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- Word count: 1703
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-Causal-comparative research is sometimes treated as a type of descriptive research since it describes conditions that already exist.
• -Causal comparative research attempts to determine reasons, or causes, for the existing condition • -In causal-comparative or ,ex-post facto, research the researcher attempts to determine the cause, or reason, for preexisting differences in groups of individuals o -Such research is referred to as ex post facto (Latin for “after the fact”) since both the effect and the alleged cause have already occurred and must be studied in retrospect • -The basic causal-comparative approach involves starting with an effect and seeking possible causes -The basic approach starts with cause and investigates its effects on some variable • -The basic approach is sometimes referred to as retrospective causal-comparative research (since it starts with effects and investigates causes) • -The variation as prospective causal-comparative research (since it starts with causes and investigates effects) • -Retrospective causal-comparative studies are far more common in educational research • -Causal-comparative studies attempt to identify cause-effect relationships; correlational studies do not • -Causal-comparative studies typically involve two (or more) groups and one independent variable, whereas correlational studies typically involve two or more variables and one group
• -Causal-comparative studies involve comparison, correlational studies involve relationship -Neither method provides researchers with true experimental data • -Causal-comparative and experimental research both attempt to establish cause-effect relationships and both involve comparisons. • -Experimental study the researcher selects a random sample and then randomly divides the sample into two or more groups -Groups are assigned to the treatments and the study is carried out • -Individuals are not randomly assigned to treatment groups because they already were selected into groups before the research began • -Experimental research the independent variable is manipulated by the researcher, whereas in causal-comparative research, the groups are already formed and already different on the independent variable • -Independent variables in causal-comparative cannot be manipulated, should not be manipulated, or simply are not manipulated but could be • -Not possible to manipulate organismic variables such as age or gender
• -Ethical considerations often prevent manipulation of a variable that could be manipulated but should not be -If the nature of the independent variable is such that it may cause physical or mental harm to participants, the ethics of research dictate that it should not be manipulated -Figure 12.1 shows independent variables used to compare two or more levels of a given variable -Students with high anxiety could be compared to students with low anxiety on attention span, or the difference in achievement between first graders who attended preschool and first graders who did not could be examined. -Experimental studies are costly in more ways than one and should only be conducted when there is good reason to believe the effort will be fruitful • -Causal comparative studies help to identify variables worthy of experimental investigation • -Despite many key advantages, causal comparative research does have some serious limitations that should also be kept in mind -Since the independent variable has already occurred, the same kinds of controls cannot be exercised as in an experimental study • -Caution must be applied in interpreting results
• -The alleged cause of an observed effect may in fact be the effect itself, or there may be a third variable -For example, a researcher hypothesized that self-concept is a determinant of reading achievement -Identify two groups: one group with high self-concepts and one group with low self-concepts -The dependent variable would be reading achievement
-If the high self-concept group did indeed show higher reading achievement, the temptation would be to conclude that self-concept influences high reading achievement. • -This conclusion would not be warranted because it is not possible to establish whether self-concept precedes achievement or vice versa. • -Both the independent and dependent variables would have already occurred, it would not be possible to determine which came first. -It would be possible that some third variable, such as parental attitude might be the main influence on self-concept and achievement. • -Caution must be exercised in attributing cause-effect relationships based on causal-comparative research. • -Only in experimental research is the degree of control sufficient to establish cause-effect relationships. -Only in experimental research does the researcher randomly assign participants to treatment groups. -In causal-comparative research the researcher cannot assign participants to treatment groups because they are already in those groups. • -Causal-comparative studies do permit investigation of variables that cannot or should not be investigated experimentally, facilitate decision making, provide guidance for experimental studies, and are less costly on all dimensions.
CONDUCTING A CAUSAL-COMPARATIVE STUDY
• -Although the independent variable is not manipulated, there are control procedures that can be exercised to improve interpretation of results. Design & Procedure
-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. -Definition and selection of the comparison groups are very important parts of the causal-comparative procedure. • -The independent variable differentiating the groups must be clearly and operationally defined, since each group represents a different population. • -In causal-comparative research the random sample is selected from two already existing populations, not from a single population as in experimental research. • -As in experimental studies, the goal is to have groups that are as similar as possible on all relevant variables except the independent variable. -The more similar the two groups are on such variables, the more homogeneous they are on everything but the independent variable.
-Lack of randomization, manipulation, and control are all sources of weakness in a causal-comparative study. -Random assignment is probably the single best way to try to ensure equality of the groups. -A problem is the possibility that the groups are different on some other important variable (e.g. gender, experience, or age) besides the identified independent variable.
• -Matching is another control technique.
• -If a researcher has identified a variable likely to influence performance on the dependent variable, the researcher may control for that variable by pair-wise matching of participants. • -For each participant in one group, the researcher finds a participant in the other group with the same or very similar score on the control variable. • -If a participant in either group does not have a suitable match, the participant is eliminated from the study. • -The resulting matched groups are identical or very similar with respect to the identified extraneous variable. • -The problem becomes serious when the researcher attempts to simultaneously match participants on two or more variables.
COMPARING HOMOGENEOUS GROUPS OR SUBGROUPS
• -To control extraneous variables, compare groups that are homogeneous with respect to the extraneous variable. • -This procedure may lower the number of participants and limits the generalizability of the findings. • -A similar but more satisfactory approach is to form subgroups within each group that represent all levels of the control variable. • -Each group might be divided into high, average, and low IQ subgroups. • -The existence of comparable subgroups in each group controls for IQ. • -In addition to controlling for the variable, this approach also permits the researcher to determine whether the independent variable affects the dependent variable differently at different levels of the control variable. • -The best approach is to build the control variable right into the research design and analyze the results in a statistical technique called factorial analysis of variance. • -A factorial analysis allows the researcher to determine the effect of the independent variable and the control variable on the dependent variable both separately and in combination. • -It permits determination of whether there is interaction between the independent variable and the control variable such that the independent variable operates differently at different levels of the control variable.
ANALYSIS OF COVARIANCE
• -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 fairly compared as if the two groups started equally.
DATA ANALYSIS AND INTERPRETATION
• -Analysis of data 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. -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 more frequently in one group than another. -Lack of randomization, manipulation, and control factors make it difficult to establish cause-effect relationships with any degree of confidence. • -However, reversed causality is more plausible and should be investigated. • -It is equally plausible that achievement affects self-concept, as it is that self-concept affects achievement. -The way to determine the correct order of causality-which variable caused which- is to determine which one occurred first. • -The possibility of a third, common explanation in causal-comparative research is plausible in many situations. • -One way to control for a potential common cause is to equate groups on that variable. • -To investigate or control for alternative hypotheses , the researcher must be aware of them and must present evidence that they are not in fact the true explanation for the behavioral differences being investigated.