Due Date: 10/06/05
PM 536: Lab 5
Data Manipulation and Scale Creation
These exercises are designed to demonstrate techniques for inspecting,
cleaning, labeling and manipulating data. Scale building is also demonstrated; it
is a technique that enables the data analyst to provide more reliable and valid
measures of study concepts such as attitude or knowledge. Chapters 8 & 9 will
provide useful background for this lab.
1. Creating an attitude scale by adding
Begin by opening a log in which you can save your results for this laboratory
exercise.
1. Use the “evaltxt2” data from blackboard. (This dataset is a 2-wave cross-
sectional survey administered to students in undergraduate courses half of whom
were exposed to a nutrition intervention.)
2. Inspect the attitude items in the data that are questions 1 through 14. Use
the “proc freq” command in SAS or “d q1-q14*” in STATA to see the
variable names and labels. Verify that the data are valid by inspecting the
range and number of observations for each.
3. Create a new variable by summing the responses to these 14 questions
with the following command:
attit_1=q1+q2+q3+q4+q5+q6+q7+q8+q9+q10+q11+q12+q13+q14
Notice that this command might generate some missing values if a respondent
has missing data for any one of the questions. (Later we’ll review ways to avoid
having missing cases in this type of situation.)
4. What is the mean, mode, range, and standard deviation of the new
variable attitude?
5. Label the new variable with a descriptor.
6. Now perform the same functions on a second attitude variable called
“att_1" consisting of question 1 through 6. Find the mean, mode range
and standard deviation of the new variable that you created.
