Assignment: Combining Classification Dimensions

Assignment: Combining Classification Dimensions

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Assignment: Combining Classification Dimensions

When used together, Johnson’s two dimensions (2001) combine to form a 3 × 3 design for a total of nine distinct categories that may be used to describe nonexperimental research. Examples of all nine may be found in the National Education Longitudinal Study of 1988 (NELS:88), which was a large-scale data collection effort. A nationally representative sample of eighth graders were first surveyed in 1988, with subsequent follow-up surveys every two years until 1994, and then once again in 2000. The National Center for Education Statistics’ Web page (http://nces.ed.gov/surveys/nels88) describes this study, and also provides an annotated bibliography of research done using the various data sets. Depending on which data were selected for each study and the study

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TABLE 4.2. Articles Classified According to Both Research Objective and

Time of Dimensions

Retrospective Cross-Sectional Prospective

Descriptive Type1 Type2 Type3

Behavioral responses Criminal case The stability of of substance-exposed complexity: An undergraduate newborns: a empirical perspective students’ cognitive test retrospective study (Heise, 2004) anxiety levels (Cassady,

(Higley & Morin, 2004) 2001)

Predictive Type4 Type5 Type6

Electric blanket use A predictive model to Electric blanket use and and breast cancer in identify women with breast cancer in the the nurses’ health injuries related to nurses’ health study study (Laden et al., intimate partner (Laden et al., 2000)

2000) violence (Halpern &

Dodson, 2006)

Explanatory Type7 Type8 Type9

A further look at youth Relationships between Thirty-year stability and intellectual giftedness parental attachment, predictive validity of and its correlates: work and family roles, vocational interests. values, interests, and life satisfaction (Rottinghaus, Coon, performance, and (Perrone, Webb, & Gaffey, & Zytowski, behavior (Roznowski, Jackson, 2007) 2007)

Reith, & Hong, 2000)

purpose, different NELS:88 studies might be classified using all nine of the purpose by time frame classifications. To help clarify this cross-classification scheme, Table 4.2 gives the titles of articles representing each type, which are then described.

Type 1—Descriptive retrospective. Using retrospective chart review, Anne Marie Higley and Karen Morin (2004) described the behavior of infants whose mothers had a drug history. Their findings supported the use of an assessment tool to guide parents in providing a supportive care environment to help infants recover.

Type 2—Descriptive cross-sectional. This study was discussed earlier as an example of a cross-sectional study. It is descriptive because the goal was to document the extent to which juries, attorneys, and judges held similar or different views about a case. The results have implications for legal reform efforts.

Type 3—Descriptive prospective. This was an investigation of the stability of test anxiety measures over time and testing formats, with data collected at three time points in an academic semester, therefore making it prospective. The purpose for the description was to determine if test anxiety was a stable condition or if it is necessary to

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include a test anxiety measure with every test in a longitudinal study. Results indicated that it is not necessary to measure anxiety with every test; it is only necessary to measure anxiety in one test-taking situation.

Type 4—Predictive retrospective and Type 6—Predictive prospective. The two parts of this study were described earlier as examples of retrospective and prospective studies. Both parts were predictive in nature, using a backward and a forward perspective to determine the extent to which electric blanket and waterbed use could be used to predict breast cancer. Although results did not exclude small risks, neither analysis supported an association between breast cancer risk and use of electric blankets and waterbeds.

Type 5—Predictive cross-sectional. In this study, discussed as an example of a predictive study, a one-time data collection was used. The authors’ aim was to develop and validate a predictive model. They subdivided their sample, using one group to develop their model and the second group to validate, or test it. Their work produced a predictive and validated model of three components: risk of self-report of intimate partner violence related injury, age, and race. The researchers then hypothesized that these three variables could be used to develop a protocol to assist in the early diagnosis of intimate partner violence in an emergency department and outpatient clinical setting.

Type 7—Explanatory retrospective. This study was explanatory because a goal was to further previous work on giftedness and knowledge and understanding of several related variables. The data came from the High School and Beyond database, a longitudinal study with baseline information on 14,825 students who were high school sophomores in 1980. The data for this study included the base year and the third follow-up survey, four years later, after graduation. The data set “allowed for more comparisons than could reasonably be included in a single study. Variables were chosen that would either serve to replicate previous findings or expand psychological and behavioral profiles of gifted male and female students into more detail” (Roznowski, Reith, & Hong, 2000, p. 96). A retrospective conclusion was that educational attainment differences of gifted males and females had their origins in the early high school years.

Type 8—Explanatory cross-sectional. Already discussed as an example of an explanatory study, this study was based on data from the fifteenth annual survey of a longitudinal study that started in 1988 with 1,724 participants. About 1,200 participants were lost in the first three years. Only 108 participants were left for this study, which shows the dramatic attrition that can happen in a longitudinal study. Although the data were from a longitudinal study, these authors only used the fifteenth year’s data, thereby making it cross-sectional.

Type 9—Explanatory prospective. The authors suggested that “Assessing the predictive validity of an interest inventory is essentially answering the question, ‘Do early interest scores match one’s future occupation?’” (Rottinghaus et al., 2007, p. 7). To answer this question, they did a thirty-year follow-up of 107 former high school juniors and seniors whose interests were assessed in 1975. The first author had collected the initial data. Their results extend research on vocational interests, indicating that interests were fairly stable even after such a long time span.

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Classifying Nonexperimental Research

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Nonexperimental Quantitative Research

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Classifying Nonexperimental Research

Causal Explanations and Nonexperimental Studies 71