The TRANSFORM statement lists the transformations and their associated variables to be transformed. The options are transformation options that provide additional information for the transformation.
The MI procedure assumes that the data are from a multivariate normal distribution when either the regression method or the MCMC method is used. When some variables in a data set are clearly non-normal, it is useful to transform these variables to conform to the multivariate normality assumption. With a TRANSFORM statement, variables are transformed before the imputation process, and these transformed variable values are displayed in all of the results. When you specify an OUT= option, the variable values are back-transformed to create the imputed data set.
The following transformations can be used in the TRANSFORM statement:
specifies the Box-Cox transformation of variables. The variable Y is transformed to , where is a constant such that each value of must be positive. If the specified constant , the logarithmic transformation is used.
The following options provide the constant and values in the transformations.
For example, the following statement requests that variables , a logarithmic transformation for the variable y1, and , a power transformation for the variable y2, be used in the imputation:
transform log(y1) power(y2/c=1 lambda=.5);
If the MU0= option is used to specify a parameter value for a transformed variable, the same transformation for the variable is also applied to its corresponding MU0= value in the test. Otherwise, is used for the transformed variable. See Example 56.10 for a usage of the TRANSFORM statement.