting steps.
  SAP Community: Engaging with the SAP community forums can be beneficial for finding solutions to similar issues encountered by other users.
  
  If the problem persists after trying the above solutions, it may be helpful to consult with an SAP expert or support for further assistance.