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Causal comparative research

Causal-Comparative Study

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Causal comparative research

  2. 2. What is Causal-Comparative Research?  In this type of research investigators attempt to determine the cause or consequences of differences that already exist between or among groups of individual.  Also known as “ex post facto” research
  3. 3. TYPES of Causal-Comparative Research There are three types of causal comparative research:  Exploration of effects  Exploration of causes  Exploration of consequences
  4. 4. CHARACTERISTICS  Attempts to identify cause and effect relationships.  Involve two or more group variables.  Involve making comparison.  Individuals are not randomly selected and assigned to two or more groups.  Cannot manipulate the independent variables.  Less costly and time consuming.
  5. 5. EXAMPLES  How does pre-school attendance affect social maturity at the end of the first grade?  How does having a working mother affect a child’s school absenteeism?
  7. 7. -The researcher selects two groups of participants, the experimental and control groups, but more accurately referred to as comparison groups. -Groups may differ in two ways.  -One group possesses a characteristic that the other does not.  -Each group has the characteristic, but to differing degrees or amounts.
  8. 8. Types of Causal-Comparative Research Designs There are two types of causal- comparative research designs:  retrospective causal-comparative research  prospective causal-comparative research.
  9. 9. Retrospective causal-comparative research Retrospective causal-comparative research requires that a researcher begins investigating a particular question when the effects have already occurred and the researcher attempts to determine whether one variable may have influenced another variable.
  10. 10. Prospective causal-comparative research Prospective causal-comparative research occurs when a researcher initiates a study beginning with the causes and is determined to investigate the effects of a condition. By far, retrospective causal-comparative research designs are much more common than prospective causal-comparative designs (Gay et al., 2006).
  11. 11. Basic approach of causal- comparative research
  12. 12. The researcher observe that 2 groups differ on some variable (teaching style) and then attempt to find the reason for (or the results of) this difference. ***Note that the difference has already occurred.***
  13. 13.  Causal-comparative studies attempt to identify cause-effect relationships.  Causal-comparative studies typically involve two (or more) groups and one independent variable.  Causal-comparative studies involve comparison.
  14. 14.  The basic causal-comparative approach involves starting with an effect and seeking possible causes (retrospective).  The basic approach starts with cause and investigates its effects on some variable (prospective).  Retrospective causal-comparative studies are far more common in educational research.
  15. 15. Steps for Conducting a Causal- Comparative Study The following steps, as described by Lodico et al. (2006), should be adhered to by researchers conducting a causal-comparative study.
  16. 16. Step One: Select a Topic Topics studied with causal- comparative research designs typically catch a researcher’s attention based on experiences or situations that have occurred in the real world.
  17. 17. Step Two: Review of literature Reviewing published literature on a specific topic of interest is especially important when conducting causal- comparative research as such a review can assist a researcher in determining which extraneous variables may exist in the situation that they are considering studying.
  18. 18. Step Three: Develop a Research Hypothesis Hypotheses developed for causal- comparative research to identify the independent and dependent variables. Causal-comparative research hypotheses should describe the expected impact of the independent variable on the dependent variable.
  19. 19. Step Four: Select Participants In causal-comparative research participants are already organized in groups. The researcher selects two groups of participants, the experimental and control groups, but more accurately referred to as comparison groups because one group does not possess a characteristic or experience possessed by the second group or the two groups differ in the amount of a characteristic that they share. The independent variable differentiating the groups must be clearly and operationally defined, since each group represents a different
  20. 20. Step Five: Select Instruments to Measure Variables & Collecting Data As with all of types of quantitative research, causal-comparative research requires that researcher select instruments that are reliable and allow researchers to draw valid conclusions (link to reliability and validity portion of site). After a researcher has selected a reliable and valid instrument, data for the study can be collected.
  21. 21. Step Six: Analyze and Interpret Results Typically, in causal-comparative studies data is reported as a mean or frequency for each group. Inferential statistics are then used to determine whether the means “for the groups are significantly different from each other” (Lodico et al., 2006, p. 214). Since casual-comparative research cannot definitively determine that one variable has caused something to occur, researchers should instead report the findings of causal comparative studies as a possible effect or possible cause of an occurrence.
  22. 22. Threats to Internal Validity in Causal-Comparative Research  The possibility exists that the groups are not equivalent on one or more important variables  Lack of randomization  Inability to manipulate an independent variable  Data collector bias  History  Maturation
  23. 23.  Oftentimes subject bias occurs  Instrument decay  Attitude  Regression  Pre-test/treatment interaction effect  Loss of subjects  Location
  24. 24. Data Analysis  In a Causal-Comparative Study, the first step is to construct frequency polygons.  Means and SD are usually calculated if the variables involved are quantitative.  The most commonly used inference test is a t- test for differences between means.  ANCOVAs are useful for these types of studies.
  25. 25. ANALYSIS OF COVARIANCE  I  It is used to adjust initial group differences on variables used in causal-comparative and experimental research studies.  Analysis of covariance adjusts scores on a dependent variable for initial differences on some other variable related to performance on the dependent.  Suppose we were doing a study to compare two methods, X and Y, of teaching fifth graders to solve math problems.  Covariate analysis statistically adjusts the scores of method Y to remove the initial advantage so that the results at the end of the study can be
  26. 26.  Analysis of data also involves a variety of descriptive and inferential statistics.  The most commonly used descriptive statistics are (a) The Mean, which indicates the average performance of a group on some measure of a variable, and (b) The Standard Deviation, which indicates how spread out a set of scores is around the mean, that is, whether the scores are relatively homogeneous or heterogeneous around the mean.
  27. 27.  The most commonly used inferential statistics are:  (a) The t test, used to determine whether the means of two groups are statistically different from one another;  (b) Analysis of variance, used to determine if there is significant difference among the means of three or more groups; and  (c) chi square, used to compare group frequencies, or to see if an event occurs
  28. 28. Limitations of Use:  There must be a “pre-existing” independent variable  Years of study, gender, age, etc.  There must be active variables- variables which the research can manipulate  The length and number of study sessions, instructional techniques, etc.  Lack of randomization, manipulation, and control factors make it difficult to establish cause-effect relationships with any degree of confidence.