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:

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

Three other data sets can be specified:

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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.

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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.

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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 Genomics software, see Files and Data Sets.

Output/Results

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