____________________________________________________________________________________________
Part I
As in the first lab, start up SPSS and start a new data file that you add data to for this lab. Create participant code numbers for the first 10 cells (variable 1) and label each of the next 5 variables with Q1, Q2, Q3, Q4, & Q5.
For this lab we will make use of this
mini-questionnaire called the
psyc
201 sociability questionnaire.
As such we are trying to consider how sociable people are with this scale.
Add two more questions that you think may represent social styles of behaviour before you collect some answers from people in your group and others outside on campus or in other groups.
Next, fill in the data set for 10 to 15 participants with their answers to 5 (+2) questions from the questionnaire.
We will then examine some functions for changing variable names and creating new variables from old ones using the Transform function.
Next we will examine the relationships among the variables collected along with the new variable that we created using reliability analysis.
Changing Variable
Names
You can switch between
data and variable
views by clicking on the tab at the bottom left of your
SPSS data window.
When inside the variable view you can click on the names and change them. At this point change the names from Q1---Q7 to names that are meaningful to you (that briefly summarize the variables).
You can also adjust the number of decimals, variable type, etc. Try this out with your first data set, (later you may repeat this in part II and then perform a reliability analysis with another data file).
Transformation
Once you have your data in a standard format
Add a new variable called "total" and then perform a transform where you compute the new variable by adding Q1 to Q5. Save your data file.
Reliability Analysis
Click on Analyze then Scale then Reliability Analysis
Add each of the original
variables (Q1-Q5) (except for total and the two new questions) to the
items box
(highlight then
click the arrow to move them to the left)
Check to see if the
model tab is on
alpha
and then click on the statistics
button and check the following boxes:
descriptives for:
click scale, scale if item deleted;
then under
summaries:
click
means and
variances;
then under
inter-item:
click correlations
then click continue to close the statistics
window.
Click OK and let the
analysis run
(this will take a few seconds and the output window
will open in front of you)
Scroll down the output window and
look over the tables of statistics,
in particular the alpha,
corrected item-total correlation, squared multiple
correlation, and the alpha if item deleted.
(ask for help if you cannot read the analysis results.
Note: you may need to read the section in the book on
reliability
and Cronbach's alpha to make sense of this
data)
Once this analysis has
run and you have looked over the results try it again adding all seven variables
(include the two new ones) and run it again. Alternatively, add these two new
variables and take out some of the first variables. Play around with the
variables that you add in and take out to see what happens to alpha.
Create a word document where you answer the following questions and copy and paste your results from the output relevant to each question to your word doc that you will place in the drop box for Lab 5.
What were the specific
questions that you added (Q6 & Q7)?
What can you say about the reliability of the total scale
?
To raise internal reliability what items would you change
or delete?
Which item would you use as the best predictor of the
total score?
Why?
Which items would make a good sub-scale if placed
together?
Why?
(consider
these first for the data set of 5 questions then report the results from the
second set with 7 questions )
Part II - Optional
Go to
data
website and download the following data file
to your local area (201 folder).
INTDAT.xls
Repeat Part I one using this data files. This set involves scores from a range of people on their score for a variable called Integration. What this means is that those scoring higher are expected to maintain both their traditional cultural ways as well as "host" or mainstream cultural practices.
open the first data file using
SPSS and repeat part one transformation and reliability analysis with this data.
(Note when opening this file
make sure the the box for "read variable names" is NOT checked, as there are no
names in this excel file. Also you may need to open it first with excel and then
save it as 97-2003 workbook. -as in Lab2)