Author: Ed Nelson
Department of Sociology, M/S SS97
California State University Fresno
Fresno, CA 93740
Phone: 559-278-2275
Email: .

Please contact the author for additional information.

Note to the instructor: The data set used in this exercise is gss0204_subset_for_classes.sav which is a combination of the 2002 and 2004 General Social Surveys.  (Some of the variables in the GSS have been recoded to make them easier to use and some new variables have been created.)  The data have been weighted according to instructions from the National Opinion Research Center.  This exercise uses RECODE and CROSSTABS in SPSS to explore relationships among variables.  In CROSSTABS, students are asked to use percentages, Chi Square, and an appropriate measure of association.  Two-variable and three-variable relationships will be explored, along with the concepts of explanation, spuriousness, and replication.  A good reference on using SPSS is SPSS for Windows Version 16.0 A Basic Tutorial by Linda Fiddler, Laura Hecht, Edward Nelson, Elizabeth Nelson and Jim Ross.  To order this book, call McGraw-Hill at 1‑800‑338‑3987.  The ISBN is 0-07-353833-7.  There is an online version of the book at http://www.ssric.org/trd/spss16.  You have permission to use this exercise and to revise it to fit your needs.  Please send a copy of any revision to the author.

Goals of Exercise

The goal of this exercise is to explore the relationship between religiosity and other variables using crosstabulation.  This exercise will focus on two-variable relationships and then on three-variable relationships.  The concepts of explanation, spuriousness, and replication will also be explored.

I’m attaching the following files:

• A Word document that contains the codebook for the General Social Survey 2002-2004 subset
• Data for the General Social Survey 2002-2004 subset (name of data file is gss0204_subset_for_classes.sav). Note: to run this file, change the extension from “.txt” to “.sav” and open it in SPSS as a .sav file.
• An SPSS syntax file for use with the General Social Survey 2002-2004 subset (name of data file is spss_syntax_for_relg2r.sps). Note: to run this file, change the extension from “.txt” to “.sps” and open it in SPSS as a syntax (.sps) file.

Part I--Recoding

We’re going to use the General Social Survey (GSS) for this exercise.  The GSS is a national probability sample of adults in the United States conducted by the National Opinion Research Center.  For this exercise we’re going to use a data set that combines the 2002 and 2004 surveys. Your instructor will tell you how to access this data set.

Religiosity is the strength of an individual’s attachment to his or her religious affiliation.  Several questions on the GSS are possible indicants of religiosity.  One of the questions asks respondents to estimate the strength of their religious affiliation.  This variable in the GSS is called RELITEN.  Respondents were also asked how often they attend religious services (ATTEND) and how often they pray (PRAY).  These are all possible indicants of religiosity, but we’re going to use ATTEND in this exercise.

Before you start, run FREQUENCIES in SPSS to get the frequency distributions for ATTEND.

The variable ATTEND has nine categories.  Let’s start by reducing the number of categories.  We’ll combine every week (value 7) and more than once a week (8) into one category and give this category a value of 1.  Combine once a month (4), two to three times a month (5), and nearly every week (6) into another category and give this a value of 2.  Finally, combine never (0), less than once a year (1), once a year (2), and several times a year (3) into another category and give this a value of 3.  Now we have three categories--often (1), sometimes (2), and infrequently (3).  Be sure to add value labels to make the output easier to read.  (Hint: When you use RECODE in SPSS, you can recode in two different ways—into the same variable or into different variables.  If you recode into the same variable, be careful.  It’s easier, but if you make a mistake, you will not be able to go back and recode it again.  You will have to close SPSS without saving the data set and then reopen the data set to get a fresh, clean copy of the data.  So for this exercise recode into different variables.  You’ll have to give your recoded variable a new name.  Call this one ATTEND1.)

Now that you have recoded these variables, run FREQUENCIES in SPSS to get a frequency distribution for ATTEND1.  Compare this distribution to the distribution you ran before you started to see if you made any mistakes.  If you made a mistake, redo this part of the exercise.  If you recoded into the same variable, you will have to exit SPSS (or close your file) being sure NOT to save it.  Then get back into SPSS and open the gss0204_subset_for_classes.sav file again.  The reason for this is that you have altered the coding of these three variables and will have to get another copy of the data file to start over.  If you saved the data file, then you would have written over the original copy.  So be careful.  That’s why we said to recode into different variables in this exercise. 

Part II—Analysis of two variable relationships

Let’s start by exploring the relationship between our measure of religiosity and whether or not respondents think pornography ought to be illegal to all or only illegal for those under the age of 18. The variable PORNLAW includes the respondents answers to the question “Which of these statements comes closest to your feelings about pornography laws?  There should be laws against the distribution of pornography whatever the age.  There should be laws against the distribution of pornography to persons under 18.  There should be no laws against the distribution of pornography.”

Use CROSSTABS in SPSS to get the crosstabulation of ATTEND1 and PORNLAW.  Be careful when you select the independent and dependent variables.  Be sure to select the correct percentages, Chi Square, and an appropriate measure of association.  Write a paragraph or two describing the relationship between these variables using all this information.

Part III—Analysis of two variable relationships continued

We know that there are other variables related to ATTEND1 and PORNLAW.  For example, other research has shown that women are more likely than men to attend church.  Perhaps women are also more likely than men to feel that pornography ought to be illegal to everyone.  Let’s see if we find these relationships in our data.

Use CROSSTABS to get the crosstabulation of SEX and ATTEND1 and the relationship of SEX and PORNLAW.  Be sure to select the proper independent and dependent variables and to ask for the correct percentages, Chi Square, and an appropriate measure of association.

Write a paragraph or two describing the relationships you find.  Were they what you expected to find?

Part IV—Analysis of multivariate relationships

Perhaps the reason that more religious people are more likely to feel that pornography ought to be illegal to all regardless of age is that women are more religious than men and women are also more likely to feel that pornography ought to be illegal to everyone.  If this was true and we were to take the effect of gender out of the relationship, then we would expect the relationship between ATTEND1 and PORNLAW to disappear (or to be reduced considerably). 

To check on this, let’s do a three-variable table.  Your independent variable would be ATTEND1; your dependent variable would be PORNLAW; your control (or test) variable would be SEX.  Be sure to get the correct percentages, Chi Square, and an appropriate measure of association.

If the relationship between ATTEND1 and PORNLAW goes away for both men and women (or decreases sharply), then we would say the relationship was spurious and that we have explained away the relationship between religiosity and feelings about pornography laws.  This is often referred to as explanation. 

If the relationship between ATTEND1 and PORNLAW does not change when we control for sex, then we would say that we have replicated the relationship.  The control variable has not affected the relationship between the independent and dependent variables.  We call this replication because the relationship between ATTEND1 and PORNLAW has been replicated (or repeated) for both men and women.

Write a paragraph or two describing what you found when you controlled for gender.  Use the percentages, Chi Square, and measure of association to help interpret your findings.