outputLab

Creates output labels for the randomized groups.

Provides randomization using permutation for applications.  To provide a Quality Control (QC) check, QC samples can be randomized within strata.  A second function allows for the ability to ”switch” samples to meet set requirements and perform a certain amount of minimization on these switches.  The functions are flexible for users by specifying strata size and number of QC samples per strata.  The randomization meets the following requirements
• QC sample requirements: QC samples not adjacent, QC
samples from same mother must follow certain patterns.
• Matched sample sets must be within a single strata, and next
to each other.

Michelle Mellers

permRand

Permutation Randomization

Thaddeus Haight

outputLab function

<dl><dt>dataOut</dt>
<dd>Dataset to be formatted for packing list.</dd>
<dt>blind</dt>
<dd>Indicator 0/1 select if a blinded (1) or unblinded(0) packing list is to be generated.</dd>
<dt>origP</dt>
<dd>Indicator, 0/1, inclusion of the original packing location (1) or deletion of the packing location (0).</dd>
<dt>maxRows</dt>
<dd>Maximum row for the output dataset.</dd>
<dt>maxCols</dt>
<dd>Maximum column for the output dataset.</dd>
<dt>newPack</dt>
<dd>0/1 indicator to generate new packing locations.</dd></dl>

Arguments

Output labels. — outputLab

<dl>

<dt>dataOut</dt>
<dd>Dataset to be formatted for packing list.</dd>


<dt>blind</dt>
<dd>Indicator 0/1 select if a blinded (1) or unblinded(0) packing list is to be generated.</dd>


<dt>origP</dt>
<dd>Indicator, 0/1, inclusion of the original packing location (1) or deletion of the packing location (0).</dd>


<dt>maxRows</dt>
<dd>Maximum row for the output dataset.</dd>


<dt>maxCols</dt>
<dd>Maximum column for the output dataset.</dd>


<dt>newPack</dt>
<dd>0/1 indicator to generate new packing locations.</dd>

</dl>

outputLab: Output labels.

Description

Usage

Value

Arguments

Examples