Fraenkel- Chapter 16 (Pages 363-388)
Causal-Comparative Research
I. Causal-Comparative Research (What is it?) (p363-364)
 Investigators attempt to determine the cause or consequences of
differences that already exist between or among groups of
individuals
 Seeks to identify associations among variables
 “Because both the effects and alleged cause(s) have already
occurred, causal-comparative research is also sometimes
referred to as ex post facto (after the fact) research.
 Begins with a noted difference between two groups (such as
ethnicity), then aims to look for possible causes, or consequences
of this difference (p386)
 Sometimes ethical constraints prevent variable from being
manipulated (ex. studying the effects of a new diet on young
children)
 Different types of causal-comparative research (364)
1) Exploring the effects (dep. variables) caused by membership in
a given group
Question: What differences in abilities are caused by gender?
Research hypothesis: Females have a greater amt. of
linguistic ability than males
2) Exploration of causes (independent variable)
Question: What causes individuals to join a gang?
Research hypothesis: Individuals who are members of gangs
have more aggressive personalities than individuals
who are not members of gangs
3) Exploration of the consequences (dep. variable) of an
intervention
Question: How do students taught by inquiry method react to
propaganda?
Research Hypothesis: Students who were taught by the
inquiry method are more critical of propaganda than
are those who were taught by the lecture method.


Causal-Comparative method- frequently used to study the
difference between males and females
Limitations on this type of research: lack of control over
threats to internal validity, relationships can be identified but
causation cannot be fully established
II. Similarities and Differences between Causal-Comparative and
Correlational Research (p365)







Both examples of associational research
Both seek to explore relationships among variables
Both attempt to explain a phenomena of interest
When relationships are identified they are often studied at a later
time by means of experimental research
Difference: casual-comparative typically compares two or more
groups of subjects, correlational investigations requires a score on
each variable for each subject
Difference: Correlational investigates 2 (or more) quantitative
variables, whereas causal-compar. Involve at least 1 categorical
variable (group membership)
Difference: Correlational-analyzes data using scatterplots and
correlation coefficients, causal-compar. Compares averages and
uses crossbreak tables
III. Similarities and Differences between Causal-Comparative and
Experimental Research (365)
 In experimental – the group membership variable is manipulated, in
causal-comparative the group differences already exist
 Both: typically require at least 1 categorical variable (group
membership)
 Both: Compare group performances (average scores) to determine
relationships
 Difference: Experimental- independent variable is manipulated,
causal-compar no manipulation takes place
 Causal comparative- likely to provide weaker evidence for
causation than experimental research
IV. Steps Involved in Causal-Comparative Research (p.366-367)
 Step One: Problem Formulation
- identify and define the particular phenomena of interest
- Consider possible causes for it, or consequences of, phenomena
- Then possible causes are usu. incorporated into a precise
statement of the research problem
- Several alternative hypothesis can be tested- should be basis for
identifying the variables on which the comparison groups are to
be contrasted
- “Shotgun approach”: a large number of measures are
administered simply because they seem interesting or are
available (This much like the “shot gun wedding” is not a
preferred method)
 Step Two: Sample
-


Most important task in selecting a sample is to define carefully
the characteristics to be studied and select groups that differ in
this characteristic
- Very important to select groups that are homogeneous with
regard to at least some important variables
- Once the defined groups have been selected, they can be
matched on one or more variables- this process controls certain
variables thereby eliminating any group differences on these
variables
Step Three: Instrumentation
-There are no limits on the types of instruments that may be used
Step Four: Design
-involves selecting 2 or more groups that differ on a particular
variable of interest and comparing them on another variable or
variables
- No manipulation involved
- Groups different in one of two ways: (1) One group either
possesses a characteristic (criterion) that the other does not,
(2)The groups differ on known characteristics
- See p367 Figure 16.1- Illustrates the basic design
V. Threats to Internal Validity in Causal-Comparative Research (367-369)
 Two weakness: (1) lack of randomization (2) inability to manipulate
an independent variable
 Random assignments of groups is not possible, since groups are
already formed
 Manipulation of indep. variable is not possible because groups
have already been exposed to indep. variable
 Subject Characteristics: (368)
-Possibility of subject selection bias is a major threat
- researchers attempt to reduce this by:
1) matching subjects on a related variable(ex. students might
be matched based on GPA in a study of attitudes),
2) creating homogeneous subgroups(ex. researcher could
seek to find two groups that have similar GPAs- 3.5 GPA
or above or divide groups in low, middle, and high GPA
subgroups and then compare each subgroup –low
gpa with another low gpa group etc),
3) Statistical Matching: adjusts scores on posttest for initial
differences on some other variable that is assumed to
be related to performance on dep. variable
 Other Threats: locations, instrumentation, loss of subjects

Type Three Studies- subject to implementation, history, maturation,
attitude of subjects, regression and testing threats
VI. Evaluating Threats to Internal Validity in Casual- Comparative Studies
 Step One: Ask: What specific factors either are known to affect or
may logically be expected to affect the variable on which groups
are being compared?
 Step Two: Ask: What is likelihood of the comparison groups differing
on each of these factors?
 Step Three: Evaluate the threats on the basis of how likely they are
to have an effect, and plan to control for them.
 See Pages 369-370: for a detailed example of how threats to
subject characteristics, morality, location, and instrumentation are
evaluated in detail
VII. Data Analysis (370-372)
 First step- construct frequency polygons
 Then calculate the mean and standard deviation of each group if
the variables are quantitative
 Most common used test: t-test for differences between means
 When two or more groups are used an analysis of covariance is
particularly useful in causal-comparative studies because
researcher cannot always match the comparison groups on all
relevant variables other than the ones of primary interest
 Analysis of Covariance: provides a way to match groups “after the
fact” on such variables as age, socioeconomic status, aptitude etc.
 The results of causal-comparative studies should always be
interpreted with caution, because they are good at identify
relationships between variables but they do not prove cause and
effect
 Two ways to strengthen interpretability of causal-comparative
studies: (1) alternative hypothesis should be formulated and
investigated whenever possible (2) if dependent variables involved
are categorical the relationship among all variables in the study
should be examined using discriminant function analysis (discuss in
ch 15)
 Most powerful way to check possible causes identified is to perform
an experiment
VIII. Associations Between Categorical Variables (p372)
 Both crossbreak and contingency coefficients can be used to
investigate possible associations between categorical variables,
although predictions from cross break tables are not precise.

Fortunately, there are very few questions of interest in education
that involved 2 categorical variables
IX. An Example of Casual-Comparative Research (373-386)
 Pages 373-384 includes a research report on personal, social, and
family characteristics of angry students for your reading pleasure!
 Page 384-386: includes analysis of the study
 Here is the cliff notes version of the study:
 Purpose of study: Collect descriptive data on personal, family, peer,
and school factors associated with students manifesting angerrelated problems at school to examine the factors promoting high
levels of anger and hostility in youth and the impact of anger and
hostility upon social, behavioral, and academic functioning
 Participants: 24 high-anger elementary age students indentified
based on teacher-ratings and standardized assessments & equal
number of low-anger students who served as comparison sample,
both groups drawn from 12 elementary schools in Honolulu,HI
 Instrumentation: The BASC (Behavioral Assessment System for
Children) Aggression Subscales were used to measure teacher’s
perceptions of students’ physical and verbal aggression, SelfPerception Profiles for Children (SPP) were completed by students
 Procedure: Fifth and Sixth Grade Teachers in 12 elementary schools
were asked to nominate as many students as they wished who fit
criteria for “low” and “high” anger at school, all schools also
administered the Multidimensional School Anger Inventory, all 48
students in study were individually interviewed, completed the BASC
and SPP, teachers were interviewed, and parents were interviewed,
coding of students and likert scales were used to facilitated analysis
of qualitative data
 Results/Discussion: In general, appeared that cumulative positive
and negative experience at home, in school, and with peers have
a major impact on frequency and intensity of anger experienced at
school. (Pages 376-380- will elaborate in great detail on findings if
you are interested)
 Implications for School Counselors (page 381)
 Limitations of Study and Future Directions (382)
 Analysis of Study (page 384-386)