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Introduction to Research Methods in Political Science: |
XIII.
LONGITUDINAL ANALYSIS OF SURVEY DATA
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Subtopics |
SPSS Tools
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Most sample surveys involve cross-sectional analysis. That is, they provide us with a snapshot of
a sample of a population at a single point in time. Time, however, is itself one of the most
important variables in politics. The
study of change over time is called longitudinal
analysis. Here we will focus on
the study of change over time in public opinion and behavior, as measured
through sample surveys. Longitudinal
analysis of survey data can be subdivided into three types: trend analysis,
cohort analysis, and panel studies.
The simplest type of longitudinal
analysis of survey data is called trend analysis, which examines overall change
over time. This figure, for example,
shows how newspaper readership declined between 1972 and 2006:
In the first year surveyed, about
two-thirds of all respondents reported reading a newspaper on a daily
basis. Thereafter, regular newspaper
readership more or less continuously declined until, by the start of the new
century, fewer than two respondents in five were daily readers. (Note: look for overall trends, and do not
get too caught up in short-term fluctuations.
The slight rise in newspaper readership in 2002 could indicate a
reversal in the downward trend, but could also be due to short term forces or
merely sampling error.)
Trend analysis has some
significant limitations. While it can reveal change, it gives us little
insight as to how or why the changes have taken place. First,
individuals may change their attitudes or behaviors as they move through the life
cycle. British Prime Minister Benjamin Disraeli (1804-1881) is supposed
to have said that “a man who is not a liberal at 16 has no heart; a man
who is not a conservative at 60 has no head.”[1]
It may be that people tend to change in predictable ways as they get older
(and, depending on one’s perspective, sell out or mature). Second, people may change because of new circumstances.
Technological developments, or a major crisis
such as a war or depression, may result in similar changes that impact all age
groups in a similar way. Finally, change may be the result of generational replacement.
Different generations are shaped by different experiences. Events that
occur as people are coming of age are likely to have a big impact on their
political outlooks, and this impact may prove lasting, continuing to influence
them for the rest of their lives. Even if no individual ever changed
after reaching adulthood, overall change would occur as one generation dies out
and another generation, having gone through different formative experiences,
comes on the scene.
One way to sort some of this out is
through cohort analysis. People born
during the same time period are considered to form an age cohort.
For example, respondents in their 20s in a 1976 survey belong to the
same age cohort as respondents in their 50s in a 2006 survey. By comparing respondents from the same age
cohort surveyed at different times, we can measure change over time in the
attitudes and behavior within the cohort.
In the examples that will be used here, respondents to the General Social
Surveys from 1972 through 2006 have been divided into the following age
cohorts:
The GI Generation (born 1927 or earlier
— the earliest year of birth reported by respondents to any of the
General Social Surveys is 1883). Members
of this cohort were at least 18 years old by the end of 1945, the year World
War II ended. This generation lived
through the Great Depression of the 1930s, the New Deal, and the Second World
War. All Presidents of the
The Silent Generation (born
1928-1945). This generation came of age
after World War II, but before the political turbulence of the late 1960s. The youngest members of the cohort turned 18
the year John Kennedy was assassinated. Because most members reached adulthood in
relatively placid times and because it is a relatively small cohort, this group
has sometimes been labeled the “silent” generation. At this writing (August 2011), it has yet to
produce a president, though four members, Walter Mondale (born 1928), Michael
Dukakis (1933), John McCain (1936), and John Kerry (1943), received major party presidential
nominations.
The Baby Boomers (born
1946-1964). During the Depression and the Second World
War, the
Generations X (born 1965-1981). The
“baby boom” was followed by the “baby bust” as birth
rates plummeted in the mid-1960s. Called
“Gen X” because, by some reckonings, this is the tenth generation of
Americans since independence (hence the Roman numeral “X”), older
members of this generation came of age during the administrations of Ronald
Reagan and the first President Bush.
Younger members attained adulthood during the Clinton
Administration. Older members of this
cohort are eligible to become president, but none have done so as yet.
Generation Y (because it comes after
Generation X; born after 1981) is sometimes called the “Millennium
Generation” because its members came of age (and are still doing so)
during or after the year 2000. The
oldest members of this cohort will not start to turn 35, and thus become
eligible for the presidency, until the 2020 election.
For background purposes, the following
figure graphs the changing composition of the General Social Survey from 1972
through 2006.
The same information is presented in tabular form below the graph. The GI Generation provides half of the
respondents to the 1972 survey, declining thereafter to less than a tenth of
all respondents in 2006. The Silent
Generation is a relatively small cohort, never reaching more than about a third
of all respondents, and reduced to less than a fifth in 2006. The Baby Boomers reach their peak of
representation in 1984 (46 percent), and still constitute over a third of the
total in 2006. The leading edge of
Generation X entered the sample in 1983, and is closing in on the Boomers as
the largest cohort. Generation Y is a small but rapidly growing part of
the electorate.
As noted earlier, an overall trend, or
lack thereof, may be explained in several ways.
First may be a new development (a major crisis, or a new technology, for
example) that effects all cohorts equally, either suddenly or gradually. If this is the case, trend lines should be
similar for each cohort. Second, there
may be life cycle factors at work. If
Disraeli is correct, an analysis of ideology would show each cohort starting
out liberal and gradually becoming more conservative. The trend line for each cohort will be in a
conservative direction, but the change for each generation will lag that of the
one preceding it. Third, a trend may
occur as a result of generational replacement; there may be little
within-cohort change over time, but an older generation may pass from the scene
and be replaced by a new generation with different attitudes or behaviors. Of course, two or more of these factors may
combine to produce the overall pattern.
To see how cohort analysis can be applied
to study change over time, consider the next figure, which breaks trends in
daily newspaper readership down by age cohort.
Clearly, the overall trend away from daily newspaper reading is due
almost entirely to generational replacement. Habits established early in life seem to
persist, but older readers are dying out.
Each generation is less devoted to the daily newspaper than its predecessor.
While cohort analysis allows us to extract
more information from our data than an overall trend analysis, it still suffers
from some serious limitations. While
people in their twenties who were surveyed in the 1970s are drawn from the same
age cohort as people in their 40s interviewed in the 1990s, they are not the
same people. Both surveys are subject to
random sampling error, and this may produce some of the changes we
observe.
For this reason, the “gold
standard” for longitudinal analysis of survey data is the panel study. In
a panel, the same people are interviewed at two or more points in time. Since
the sample is the same, any changes we observe are not a result of sampling
error.
Panel studies, however, have
problems of their own. For one thing, they are generally very expensive, since
great effort has to be expended to keep track of respondents. For
another, despite our best efforts, we will not be successful in all of our
attempts to recontact respondents, especially if the
study is conducted over a long period of time. Those who drop out of the
panel (by moving, dying, refusing to continue, etc.) might have differed in
their attitudes and behaviors from those who remain. Finally, there is
the problem of reactivity. When respondents are interviewed, their
interest in politics may be piqued. If they know that they will be interviewed
again, they may even tend to study up on politics so as not to appear ignorant.
By the end of the study, what started off as a representative sample may
have become something of an elite group.
age cohort
cohort analysis
cross sectional analysis
generational replacement
longitudinal analysis
panel study
reactivity
trend analysis
1. Start SPSS, and open gsscums.sav. Open the General Social Survey 1972-2006 Subset codebook. To
facilitate analysis for the exercises in this Topic, all attitudinal and
behavioral variables in this subset have been recoded to form dichotomies, with
valid values of 0 and 100. Variables
were recoded to divide respondents into groups that are as nearly equal in size
as possible. The vertical axes of the line charts can be interpreted as the
percent of respondents choosing one side of the dichotomy. In the case of
newspaper readership, this represents the percent reporting daily readership of
a newspaper.
Create line charts, repeating the
analysis of figures 1 and 3 in this topic, but replacing “news”
with tvhours (the percent reporting that they watch more
than two hours of television per day) another measure of attitude. Is there an overall trend over time? Are there differences within and/or between
cohorts? How would you explain the
patterns you observe - as generational replacement, stage in the life cycle, or
a change that impacts all generations in a similar fashion?
Do the same for conpress
(the percent expressing at least some confidence in the press), and for
other variables of your choosing.
The remainder of the exercises
for this topic use data from the American National Election Study 2000-2004
Panel Study Subset. Start SPSS, and open
“anespanl.sav.” Open the American National Election Study 2000-2004 Panel Study Subset
codebook.
2. Did some people recall their 2000 president votes differently in 2002 and 2004 than they had right after the election? Crosstabulate p200000 and p200004.
3. Use Select Cases to analyze only those who in 2000 said that they had voted for Bush. Crosstabulate how, in 2004, they recalled voting in 2000 by whether their feelings about Bush (as measured by feeling thermometers) got warmer, cooler, or stayed the same between the 2000 post-election survey and 2004.
4. The panel study includes
feeling thermometers for George W. Bush and Ralph Nader in each election
year. Compute new variables measuring changes in how respondents
felt about each of these people over time.
Select independent variables that you think might explain these
changes. For example, did Democrats
(more than independents and Republicans) become less warm in their feelings
toward Ralph Nader as a result of the election?
Compare means
to test these hypotheses.
5. We might hypothesize that
the traumatic events of September 11, 2001 might have changed the way we regard
other individuals and the government. Examine changes over time in the
several "Trust" measures described in the codebook. Were
changes uniform across the sample, or did some groups change more or in
different ways than others?
Nelson, Elizabeth N., and Edward E. Nelson, “Research
Design and Methods of Analysis for Change Over Time,” California
Opinions on Women's Issues — 1985-1995 http://www.ssric.org/trd/modules/cowi/chapter6. August 15, 1998. Accessed September 6, 2006
Palmquist, Ruth A., “Survey Methods,” http://www.gslis.utexas.edu/%7Epalmquis/courses/survey.html. Accessed
Ruspini, Elisabetta,
“Longitudinal Research in the Social Sciences,” Social Research Update. http://www.soc.surrey.ac.uk/sru/SRU28.html. Spring, 2000. Accessed
[1] Similar
sayings have been attributed to various others. See Mark T. Shirey, “Unquote,” http://www.geocities.com/Athens/5952/unquote.html.
Accessed
[2] Keith, Bruce E., et
al. The Myth of the
Independent Voter (Berkeley: University of California, 1992).
Except where indicated, © 2003-2012 John L. Korey
Last Updated: December 18, 2012