4 Key excerpts on "Cross Sectional Research"

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  eBook - ePub

  The SAGE Encyclopedia of Abnormal and Clinical Psychology

  • Amy E. Wenzel(Author)
  • 2017(Publication Date)
  • SAGE Publications, Inc

    (Publisher)

  Jennifer A. McCabe Jennifer A. McCabe McCabe, Jennifer A.

  Cross-Sectional Research Design Cross-Sectional Research Design

  914 915

  Cross-Sectional Research Design

  The purpose of some research studies is to simply record information or to describe associations, not to manipulate variables. Studies like these are called observational or descriptive studies, whereas studies that manipulate one or more independent variables are called experiments. Once a researcher decides to use an observational or descriptive study, the next choice is between a cross-sectional research design and a longitudinal research design. In a cross-sectional design, researchers take measurements, or record data, at a single time point from people who differ in one characteristic of interest (e.g., age) but are similar in other characteristics (e.g., socioeconomic status, ethnic background, education level). In contrast, in a longitudinal design, researchers measure the same people over multiple time points, usually across an extended period. By way of analogy, a cross-sectional design is akin to taking a still photograph at a specific point in time, whereas a longitudinal design is akin to recording a movie, or a series of photos, over a span of time.

  Cross-sectional research designs are particularly useful in developmental research, where researchers collect data from people from different age groups but who are similar on other variables. People of a similar age are sometimes called a cohort, because they developed across the same time period. For example, researchers using a cross-sectional research design could go to a preschool and give the same problem-solving test on a single day to students in three cohorts (i.e., 2-, 3-, and 4-year-olds). Assuming that the participants are similar in a variety of other ways, researchers can compare the test results to examine how age is related to problem-solving ability. This particular study would be a quasi-experimental research design

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  eBook - ePub

  Cross-Cultural Psychology

  Critical Thinking and Contemporary Applications, Sixth Edition

  • Eric B. Shiraev, David A. Levy(Authors)
  • 2016(Publication Date)
  • Routledge

    (Publisher)

  These kinds of differences (and, of course, similarities) are studied in cross-cultural psychology (Gudykunst & Bond, 1997). Cross-cultural psychology is the critical and comparative study of cultural effects on human psychology. Please notice two important elements of this definition. First, this is a comparative field. Any study in cross-cultural psychology draws its conclusions from at least two samples that represent at least two cultural groups. Second, because cross-cultural psychology inherently involves comparisons, and the act of comparison requires a particular set of critical skills, the study of cross-cultural psychology is inseparable from critical thinking. Cross-cultural psychology examines psychological diversity and the underlying reasons for such diversity. In particular, cross-cultural psychologists study—again, from a comparative perspective—the links between cultural norms and behavior and the ways in which particular human activities are influenced by different, sometimes dissimilar social and cultural forces (Segall et al., 1990). For example, consider the question suggested by the opening vignette to this chapter: Do disaster survivors experience similar symptomatology across cultures (see Bemak & Chung, 2008)? If they do, can a psychologist use an intervention aimed at treating posttraumatic symptoms in the United States in other cultural environments such as Sudan or Iran? Cross-cultural psychology attempts not only to distinguish differences between groups but also to establish psychological universals and phenomena common to all people and groups (Berry et al., 1992; Lonner, 1980). (See Figure 1.1.) For example, cross-cultural psychology attempts to identify commonalties with regard to the structure of human personality: relatively enduring patterns of thinking, feeling, and acting. Such universal traits include neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness (Costa & McCrae, 1997)

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  eBook - ePub

  The Wiley Encyclopedia of Personality and Individual Differences, Set

  • (Author)
  • 2020(Publication Date)
  • Wiley

    (Publisher)

  individual data, however, as opposed to grouped data and is limited by the inability of the researcher to manipulate variables.

  Case study research in psychology has three distinct qualities (Yin, 2014 ): making an in‐depth inquiry, studying conditions over time, and covering contextual conditions. This third quality, contextual conditions, is actually one of the strengths of this type of research. To fully understand the subject of study, you need to understand the contextual issues surrounding it. Consider the psychobiography. It is important to examine the friends, community, work, family, and cultural contexts in which this individual’s life is embedded. As you contemplate these real‐life concerns, they will not all fall into easy categories. This blurring of categories, and blurring between your subject and their world, is another strength of case study research (Yin, 2014 ) and may provide new insights that were never anticipated. The reasons psychologists use case study methods fall into three categories: description, explanation, and evaluation (Small Group Instructional Diagnosis would be a type of evaluative case study). When case study research is done correctly (using protocols, and triangulating data, and increasing reliability through use of databases and a chain of evidence) it is rigorous and demands a great deal of effort. Done correctly, it is a very powerful tool.

  To be exemplary, a case study must be well defined and avoid artificially controlled non‐ research constraints. If you do not have the time or money for this, limit your design from the outset. Be sure that your data collection process is complete. Continue to gather and analyze data until you reach a saturation point where new insights are no longer being identified.

  While analyzing data, rival explanations must be considered. The research must clearly show that all evidence was considered, not just the evidence that supported the initial point of view. At the same time, avoid allowing the pressure of the volume of data to try to make one’s case. Be clear on the validating steps taken, without belaboring the issue. One needs to be concise, parsimonious, and still entice the reader to continue reading. This takes talent, and numerous rewrites. If one can balance the skills of the scientist and

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  eBook - ePub

  Quantitative Longitudinal Data Analysis

  Research Methods

  • Vernon Gayle, Paul Lambert(Authors)
  • 2020(Publication Date)
  • Bloomsbury Academic

    (Publisher)

  2 The Luxembourg Income Study offers coordinated access to micro-data for the analysis of selected Labour Force Surveys from different countries after harmonization work has already been undertaken (see Smeeding, Jesuit and Alkemade, 2002). A standard approach is to derive aggregate summary statistics from different Labour Force Surveys and explore trends in those aggregate records.

  There are some important attractions to using cross-national surveys for longitudinal research. There are many surveys available for studying trends over time. There are well-known challenges of comparability and standardization of measures when working with cross-national repeated cross-sectional survey datasets (see Johnson, 1998; Burkhauser and Lillard, 2005; Hoffmeyer-Zlotnik and Warner, 2014; Connelly, Gayle and Lambert, 2016b). Despite these challenges many projects have successfully analysed trends over time (see Mayer, 2005). It is reasonably easy for academic researchers to gain access to international survey data from national or international data archives

  3

  or from the online resources that projects often provide (see Hoffmeyer-Zlotnik and Warner, 2014). The majority of studies listed in Figure 3 offer access to their micro-data for secondary research free, or at nominal cost, for non-commercial and not-for-profit uses.

  Conclusions 

  Considerable progress can be made by investigating longer term social trends using repeated (or pooled) cross-sectional surveys. A clear benefit of analysing pooled or repeated cross-sectional surveys is that well-understood standard techniques such as linear regression and logistic regression models can be used. The most serious challenge when dealing with repeated cross-sectional surveys is ensuring that measures are sufficiently equivalent over time in order to allow realistic comparisons to be made. Researchers should also consider how best to represent temporal dimensions in their analyses.

  Notes

  1. Websites (accessed 1 June 2016).

  2. See http://www.ilo.org/dyn/lfsurvey/lfsurvey.home (accessed 1 June 2016).

  3. See UK Data Service https://www.ukdataservice.ac.uk

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