Exclude statement

 Exclude
   Rule=All|Neg|Add|Expand|Equal|Greater|Less|Cluster|Ons|Offs|Begs
     |Ends||Max|Min|LocalMax|LocalMin|LocalExtr|Interval|Count
   [Crit=criterion_expression]

Type conventions and statement syntax are explained in the Glossary.

Modifies the bit values in the active selection mask, that is changes the selection state of the cells in the active data matrix according to the rule specified in the Rule parameter of the statement.

Parameters...

Rule
Radio button parameter indicating the rule to be used to change the selection state of the cells in the matrix. There is no default, specify one of the following options:

• All = deselect all cells.
• Neg = invert the selection state of all cells.
• Add = look for clusters of cells that are not selected. Deselect more cells at the end of each cluster to expand it. The absolute value of Crit specifies the number of cells to be deselected per cluster. Clusters are expanded in upstream direction if Crit<0, else downstream.
• Expand = look for clusters of cells that are not selected. Deselect more cells at the end of each cluster to expand it by the number of seconds specified by the absolute value of Crit. Clusters are expanded in upstream direction if Crit<0, else downstream.
• Equal = deselect all cells whose value equals Crit. Do not change the state of empty cells or of cells that do not meet the criterion.
• Greater = deselect all cells whose value is greater than Crit. Do not change the state of empty cells or of cells that do not meet the criterion.
• Less = deselect all cells whose value is less than Crit. Do not change the state of empty cells or of cells that do not meet the criterion.
• Cluster = look for clusters of selected cells. Of each cluster found, calculate the sum of the values of non-empty cells. Deselect all cells of the cluster if the sum is equal or greater than Crit, else keep the cells selected.
• Ons = look for clusters of selected cells. Deselect the first cell of each cluster found, but never deselect the first cell in a column.
• Offs = look for clusters of selected cells. Deselect the last cell of each cluster found, but never deselect the last cell in a column.
• Begs = look for clusters of selected cells. Deselect the first cell of each cluster no matter whether it is the first in a column or not.
• Ends = look for clusters of selected cells. Deselect the last cell of each cluster no matter whether it is the last in a column or not.
• Max = look for clusters of selected cells. Of each cluster deselect all cells with the largest value in the cluster.
• Min = look for clusters of selected cells. Of each cluster deselect all cells with the smallest value in the cluster.
• LocalMax = look for local maxima and minima of cell values in each column. Deselect all maxima that differ by Crit or more from at least one of the framing local minima. Do not change the state of the remaining cells.
• LocalMin = look for local maxima and minima of cell values in each column. Deselect all minima that differ by Crit or more from at least one of the framing local maxima. Do not change the state of the remaining cells.
• LocalExtr = look for local maxima and minima of cell values in each column. Deselect all minima that differ by Crit or more from at least one of the framing local maxima. Then deselect all maxima that differ by Crit or more from at least one of the framing local minima. Do not change the state of the remaining cells.
• Interval = assuming that cell values represent cumulative distance moved, deselect equidistant points at the interval specified by Crit. The first non empty cell is always deselected. The selection status of cells not falling next to interval borders is not changed. By analogy, the operation can be applied to any monotonously ascending data.
• Count = deselect the first Crit selected cells without changing the status of all other cells. If Crit<0 deselect the last [Crit] selected cells. Contiguous repetitions of cell values without interspersed empty cells are counted as one cell. This rule is intended for use with data matrices representing field entries (Matrix statement with Data=Field).

Crit
Name parameter indicating the criterion for rules Equal, Add, Expand, Greater, Less, Cluster, LocalMax, LocalMin, LocalExtr, and Count. There is no default: a criterion must be specified if any of these rules is used. It may be a constant, a data array name or an expression of array names or array names and constants. Valid array names are a1 through a10. If an expression is specified, the arrays are combined element by element.

Note that...

You must build a selection mask using the Include and/or Exclude statements, before you can define any variables by executing variable definition file statements. Wintrack maintains only one active mask and all Exclude or Include statements you use will affect this same selection mask. The Exclude and Include statements never modify the content of the cells in the active data matrix. Before you can use a data array as criterion, you must fill it with valid data using a Collapse statement.

Additional information...

• Managing custom variable definition files provides general information on the management of custom variable definition files.
• The Flowchart of advanced data analysis gives a synopsis of data and variable types.
• There is a topic describing how to build a custom variable definition file.
• There is a list of all available variable definition statements.
• Using the Memory statement you can build collections of data matrices and selection masks for later reuse in other variables.
• See Analyze Case Document command for basic information on that command.
• Inside case documents provides advanced information on case documents.