Religion_1SPR – Religious Similarity and Dissimilarity between Respondent and Spouse or Partner

Note to the Instructor: This is the first in a series of three exercises that focus on religious similarity and dissimilarity between respondent and spouse/partner.  We'll compare the respondent's religious preference with spouse's or partner's preference.  In these exercises we're going to analyze data from the Pew 2014 Religious Landscape Survey conducted by the Pew Research Center.  We're going to use SPSS to analyze the data.  A weight variable is automatically applied to the data set so it better represents the population from which the sample was selected.  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 so I can see how people are using the exercises. Please contact the author for additional information.

Goal of Exercise

The goal of this exercise is to explore religious similarity and dissimilarity between respondent and spouse or partner.  We'll compare the respondent's religious preference with spouse's or partner's preference.  In the next exercise (Religion_2SPR) we'll develop an overall measure of religious similarity and look more closely at respondents who are not similar to their spouses and partners in religious preference. 

Part I – The Data Set We'll be Using

The Pew Research Center has conducted a number of surveys that deal with religion.  Two of these surveys are the Religious Landscape Surveys conducted in 2007 and then repeated in 2014.  They were very large telephone surveys of about 35,000 adults in the United States.   For more information about the surveys, go to their website

We'll be using a subset of the 2014 survey in this exercise which I have named Pew_2014_Religious_Landscape_ Survey_subset_for_classes.sav.  For the purposes of these exercises I selected a subset of variables from the complete data set.  I recoded some of the variables, created a few new variables, and renamed the variables to make them easier for students to use.  There is a weight variable which should always be used so that the sample will better represent the population from which the sample was selected.  To open the data set in SPSS, just double click on the file name.[1]  Your instructor will tell you where the file is located.

Part II – Measuring Religious Preference

Religious preference refers to the religion with which respondents and their spouses/partners identify.  The Pew survey asked, "What is your present religion, if any?  Are you Protestant, Roman Catholic, Mormon, Orthodox such as Greek or Russian Orthodox, Jewish, Muslim, Buddhist, Hindu, atheist, agnostic, something else, or nothing in particular?"  The same question was asked about their spouse or partner.

Now that you have opened the data set, run a frequency distribution for the variable R1 which is the name of one of the variables we will be using.  The variable name starts with the letter R which tells you that this variable describes the respondent's religious preference.  Some of you have used SPSS, the statistical package we're using, and know how to get a frequency distribution.  Others of you are new to SPSS.  There is a tutorial that you can use to learn how to get a frequency distribution.  The tutorial is freely available on the Social Science Research and Instructional Center's website.  Chapter 1 of the tutorial gives you a basic overview of SPSS and frequency distributions are covered in Chapter 4. 

It's very easy to get frequency distributions.  Once you have opened the data set in SPSS, look on the menu bar at the top and click on "Analyze."  This will open a drop-down menu.  Click on "Descriptive Statistics" and then on "Frequencies."  You screen should look like Figure 1.

Title: Figure 1 - Description: This is the SPSS dialog box for Frequencies.

Figure 1

Notice that the list of all variables is in the pane on the left.  I scrolled down to the variables that start with R (i.e., R1 through R7).  Select R1 by clicking on it and then click on the arrow pointing to the right.  This will move R1 into the "Variable(s)" box.  Your screen should look like Figure 2.

Title: Figure 2 - Description: This is the SPSS dialog box for Frequencies with R1 selected.

Figure 2

Now all you have to do is to click on "OK" to get your frequency distribution.  (Don't include this table in your paper.)  Your screen should look like Figure 3.  Note that I have only displayed the top part of the distribution because it's a very large table.[2]

Title: Figure 3 - Description: This is the SPSS output displaying the frequency distribution for R1.

Figure 3

Take a few minutes to familiarize yourself with the information in the table.

  • The first column is the value and the value label.  The value "1" refers to all people who answered Protestant.
  • The second column is the number of respondents who said they were Protestants (15,431).
  • The third column converts the frequencies to percents.  Notice that there are two types of missing information – responses that were uninterpretable and those who said they didn't know or refused to answer.  The percent column converts the frequency to a percent by dividing the frequency (15,431) by the total number of cases including those with missing values (35,071).  Carry out the computation for yourself and convince yourself that it is 44.0%.
  • The fourth column converts the frequencies to valid percents by dividing the frequency (15,431) by the number of cases with valid information (34,846).  In other words, it excludes the cases with missing information (225) from the denominator when computing the percent.  Carry out the computation for yourself and convince yourself that it is 44.3%.  This is called the valid percent.  The more missing information there is in the distribution, the greater could be the difference between the percent and the valid percent.  Normally we want to use the valid percents when describing the frequency distribution.
  • The fifth column is the cumulative percent.  Recall that the first twelve categories in the distribution were listed in Figure 3.  The cumulative percent for this twelfth category is 94.4%.  In other words, 94.4% of the cases with valid information selected one of the categories included in the first twelve categories.  You can see where this comes from if you add up the valid percents for the first twelve categories.

Now it's your turn.  The second category in the distribution is Roman Catholic.

  • What is the value for this category?
  • How many respondents said they were Roman Catholic?
  • What is the percent for this category?  What does this mean?
  • What is the valid percent for this category?  What does this mean?
  • Why aren't the percent and valid percents the same?
  • What is the cumulative percent for this category?  What does this mean?

Part III – Measuring Religious Preference for Protestants

One problem with the first question is that over 15,000 respondents said they were Protestant.  We know there are many different types of Protestants so we might want to break Protestants down more finely.  To do this the Pew survey asked another question – "As far as your present religion, what denomination or church, if any, do you identify with most closely?  Just stop me when I get to the right one. Are you Baptist, Methodist, Lutheran, Presbyterian, Pentecostal, Episcopalian or Anglican, Church of Christ or Disciples of Christ, Congregational or United Church of Christ, Holiness, Reformed, Church of God, nondenominational or independent church, something else, or none in particular?"

Run a frequency distribution for R2 which is the name of this variable.  (Don't include this table in your paper.)

This question was only asked of those who said they were Protestant in R1.  Notice that the number of cases with valid information was 15,403 and that there were 28 respondents who said they didn't know or refused to answer.  If you add these two numbers together, you get 15,431 which is the number who said Protestant in R1.  Those who didn't say they were Protestant in the previous question are included in the category that is labeled "system missing." 

The large number of categories in R2 makes it difficult to interpret.  R5 is an attempt to reduce the number of categories.  Run a frequency distribution for R5. (Include this table in your paper.)   Notice that this time Protestants are broken down by religious tradition.  Religious tradition is divided into three categories.

  • Evangelical Protestant tradition
  • Mainline Protestant tradition
  • Historically Black Protestant tradition

To find out what the Pew Center means by these traditions, read the following Pew reports: 

  • Chapter 1 of the full report for the 2014 Religious Landscape Survey on "The Changing Religious Composition of the U.S. Population" and
  • Appendix B to this report on "Classification of Protestant Denominations."

For more information on the difference between the evangelical and the mainline Protestant traditions, read the article by John Green in the PBS Frontline article on "Evangelicals v. Mainline Protestants."  For a history of the black church, read Marilyn Mellowes' article on "The Black Church."

Now it's your turn again.  Write a paragraph explaining in your own words what is meant by these three religious traditions – the Evangelical Protestant tradition, the Mainline Protestant tradition, and the Historically Black Protestant tradition.  Study the frequency distribution carefully and be sure to answer the following questions.  Use the valid percents.

  • What are the five largest religious groups in R5?  Note that this table includes the religiously unaffiliated as a group.  What are the percents for each of these groups?
  • What percent of adults are Christian?  Non-Christian?  For this question be sure to also include Orthodox Christians, Jehovah's Witness, Mormon, and Other Christian as Christian when you compute the percent of adults who are Christian.
  • Which non-Christian group is the largest?  What is the percent for that group?

Part IV – Exploring Religious Similarity and Dissimilarity between Respondent and Spouse

We'll going to compare the respondent's religious preference with the religious preference of their spouse or partner. You already looked at the frequency distribution for R5 which describes respondent's current religious preference.  The variable RS3 refers to the religion of the respondent's spouse or partner.  Respondents who are not married or living with a partner are treated as missing data for RS3 and not included in the frequency distribution.  The letters RS stand for "spouses and partners religious preference." 

Now that we have figured out how to measure religious preference, let's turn to the question of the similarity and dissimilarity of respondent's religious preference and the preference of their spouse or partner.  This represents a shift from what we typically call univariate (i.e., one-variable) analysis to bivariate (i.e., two-variable) analysis.  Frequency distributions look at variables one at a time.  Now we are going to look at the relationship between two variables – respondent's religious preference (R5) and spouse's or partner's preference (RS3).  Crosstabulation looks at variables two at a time.

The statistical tools that we're going to use to explore the relationship between R5 and RR3 are crosstabulation and percents.  We're not going to go into a lot of detail about these tools.  Your instructor will provide that information.   We will talk briefly about how to get SPSS to compute them and how to interpret them. 

Before we look at the relationship between variables, let's talk about independent and dependent variables.  Typically, the dependent variable is whatever you are trying to explain and the independent variable is some variable that you think will help you explain the variation in the dependent variable.  So if you were looking at the relationship between religious preference and how people felt about social issues such as abortion or same-sex marriage, you would want to use religious preference as the independent variable and opinion on abortion or same-sex marriage as your dependent variable since you are trying to explain why people have different opinions on these issues.  But in this exercise we're not trying to explain religious preference.  Rather we're trying to measure the similarity or dissimilarity between the religious preference of the respondent and their spouse or partner.  So we don't need to decide which is the independent and dependent variable. 

To run a crosstabulation in SPSS click on "Analyze" in the menu bar at the top of the screen.  Now click on "Descriptive Statistics" in the drop-down menu and then on "Crosstabs."  (See Chapter 5, Cross Tabulations, in the online SPSS book cited on page 1 of this exercise.)   Your screen should look like Figure 4. 

Title: Figure 4 - Description: This is the SPSS dialog box for Crosstabs.

Figure 4

You're going to put your two variables (i.e., R5 and RS3) in the "Row(s)" and "Column(s)" boxes by clicking on the variable in the left-hand pane to select it and then clicking on the arrow that points to the right.  When you do that, the arrow will change so it points left.  If you click on it again, it will move the variable back to the left-hand pane.  That way you can correct errors you would make when you select the wrong variable.

But which variable goes in which box?  Typically, we put the independent variable in the column box and the dependent variable in the row box.  But we just decided that we didn't need to designate independent and dependent variables.   In order to standardize our tables so they will look similar, we're going to put R5 in the column box and RS3 in the row box.  We're also going to click on the "Cells" box and check the box for "Column" percents.  Your screens should look like Figure 5 and 6.

 

Title: Figure 5 - Description: This is the SPSS Crosstabs dialog box with R5 in the columns and RS3 in the rows.

Figure 5

This is the second part of the SPSS Crosstabs dialog box, withcolumn percentages selected.

Figure 6

To get the table, click on "Continue" and then on "OK."  Your screen should look like Figure 7.  This is a big table so I'm only showing the top left part of the output.

Title: Figure 7 - Description: This is the SPSS output for the crosstab of R5 and RS3.

Figure 7

There are two numbers in each cell of the table.  The top number is the number of cases in each cell and the bottom number is the column percent.  Notice that the column percents add down by column to 100.  Since the percents sum down to 100, you want to compare the percents across.  Always compare the percents in the direction opposite to the way they sum to 100.  This part of the table shows you that 75% of respondents who are Evangelical Protestant are either married to living with someone who is also Evangelical Protestant and that 60% of those who are Mainline Protestant are married to or living with someone who is Mainline Protestant. 

This table is too large to conveniently print out or to copy into your paper so you will need to refer to the table in SPSS.  You're going to fill in the information in the table below by referring to the table in the SPSS output. 

What we want to know is the percent of respondents in each religious category that are married to or living with someone in that same category and the percent that are married to or living with someone in another religious category.

Title: Figure 8 - Description: For each religious category, the percent of respondents married to or living with someone in the same category, and the percent married to or living with someone in another category

Figure 8

I filled in the first row for you so you would have an example to work from.  Notice that the second and third columns sum across to 100%.

Now that you have the data, write a paragraph or two describing the similarity and dissimilarity between respondent's religious preference and that of their spouse or partner.  To help you write your paragraph(s), consider the following questions.

  • Which religious groups show more similarity than dissimilarity?  Which groups have the greatest similarity?
  • Which religious groups are more dissimilar than similar?  Which groups have the greatest dissimilarity?
  • Look at those who are unaffiliated without any religious preference.  What percent of that group are married to or living with someone who is also unaffiliated?

Conclusions

Write a summary of what you learned about the similarity and dissimilarity of religious preference for respondents and their spouses or partners.  Which religious groups have the most and the least similarity?  What does this tell you about religious similarity and dissimilarity for respondents and their spouses and partners in the United States?

 


 

[1] This assumes that the proper associations have been set up on your computer so the computer knows that .sav files are SPSS data files

[2] SPSS allows you to change the way your output is displayed.  You can change these preferences by clicking on "Edit" in the menu bar at the top of the screen and then clicking on "Options" and finally on the "Output" tab.  Under "Variables in item labels shown as" select "Names and Labels" and then under "Variable values in item labels shown as" select "Values and Labels."  Then click on "OK."  You can also try out other options.