Assignment: Purpose Based Classification Assignment: Purpose Based Classification
Assignment: Purpose Based Classification
Assignment: Purpose Based Classification
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Assignment: Classification Based on Purpose (Dimension 1)
The categories of the first dimension for classifying nonexperimental studies, which are based on the main purpose of the study, are:
1. Descriptive nonexperimental research, in which the primary focus for the research is to describe some phenomenon or to document its characteristics. Such studies are needed in order to document the status quo or do a needs assessment in a given area of interest.
2. Predictive nonexperimental research, in which the primary focus for the research is to predict some variable of interest (typically called the criterion) using information from other variables (called predictors). The development of the proper set of predictors for a given variable is often the focus of such studies.
3. Explanatory nonexperimental research, in which the primary focus for the research is to explain how some phenomenon works or why it operates. The objective is often to test a theory about the phenomenon. Hypotheses derived from a given theoretical orientation are tested in attempts to validate the theory.
The three categories could be seen as answers to the question: Was the main purpose of the research to describe a phenomenon, to study how to predict some future event, or to understand how something operates or what drives it?
To help explain these three categories, consider the use of exit interviews. Such interviews are often conducted by organizations with employees who leave or by school systems with departing teachers and graduating seniors. An exit interview study can be descriptive if the purpose is to collect data in order to get a comprehensive picture of reasons for employees leaving their organization or school. These descriptions might be used to determine if people leave for reasons related to the organization or for personal reasons. On the other hand, the study would be predictive if exit data were collected and then related to hiring data for the same individuals for the purpose of using the results to screen potential employees and hiring people who might be less likely to leave. Finally, the study would be explanatory if the data were analyzed with the
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purpose of testing hypotheses about how personal characteristics might be related to employee or student feelings about their organization or school.
A good example of a published descriptive study is the 39th Annual Phi Delta Kappa/Gallup Poll of the Public’s Attitudes toward the Public Schools (Rose & Gallup, 2007). Begun as an effort to inform educators, the annual survey now provides information that has policy implications. Although the accumulated database can be used to track changes in attitudes about Pre-K–12 schooling over a long period of time, the design for each yearly survey is purely descriptive in terms of its purpose. Results are a descriptive representation of how the general public feels about different aspects of public schools.
A study by Leslie Halpern and Thomas Dodson (2006) to develop a set of indicators that could identify women likely to report injuries related to intimate partner violence is an example of a predictive study. They tried to develop markers that could be used in hospital settings to make predictions about likelihood of intimate partner violence. They identified two variables as potential predictors: injury location and responses to a standard screening questionnaire. They included them, along with demographic variables, in developing a prediction model.
An explanatory study was done to examine the relationships among the variables of attachment, work satisfaction, marital satisfaction, parental satisfaction, and life satisfaction (Perrone, Webb, & Jackson, 2007). This research was informed by attachment theory, which describes “parental attachment as a stable connection that provides a feeling of safety and security for the child” (p. 238). The researchers used five published instruments and present a very good description of reliability and validity for each one.
Classification Based on Time (Dimension 2)
The categories of the second dimension for classifying nonexperimental research, which refer to time, are:
1. Cross-sectional research, in which data are collected at one point in time, often in order to make comparisons across different types of respondents or participants.
Assignment: Purpose Based Classification
2. Prospective or longitudinal research, in which data are collected on multiple occasions starting with the present and going into the future for comparisons across time. Data are sometimes collected on different groups over time in order to determine subsequent differences on some other variable.
3. Retrospective research, in which the researcher looks back in time using existing or available data to explain or explore an existing occurrence. This backwards examination may be an attempt to find potential explanations for current group differences.
These categories could be seen as answers to the question: Were the data collected at a single time point, across some time span into the future, or were already existing data explored? You could think of them as representing the past (retrospective), present (cross-sectional), and future (prospective) with respect to timing of data collection. As an example, suppose you were interested in assessing differences in college students’ attitudes toward potential careers. In a cross-sectional study, you might take a
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random sample of first-year college students (freshmen) and fourth-year college students (seniors) and compare their attitudes. Your purpose might be to show that more mature students (seniors) view career options differently from less mature students (freshmen).
Assignment: Purpose Based Classification
Now consider assessing career attitudes in a prospective study. There are actually three options: trend, cohort, or panel study. To distinguish among these three approaches, think of a four-year prospective study starting in 2008 with college freshmen. The population of interest is all college freshmen in the United States. In 2008, a random sample of college freshman is taken for all three approaches. Table 4.1 describes the samples in the subsequent three years for each approach. In the trend study, the same general population (college freshmen) is tracked. In the cohort study, the same specific population (college freshmen in 2008) is tracked. In the panel study, the same individuals are tracked. One of the advantages of a panel study is that you can look for changes and not simply report on trends. A disadvantage is that you have to start with a fairly large sample due to attrition over time, particularly for a lengthy study.
An example of a retrospective study could be an examination of the educational background and experience of very successful teachers and less successful teachers. The idea is to look backward in time and examine what differences existed that might provide an explanation for the present differences in success. To the extent that such a study needed to depend on people’s memories of relevant background information, it would be less accurate than if prior data were available for examination.
For a published example, consider one question addressed by Michael Heise (2004), which was whether key actors in a criminal court case view case complexity in the same way. The results of his cross-sectional comparison of three key actor groups (juries, attorneys, and judges) suggest that they do possess slightly different views on whether crimes are complex.
Examples of both prospective and retrospective research are based on the Nurses’ Health Study, a large scale longitudinal study started in 1976 with a mailed survey of 121,700 female registered nurses between thirty and fifty-five years of age who lived in eleven states. Descriptive information about risk factors for major chronic diseases and related issues were gathered every two years. Although most of the information gathered
TABLE 4.1. Description of Samples After Initial 2008 Sampling of College Freshmen
2009 2010 2011
Trend New sample—college New sample—college New sample—college freshmen freshmen freshmen
Cohort New sample—college New sample—college New sample—college sophomores juniors seniors
Assignment: Purpose Based Classification
Panel Same sample from Same sample from 2008, Same sample from 2008, who are now who are now juniors 2008, who are now
sophomores seniors
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was identical, new questions were added periodically. The Nurses’ Health Study Web page (www.channing.harvard.edu/nhs) contains a complete list of publications based on these data.
One such study was conducted by Francine Laden et al. (2000). They examined the responses from the 87,497 women who answered newly included questions about lifetime use of electric blankets and heated waterbeds. Using data from the larger study, Laden and her colleagues focused their attention on the relationship between electric blanket use and breast cancer from both a prospective and retrospective view. This was done because electric blanket use is a source of electric and magnetic fields (EMFs) exposure, and EMF exposure had been hypothesized to increase the risk of breast cancer. The relevant year is 1992, when information about use of electric blankets and waterbeds was first documented. For the prospective part of their study, they considered women who had not been diagnosed with cancer as of 1992 and analyzed the occurrence of breast cancer from 1992 to 1996 for groups according to electric blanket or waterbed usage. For the retrospective part, they used records from 1976 to 1992, considering only women who were cancer free in 1976. In the prospective part of the study “exposure to electric blankets and waterbed use was assessed prior to the occurrence of breast cancer,” while in the retrospective analysis “exposure was ascertained after diagnosis” (Laden et al., 2000, p. 42).
Retrospective studies may be based on past records, as in the previous example, or on retrospective questions, that is, on questions about past behaviors or experiences. Merely using already existing data, however, does not make it retrospective. The key distinction is the study’s purpose. Are you looking backwards to discover some potential cause or explanation for a current situation, or are you using data from one point in time to predict data from a later time? Notice that Laden and her colleagues (2000) used preexisting data for both retrospective and prospective studies. For the prospective part, women who had not been diagnosed with cancer in 1992 were divided into groups based on whether they did or did not use electric blankets, and the groups were then compared with respect to breast cancer incidents by 1996. For the retrospective part, they divided the women into two groups based on whether they had or had not been diagnosed with cancer as of 1992 and then compared them in terms of reported prior use of electric blankets.
