Data Standardize

The Data Standardize normalization process standardizes values of numeric variables in a SAS data set. A large number of potential methods are available for performing the standardization .

What do I need?

One data set is required for this process:

•	The SAS Input Data Set contains all of the numeric data to be analyzed.

Three other data sets can be specified:

•	The Standardization Statistics Input SAS Data Set , needed when DATASET is chosen as the Standardization Method . It contains location and scale estimates by which to standardize the Input SAS Data Set .

•

The Experimental Design Data Set (EDDS) . This data set tells how the experiment was performed, providing information about the columns in the input data set. Note that one column in the EDDS must be named ColumnName , and the values contained in this column must exactly match the column names in the input data set.

•	The Subset Data Set to Use for Normalization (only available in column standardization). It enables a subset of features to be used to normalize all of the data.

The adsl_dii_phlebitis.sas7bdat file (found in the \LifeSciences\Sample Data\Nicardipine\ADaM directory included with JMP Genomics and JMP Clinical, and described in Nicardipine ) serves as an example input SAS data set, and is shown below .

For detailed information about the files and data sets used or created by JMP Life Sciences software, see Files and Data Sets .

Output/Results

Refer to the Data Standardize output documentation for detailed descriptions of the output of this process.