Educational Research: Causal-Comparative StudiesEDU 8603Educational ResearchRichard M. Jacobs, OSA, Ph.D.

Research...The systematic application of a family of methods employed to provide trustworthy information about problemsan ongoing process based on many accumulated understandings and explanations that, when taken together lead to generalizations about problems and the development of theories

The basic steps of research...Scientific and disciplined inquiry is an orderly process, involving: description and execution of procedures to collection information (method) objective data analysis statement of findings (results) recognition and identification of a topic to be studied (problem)

Research methods...Quantitativecollects and analyzes numerical data obtained from formal instruments

Quantitative methods...descriptive research (survey research)correlational researchcausal-comparative research (ex post facto research)experimental research

causal-comparative research (ex post facto research) at least two different groups are compared on a dependent variable or measure of performance (called the effect) because the independent variable (called the cause) has already occurred or cannot be manipulated

Research variables...Independentan activity of characteristic believed to make a difference with respect to some behavior(syn.) experimental variable, cause, treatment

dependent variablethe change or difference occurring as a result of the independent variable(syn.) criterion variable, effect, outcome, posttest

A causal-comparative studya study in which the researcher attempts to determine the cause, or reason, for pre-existing differences in groups of individualscalled an ex post facto study because both the effect and the alleged cause have already occurred and must be studied in retrospect

Differences in causal-comparison and correlational studiescausal-comparative studiesattempt to identify cause-effect relationshipscorrelational studiesattempt to identify relationships

causal-comparative studiesinvolve two (or more) groups and one independent variablecorrelational studiestypically involve two (or more) variables and one group

causal-comparative studiesinvolve making comparisonscorrelational studiesinvolve establishing relationships

Differences in causal-comparison and experimental studiescausal-comparative studiesindividuals are not randomly selected but selected because they belong to groupsexperimental studiesindividuals are randomly selected and assigned to two (or more) groups

causal-comparative studiesthe researcher cannot manipulate the independent variableexperimental studiesthe researcher manipulates the independent variable

causal-comparative studiesthe independent variable has already occurred and cannot be manipulatedexperimental studiesthe researcher manipulates the independent variable to determine its effects

causal-comparative studiesthe random sample is selected from two already-existing populationsexperimental studiesthe random sample is selected from a single population

Conducting a causal-comparative study1. select the problem2. select participants and instrument3. design and procedure4. data analysis and interpretation

1. select the problemthe researcher starts with an effect and seeks its causesthe independent variable cannot or should not be manipulated

2. select the participants and instrumentselect samples representative of their respective populations and similar with respect to critical variables other than the independent variablecalled comparison groups

3. design and procedurethe performance of the groups is compared using some valid dependent variable measure (instrument)lack of randomization, manipulation, and control are sources of weakness

controlthe process by which the researcher attempts to ensure that the findings are as free of researcher bias and error as possible

types of controlrandom assignment of participants to groupspair-wise matchingcomparing homogeneous groupscomparing homogeneous subgroupsfactorial analysis of varianceanalysis of covariance

random assignment of participants to groupsnot possible in causal-comparative studies because the groups already exist and have already received the treatment

pair-wise matchingfirst: find a participant in the second (third, fourth, etc.) group with the same or similar score on the control (nonmanipulated) variable as the participant in the first groupsecond: if a participant in either group does not have a suitable match, the participant is eliminated from the study

comparing homogeneous groupscontrol for extraneous variables that are homogeneous with respect to the extraneous variableslimitation: lowers the number of participants in the study and, of course, limits the generalizability of the findings

comparing homogeneous subgroupsform subgroups within each group that represent all levels of the control (nonmanipulated) variablecontrols for the variable and also permits the researcher to determine whether the independent variable affects the dependent variable differently at different levels of the control (nonmanipulated) variable

factorial analysis of variance (FANOVA)building the control (nonmanipulated) variable into the research design then use FANOVA to analyze the results to determine the effect of the independent and control (nonmanipulated) variable on the dependent variable, both separately and in combination

FANOVA allows the researcher to determine if there is an interaction between the independent variable and the dependent variable such that the independent variable operates differently at different levels of the independent variable building it into the research design

analysis of covariance (ANCOVA)statistically adjusts initial group differences on a dependent variable for initial differences on some other variable related to performance on the dependent variableremoves initial differences so that the results can be fairly compared as if the two groups started equally

symbolic representation of the basic causal-comparative design Independent DependentGroup Variable Variable

(E) (X) O (C) O

Where: E (experimental group); C (control group); X (independent variable); O (dependent variable)

Independent DependentGroup Variable Variable

(E) (X1) O (C) (X2) O

Where: E (experimental group); C (control group); X (independent variable); O (dependent variable)

4. Data analysis and interpretationresearcher uses a variety of descriptive and inferential statistics:meanstandard deviationt-testanalysis of variancechi squared

meanthe descriptive statistic indicating the average performance of an individual or group on a measure of some variable

standard deviationthe descriptive statistic indicating the spread of a set of scores around the mean

t-testthe inferential statistic indicating whether the means of two groups are significantly different from one another

analysis of variance (ANOVA)the inferential statistic indicating the presence of a significant difference among the means of three or more groups

chi squared (2)the inferential statistic indicating that there is a greater than expected difference among group frequencies

Mini-QuizTrue and falsecausal-comparative studies attempt to identify the cause-effect relationships; correlational studies do notTrue

causal-comparative studies typically involve two (or more) groups and one independent variable, whereas correlational studies typically involve two (or more) variables and one groupTrue

causal-comparative studies involve relation, whereas correlational studies involve causeFalse

oftentimes, causal-comparative research is undertaken because the independent variable could be manipulated but should notTrue

one of the most important reasons for conducting causal-comparative research is to identify variables worthy of experimental investigationTrue

lack of control means that the researcher can and should manipulate the independent variableFalse

each group in a causal-comparative study represents a different populationTrue

the more similar two groups are on all relevant variables except the independent variable, the stronger the study isTrue

there is random assignment to treatment groups from a single population in causal-comparative studiesFalse

lack of randomization, manipulation of the independent variable, and control are all sources of weakness in a causal-comparative designTrue

matching, comparing homogenous groups or subgroups, and covariate analysis are strategies that enable researchers to overcome problems of initial group differences on an extraneous variableTrue

interpretation of the findings in a causal-comparative study requires considerable caution because the cause may be the effect and the effect may be the causeTrue

extraneous variables or confounding factors may be the real cause of both the independent and dependent variablesTrue

Fill in the blankgroups selected for a causal-comparative study which differ on some independent variable and comparing them on some dependent variablecomparison groups

Fill in the blankunexplained variables that influence a dependent variable confounding factorsextraneous variables

Fill in the blanka method for controlling extraneous variables by comparing groups that are homogeneous with respect to the extraneous variablecomparing homogeneous groups

Fill in the blanka method for controlling extraneous variables by forming subgroups within each group that represent all levels of the control variablecomparing homogeneous subgroups

Fill in the blanka statistical tool to determine the effects of the independent variable and the control variable on the dependent variable, both separately and in combinationfactorial analysis of variance

Fill in the blanka statistical tool to adjust initial group differences on variablesanalysis of covariance

Fill in the blankthe descriptive statistic indicating the average performance of a group on a measure of some variablemean

Fill in the blankthe descriptive statistic indicating how clustered or spread out around the mean a set of scores isstandard deviation

Fill in the blankthe inferential statistic determining whether there is a significant difference between the means of two groupst-test

Fill in the blankthe inferential statistic determining whether there is a significant difference between the means of three or more groupsanalysis of variance

Fill in the blankthe inferential statistic determining whether there is a greater than expected difference among group frequencieschi squared

Fill in the blankactivities by which a researcher endeavors to ensure that the results of a causal-comparative study are not tainted by extraneous variablescontrol

This module has focused on...which identify the cause, or reason, for existing differences in the behavior or status of groupscausal-comparative studies

The next module will focus on......which test hypotheses to establish cause-and-effect relationshipsexperimental studies