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In this article

1. Create a Measure
2. Define the Expression
   1. If Statements
   2. Count of Responses
   3. Arithmetic Calculations
   4. Aggregation Types (Multi-level only)

1. Create a Measure

To create a measure, you first need to select the desired position in the project tree. From here choose new measure under construct from the design menu. Learn more about the design menu and then define the expression using the expression editor.

• You can create new measures from an existing measure, or weight, values, or by entering values explicitly into the definition.
• Measures contain a single value for each respondent.
• Records to be excluded from the measure’s count need to be assigned a NULL value. 

• Select a position in the project tree
• Click new measure and type a name
• Press enter to open the expression editor where you will define the measure

2. Define the Expression

The following options are used when defining a measure:

1. If Statements
2. Count of Responses
3. Calculations
4. Aggregate Types (Multi-level only)

a. If Statements

If statements are used to populate a new measure or weight with a different value depending on specific conditions.

If statement syntax

• The syntax for the if statement is:

 if (Logic_Test, Value_if_True, Value_if_False)

• The syntax for a nested if statement is:

if (Logic_Test, Value_if_True, if (Logic_Test, Value_if_True, Value_if_False))

Example

Let's assume you want to calculate the NPS based on the "Likely to recommend" question.  For this, you need to assign the appropriate -100, 0, and 100 values to each respondent.  The records to be excluded from the measure’s count need to be assigned a NULL value.

The syntax in this case would be:

if(Recommend.(9 or 10) ,100,if(Recommend.(7 or 8), 0,if(Recommend.(0,1,2,3,4,5,6),-100,null))) 

Where:

• Logic Test - Likely to recommend
• Value if true - Factor to be applied (-100, 0 or 100)
• Value if false - Null

Now, let's assume we want to create a separate NPS for only Females. Your logic test needs to consider this condition: "Likely to recommend" question and Gender.

if(Recommend.(9 or 10) and Gender.Female, 100,if(Recommend.(7 or 8) and Gender.Female, 0,if(Recommend.(0,1,2,3,4,5,6) and Gender.Female,-100,null))) 

• Logic Test - Likely to recommend and Gender
• Value if true - Factor to be applied (-100, 0 or 100)
• Value if false - Null

b. Count of Responses

The count function is used to define a new element or a new measure by counting the number of responses given to the items listed in a comma-separated list.  The count function creates a numeric value from an existing axis, element or measure.  Learn more about the Count function

Count function syntax for measures

a) Counting all responses in a standard axis.

With this syntax, the values count returns are the number of elements each respondent responded to.  Note, only multiple-response variables will ever give a count greater than 1.

• Measure: count (AxisName1) 

b) Count function with Boolean logic can be used to count whether a respondent mentioned at least one response to a specific set of items.

Using count  ( _ or _ or _ )

With this syntax, the values count returns are 0 and 1. The maximum count the expression returns is 1.

• Measure:  count (AxisName1.(ElementName1 or  ElementName2  or   Element 3)) 

Using  count ( _ , _ , _ )

With this syntax, you can sum together counts from a specific set of items.  It evaluates the number of items a respondent has answered and adds the count for each. The maximum count the expression returns is the max number of possible responses.

• Measure:  count (AxisName1.ElementName1 ,  AxisName1.ElementName2  ,   AxisName1.ElementName3) 

Examples

Let's assume you want to find out the number of activities during a trip, excluding the element "None of these".  In this case, the best syntax to use is count ( _ , _ , _ ). This will just take into account the elements you want to include in the calculation. 

c. Calculations

Measures can also be defined using calculations, i.e.,

• Addition using +
• Subtraction using -
• Multiplication using *
• Division using /

Example

Let's assume you want to create an "Other Costs" measure containing the amount spent that wasn’t on airfares or packages, i.e. the amount left after subtracting airfares and packages from total spend.

d. Aggregation Types (Multi-level only)

Four aggregate types are available: Sum, Avg, Min and Max. When creating an aggregate measure or weight, for example, at the parent level, the calculations are as follows:

• Sum – all records at the child level are added together to become the aggregate result at the parent level.
• Avg – all records at the child level are added together and divided by the number of records to become the aggregate result at the parent level.
• Min – just the lowest record at the child level is used as the aggregate result at the parent level.
• Max – just the highest record at the child level is used as the aggregate result at the parent level.

Example

Let's create an "Average Occasions" measure at the parent level using the occasion data from the child level.

• Add a new measure at the parent level and define it.
• Select the aggregate type you need.
• Save or apply the expression.

Where to from here?

Learn more about different construction types:

• Measure Groups
• Headings
• Expression Editor
• Standard Axes and Elements
• Weights
• Grids