Religion_2MR – Measuring Religiosity

Note to the Instructor: This is the second in a series of four exercises that focus on the measurement of religious preference, religiosity, religious beliefs, and religious behavior. 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 provide an introduction to measurement which is an integral part of any research design.  In this exercise we're going to focus on measuring religiosity. In the next exercise (Religion_3MR) we'll look at measuring religious beliefs.

Part I—Concepts

We use concepts all the time.  We all know what a book is.  But when we use the word “book” we may not be talking about a particular book we’re reading. We could be talking about books in general.  In other words, we’re talking about the concept to which we have given the name “book.”  There are many different types of books – paperback, hardback, small, large, short, long, and so on.  But they all have one thing in common – they all belong to the category “book.”

Let’s look at some other examples.  Religious preference refers to the religion with which people identify.  Some people say they are Lutheran; others say they are Roman Catholic; still others say they are Muslim; and others say they have no religious preference. Religiosity is another concept which refers to the degree of attachment that individuals have to their religious preference.  It’s different than religious preference. Religiosity and religious preference are both concepts.

In other words, a concept is an abstract idea.  There are the abstract ideas of book, religiosity, religious preference, and many others.  Since concepts are abstract ideas and not directly observable, we must select measures or indicants of these concepts.  We call this process measurement.

Part II – 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 III – Measuring Religiosity Using Attendance at Religious Services

Religiosity refers to how religious people say they are. The Pew survey asked three questions that can be used to measure religiosity. One question asked how often respondents attend religious services. Another question asked how important religion is in their lives. And still another asked how often respondents say they pray.

Let's start with attendance at religious services. The Pew survey asked the following question – "Aside from weddings and funerals, how often do you attend religious services... more than once a week, once a week, once or twice a month, a few times a year, seldom, or never?"

Now that you have opened the data set, run a frequency distribution for the variable REL1 which is the name of this variable. The variable name starts with the letter REL which tells you that this variable describes religiosity. There are three variables in this category named REL1 to REL3. We're going to look at all of them in this exercise. 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 shows the Frequencies dialog box in SPSS.

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 REL (i.e., REL1 through REL3). Select REL1 by clicking on it and then click on the arrow pointing to the right. This will move REL1 into the "Variable(s)" box. Your screen should look like Figure 2.

Title: Figure 2 - Description: This shows the Frequency dialog box with REL1 selected.

Figure 2

Now all you have to do is to click on "OK" to get your frequency distribution. Your screen should look like Figure 3.[2]

Title: Figure 3 - Description: This shows the Frequencies output for REL1.

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 said they attended religious services more than once a week.

·         The second column is the number of respondents who said they attended more than once a week (4,880).

·         The third column converts the frequencies to percents. Notice that there is a code (9) for those who said they didn't know or refused to answer. The percent column converts the frequency to a percent by dividing the frequency (4,880) 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 13.9%.

·         The fourth column converts the frequencies to valid percents by dividing the frequency (4,880) by the number of cases with valid information (34,873). In other words, it excludes the cases with missing information (198) from the denominator when computing the percent. Carry out the computation for yourself and convince yourself that it is 14.0%. 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. Look at the cumulative percent for the second category (attended once a week). This tells you that 35.9% attended more than once a week or once a week. Another way to say this is that 35.9% attended at least once a week. You can see where this comes from if you add up the valid percents for the first two categories.

Now it's your turn. The third category in the distribution is for those who attended once or twice a month.

·         What is the value for this category?

·         How many respondents said they attended once or twice a month?

·         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 IV – Measuring Religiosity Using Importance of Religion

Often there's more than one way to measure a concept and that's certainly the case for religiosity. The Pew survey also asked about the importance of religion in the respondent's life. Here's the question – "How important is religion in your life – very important, somewhat important, not too important, or not at all important?"

The name of this variable in the Pew data set is REL2. Run a frequency distribution for REL2. Write a paragraph describing what this frequency distribution tells you about religiosity in the U.S. Be sure to answer the following questions. Use the valid percents.

·         What percent of adults feel that religion is very important in their lives?

·         What percent of adults think that religion is at least somewhat important? How did you arrive at your answer?

·         Based on the frequency distribution, how important do you think religion is to adults? Use the percents in the table to justify your answer.

Part V – Another Way to Measure Religiosity – How Often Respondents Pray

Another way that religiosity is often measured is by asking respondents how often they pray. Here's the question that was asked in the Pew survey – "People practice their religion in different ways. Outside of attending religious services, do you pray several times a day, once a day, a few times a week, once a week, a few times a month, seldom, or never?"

The name of this variable is REL3. Run a frequency distribution for REL3. Write a paragraph describing what this frequency distribution tells you about religiosity in the U.S. Be sure to answer the following questions. Use the valid percents.

·         What percent of adults say they pray several times a day?

·         What percent of adults say they pray once a day?

·         What percent of adults say they pray less than once a day? How did you arrive at your answer?

Part VI – Putting All This Information Together

Write a paragraph using all three measures to describe religiosity in the U.S. Think carefully about how you are going to use all this information to describe religiosity. Use the valid percents from the three frequency distributions to support your answer.

 


 

[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.