The Ex Post Facto Research Method: A Complete Guide to Retrospective Study Design and Methods. Ex post facto research is a retrospective study design that investigates cause-and-effect relationships by examining existing conditions and retrospectively searching for possible causes.
What is Ex Post Facto Research: A Complete Guide to Retrospective Study Design and Methods
It is used when manipulation of independent variables is not possible for ethical or practical reasons. The primary method involves retrospectively comparing groups using techniques such as correlational or criterion group studies. However, conclusions are limited by the lack of control for confounding variables and the absence of random assignment.
What is Ex Post Facto Research?
When translated literally, ex post facto means ‘from what is done afterwards’. In the context of social and educational research the phrase means ‘after the fact’ or ‘retrospectively’ and refers to those studies which investigate possible cause-and-effect relationships by observing an existing condition or state of affairs and searching back in time for plausible causal factors.
In effect, researchers ask themselves what factors seem to be associated with certain occurrences, or conditions, or aspects of behavior. Ex post facto research, then, is a method of teasing out possible antecedents of events that have happened and cannot, therefore, be engineered or manipulated by the investigator. The following example will illustrate the basic idea.
Ex Post Facto Research Definition and Real-World Example
Imagine a situation in which there has been a dramatic increase in the number of fatal road accidents in a particular locality. An expert is called in to investigate. Naturally, there is no way in which she can study the actual accidents because they have happened; nor can she turn to technology for a video replay of the incidents. What she can do, however, is attempt a reconstruction by studying the statistics, examining the accident spots, and taking note of the statements given by victims and witnesses.
In this way the expert will be in a position to identify possible determinants of the accidents. These may include excessive speed, poor road conditions, careless driving, frustration, inefficient vehicles, the effects of drugs or alcohol and so on. On the basis of her examination, she can formulate hypotheses as to the likely causes and submit them to the appropriate authority in the form of recommendations. These may include improving road conditions, or lowering the speed limit, or increasing police surveillance, for instance.
The point of interest to us is that in identifying the causes retrospectively, the expert adopts an ex post facto perspective. Kerlinger (1970) has defined ex post facto research more formally as that in which the in dependent variable or variables have already occurred and in which the researcher starts with the observation of a dependent variable or variables. She then studies the independent variable or variables in retrospect for their possible relationship to, and effects on, the dependent variable or variables.
The researcher is thus examining retrospectively the effects of a naturally occurring event on a subsequent outcome with a view to establishing a causal link between them. Interestingly, some instances of ex post facto designs correspond to experimental research in reverse, for instead of taking groups that are equivalent and subjecting them to different treatments so as to bring about differences in the dependent variables to be measured, an ex post facto experiment begins with groups that are already different in some respect and searches in retrospect for the factor that brought about the difference. Indeed Spector (1993:42) suggests that ex post facto research is a procedure that is intended to transform a non-experimental research design into a pseudo-experimental form.
Two Main Types of Ex Post Facto Research Designs
Two kinds of design may be identified in ex post facto research—the co-relational study and the criterion group study. The former is sometimes termed ‘causal research’ and the latter, ‘causal-comparative research’.
Co-relational (Causal) Study Design
A co-relational (or causal) study is concerned with identifying the antecedents of a present condition. As its name suggests, it involves the collection of two sets of data, one of which will be retrospective, with a view to determining the relationship between them. The basic design of such an experiment may be represented thus:
An example of this kind of design can be seen in the study by Borkowsky (1970). Where a strong relationship is found between the independent and dependent variables, three possible interpretations are open to the researcher:
1 That the variable has caused O
2 That the variable O has caused
3 That some third unidentified, and therefore unmeasured, variable has caused and O. It is often the case that a researcher cannot tell which of these is correct.
The value of co-relational or causal studies lies chiefly in their exploratory or suggestive character for, as we have seen, while they are not always adequate in themselves for establishing causal relationships among variables, they are a useful first step in this direction in that they do yield measures of association. In the criterion-group (or causal-comparative) approach, the investigator sets out to discover possible causes for a phenomenon being studied, by comparing the subjects in which the variable is present with similar subjects in whom it is absent. The basic design in this kind of study may be represented thus:
If, for example, a researcher chose such a de sign to investigate factors contributing to teacher effectiveness, the criterion group O1 , the effective teachers, and its counterpart O2 , a group not showing the characteristics of the criterion group, are identified by measuring the differential effects of the groups on classes of children. The researcher may then examine some variable or event, such as the background, training, skills and personality of the groups, to discover what might ‘cause’ only some teachers to be effective.
Criterion-Group (Causal-Comparative) Study Design
Criterion-group or causal-comparative studies may be seen as bridging the gap between descriptive research methods on the one hand and true experimental research on the other.
Key Characteristics of Ex Post Facto Research
Characteristics of ex post facto research In ex post facto research the researcher takes the effect (or dependent variable) and examines the data retrospectively to establish causes, relationships or associations, and their meanings.
Ex Post Facto vs. Experimental Research: Understanding the Differences
Other characteristics of ex post facto research become apparent when it is contrasted with true experimental research. Kerlinger (1970) describes the modus operandi of the experimental researcher. (‘If x, then y’ in Kerlinger’s usage. We have substituted for x and O for y to fit in with Campbell and Stanley’s (1963) conventions throughout the topic.) Kerlinger hypothesizes: if , then O; if frustration, then aggression. Depending on circumstances and his own predilections in research de sign, he uses some method to manipulate.
He then observes O to see if concomitant variation, the variation expected or predicted from the variation in, occurs. If it does, this is evidence for the validity of the proposition, –O, meaning ‘If, then O’. Note that the scientist here predicts from a controlled to O. To help him achieve control, he can use the principle of randomization and active manipulation of and can assume, other things being equal, that O is varying as a result of the manipulation of.
In ex post facto designs, on the other hand, O is observed. Then a retrospective search for ensues. An is found that is plausible and agrees with the hypothesis. Due to lack of control of and other possible s, the truth of the hypothesized relation between and O cannot be asserted with the confidence of the experimental researcher.
The Control Problem: Main Weakness of Ex Post Facto Studies
Basically, then, ex post facto investigations have, so to speak, a built-in weakness: lack of control of the independent variable or variables. As Spector (1993:43) suggests, it is impossible to isolate and control every possible variable, or to know with absolute certainty which are the most crucial variables. This brief comparison highlights the most important difference between the two designs— control. In the experimental situation, investigators at least have manipulative control; they have as a minimum one active variable. If an experiment is a ‘true’ experiment, they can also exercise control by randomization.
They can assign subjects to groups randomly; or, at the very least, they can assign treatments to groups at random. In the ex post facto research situation, this control of the independent variable is not possible, and what is perhaps more important, neither is randomization. Investigators must take things as they are and try to disentangle them, though having said this, we must point out that they can make use of selected procedures that will give them an element of control in this research.
These we shall touch upon shortly. By their very nature, ex post facto experiments can provide support for any number of different, perhaps even contradictory, hypotheses; they are so completely flexible that it is largely a matter of postulating hypotheses according to one’s personal preference.
The investigator begins with certain data and looks for an interpretation consistent with them; often, however, a number of interpretations may be at hand. Consider again the hypothetical increase in road accidents in a given town. A retrospective search for causes will disclose half a dozen plausible ones. Experimental studies, by contrast, begin with a specific interpretation and then determine whether it is congruent with externally derived data.
The Post Hoc Fallacy and Interpretation Challenges
Frequently, causal relationships seem to be established on nothing more substantial than the premise that any related event occurring prior to the phenomenon under study is assumed to be its cause—the classical post hoc, ergo propter hoc fallacy. Overlooked is the fact that even when we do find a relationship between two variables, we must recognize the possibility that both are individual results of a common third factor rather than the first being necessarily the cause of the second.
And as we have seen earlier, there is also the real possibility of reverse causation, e.g. that a heart condition promotes obesity rather than the other way around, or that they encourage each other. The point is that the evidence simply illustrates the hypothesis; it does not test it, since hypotheses cannot be tested on the same data from which they were derived. The relationship noted may actually exist, but it is not necessarily the only relationship, or perhaps the crucial one. Before we can accept that smoking is the primary cause of lung cancer, we have to rule out alternative hypotheses.
We must not conclude from what has just been said that ex post facto studies are of little value; many of our important investigations in education and psychology are ex post facto de signs. There is often no choice in the matter: an investigator cannot cause one group to become failures, delinquent, suicidal, brain-damaged or dropouts. Research must of necessity rely on existing groups.
On the other hand, the inability of ex post facto designs to incorporate the basic need for control (e.g. through manipulation or randomization) makes them vulnerable from a scientific point of view and the possibility of their being misleading should be clearly acknowledged. Ex post facto designs are probably better conceived more circumspectly, not as experiments with the greater certainty that these denote, but more as surveys, useful as sources of hypotheses to be tested by more conventional experimental means at a later date.
When to Use Ex Post Facto Research
Situations Where Ex Post Facto Research is Most Suitable
It would follow from what we have said in the preceding section that ex post facto designs are appropriate in circumstances where the more powerful experimental method is not possible. These would arise when, for example, it is not possible to select, control and manipulate the factors necessary to study cause-and-effect relationships directly; or when the control of all variables except a single independent variable may be unrealistic and artificial, preventing the normal interaction with other influential variables; or when laboratory controls for many research purposes would be impractical, costly or ethically undesirable.
Common Applications in Education and Social Sciences
Ex post facto research is particularly suit able in social, educational and—to a lesser ex tent—psychological contexts where the independent variable or variables lie outside the researcher’s control. Examples of the method abound in these areas: the research on cigarette smoking and lung cancer, for instance; or studies of teacher characteristics; or studies examining the relationship between political and religious affiliation and attitudes; or investigations into the relationship between school achievement and independent variables such as social class, race, sex and intelligence.
Many of these may be divided into large-scale or small-scale ex post facto studies, for example Stablest (1990) large scale study of differences between pupils from mixed and single sex schools (1990) and Arnold’s and Atkins’s (1991) small scale study of the social and emotional adjustment of hearing-impaired children.
Advantages of Ex Post Facto Research
Among the advantages of the approach we may identify the following:
- Ex post facto research meets an important need of the researcher where the more rigorous experimental approach is not possible. In the case of the alleged relationship between smoking and lung cancer, for instance, this cannot be tested experimentally (at least as far as human beings are concerned).
- The method yields useful information concerning the nature of phenomena—what goes with what and under what conditions. In this way, ex post facto research is a valuable exploratory tool.
- Improvements in statistical techniques and general methodology have made ex post facto designs more defensible.
- In some ways and in certain situations the method is more useful than the experimental method, especially where the setting up of the latter would introduce a note of artificiality into research proceedings.
- Ex post facto research is particularly appropriate when simple cause-and-effect relationships are being explored.
- The method can give a sense of direction and provide a fruitful source of hypotheses that can subsequently be tested by the more rigorous experimental method.
Disadvantages and Limitations of Ex Post Facto Research
Among the limitations and weaknesses of ex post facto designs the following may be mentioned:
- There is the problem of lack of control in that the researcher is unable to manipulate the independent variable or to randomize her subjects.
- One cannot know for certain whether the causative factor has been included or even identified.
- It may be that no single factor is the cause.
- A particular outcome may result from different causes on different occasions.
- When a relationship has been discovered, there is the problem of deciding which is the cause and which the effect; the possibility of reverse causation has to be considered.
- The relationship of two factors does not establish cause and effect.
- Classifying into dichotomous groups can be problematic.
- There is the difficulty of interpretation and the danger of the post hoc assumption being made, that is, believing that because precedes O, causes O.
- It often bases its conclusions on too limited a sample or number of occurrences.
- It frequently fails to single out the really significant factor or factors, and fails to recognize that events have multiple rather than single causes.
- As a method it is regarded by some as too flexible.
- It lacks nullifiability and confirmation.
- The sample size might shrink massively with multiple matching’s (Spector, 1993:43).
How to Design an Ex Post Facto Investigation
Designing an ex post facto investigation We earlier referred to the two basic designs embraced by ex post facto research—the co-relational (or causal) model and the criterion group (or causal-comparative) model. We return to them again here in order to consider designing both types of investigation.
The Causal Model Design Structure
As we saw, the causal model attempts to identify the antecedent of a present condition and may be represented thus: Although one variable in an ex post facto study cannot be confidently said to depend upon the
other as would be the case in a truly experimental investigation, it is nevertheless usual to designate one of the variables as independent (X) and the other as dependent (O). The left to right dimension indicates the temporal order, though having established this, we must not overlook the possibility of reverse causality.
The Causal-Comparative Model Design Structure
The second model, the causal-comparative, may be represented schematically as:
Using this model, the investigator hypothesizes the independent variable and then compares two groups, an experimental group (E) which has been exposed to the presumed independent variable and a control group (C) which has not. (The dashed line in the model shows that the comparison groups E and C are not equated by random assignment.) Alternatively, she may examine two groups that are different in some way or ways and then try to account for the difference or differences by investigating possible antecedents.
Cause-to-Effect vs. Effect-to-Cause Approaches
These two examples reflect two types of approach to causal-comparative research: the ‘cause-to-effect’ kind and the ‘effect-to-cause’ kind. The basic design of causal-comparative investigations is similar to an experimentally designed study. The chief difference resides in the nature of the independent variable, . In a truly experimental situation, this will be under the control of the investigator and may therefore be described as manipulable. In the causal-comparative model (and also the causal model), however, the independent variable is beyond her control, having already occurred. It may therefore be described in this design as non-manipulable.
Step-by-Step Procedures in Ex Post Facto Research
We now examine the steps involved in implementing a piece of ex post facto research.
Planning Your Ex Post Facto Study: 5 Essential Steps
We may begin by identifying the problem area to be investigated. This stage will be followed by a clear and precise statement of the hypothesis to be tested or questions to be answered. The next step will be to make explicit the assumptions on which the hypothesis and subsequent procedures will be based. A review of the research literature will follow. This will enable the investigator to ascertain the kinds of issues, problems, obstacles and findings disclosed by previous studies in the area.
There will then follow the planning of the actual investigation and this will consist of three broad stages—identification of the population and samples; the selection and construction of techniques for collecting data; and the establishment of categories for classifying the data. The final stage will involve the description, analysis and interpretation of the findings.
It was noted earlier that the principal weakness of ex post facto research is the absence of control over the independent variable influencing the dependent variable in the case of causal designs or affecting observed differences between dependent variables in the case of causal-comparative designs. (We take up the question of control in experimental research in greater detail in the next chapter.)
Although the ex post facto researcher is denied not only this kind of control but also the principle of randomization, she can nevertheless utilize procedures that will give her some measure of control in her investigation. And it is to some of these that we now turn.
Introducing Control Through Matching Subjects
One of the commonest means of introducing control into this type of research is that of matching the subjects in the experimental and control groups where the design is causal-comparative. One group of writers explain it thus: The matching is usually done on a subject-to-subject basis to form matched pairs.
For example, if one were interested in the relationship between scouting experiences and delinquency, he could locate two groups of boys classified as delinquent and non-delinquent according to specified criteria. It would be wise in such a study to select pairs from these groups matched on the basis of socio economic status, family structure, and other variables known to be related to both scouting experience and delinquency Analysis of the data from the matched samples could be made to determine whether or not scouting characterized the non-delinquent and was absent in the background of the delinquent. (Ary et al., 1972)
There are difficulties with this procedure, however, for it assumes that the investigator knows what the relevant factors are, that is, the factors that may be related to the dependent variable. Further, there is the possibility of losing those subjects who cannot be matched, thus reducing one’s sample.
Using Analysis of Variance to Control Extraneous Variables
As an alternative procedure for introducing a degree of control into ex post facto research, Ary and his colleagues suggest building the extraneous independent variables into the design and using an analysis of variance technique. They explain: Assume that intelligence is a relevant extraneous variable and it is not feasible to control it through matching or other means. In this case, intelligence could be added to the design as another independent variable and the subjects of the study classified in terms of intelligence levels.
The dependent variable measures would then be analyzed through an analysis of variance and the main and interaction effects of intelligence might be determined. Such a procedure would reveal any significant differences among the groups on the de pendent variable, but no causal relationship between intelligence and the dependent variable could be assumed. Other extraneous variables could be operating to produce both the main effect and any interaction effects. (Ary et al., 1972)
Selecting Homogeneous Samples for Better Control
Yet another procedure which may be adopted for introducing a measure of control into ex post facto design is that of selecting samples that are as homogeneous as possible on a given variable. The writers quoted above illustrate the procedure with the following example. If intelligence were a relevant extraneous variable, its effects could be controlled by using subjects from only one intelligence level.
This procedure serves the purpose of disentangling the independent variable in which the investigator may be interested from other variables with which it is commonly associated, so that any effects that are found can justifiably be associated with the independent variable. (Ary et al., 1972)
Testing Alternative Hypotheses
Finally, control may be introduced into an ex post facto investigation by stating and testing any alternative hypotheses that might be plausible explanations for the empirical outcomes of the study. A researcher has thus to beware of accepting the first likely explanation of relationships in an ex post facto study as necessarily the only or final one.
A well-known instance to which reference has already been made is the presumed relationship between cigarette smoking and lung cancer. Government health officials have been quick to seize on the explanation that smoking cause’s lung cancer. Tobacco firms, however, have put forward an alternative hypothesis—that both smoking and lung cancer are possibly the result of a third, as yet unspecified, factor. In other words, the possibility that both the independent and dependent variables are simply two separate results of a single common cause cannot be ignored.
FAQs
What is the difference between ex post facto research and experimental research?
Answer: The main difference lies in control and timing. In experimental research, the researcher manipulates the independent variable and can randomly assign subjects to groups. In ex post facto research, the independent variable has already occurred naturally, and the researcher examines it retrospectively without manipulation or randomization. Experimental research predicts “if X, then Y,” while ex post facto research observes Y and searches backward for X.
Can ex post facto research prove causation?
Answer: No, ex post facto research cannot definitively prove causation due to lack of control over variables. It can only suggest possible causal relationships or correlations. The classic post hoc fallacy (assuming that because X preceded Y, X caused Y) is a major concern. Alternative explanations must always be considered, such as reverse causation or the influence of unmeasured third variables. Ex post facto findings are best used to generate hypotheses for later experimental testing.
When should researchers use ex post facto research instead of experimental methods?
Answer: Ex post facto research is appropriate when experimental manipulation is impossible, unethical, or impractical. Examples include studying the effects of smoking on lung cancer, investigating differences between males and females, examining the impact of past traumatic events, or researching naturally occurring variables like socioeconomic status, intelligence levels, or pre-existing conditions. It’s also useful when controlling all variables would create artificial conditions that don’t reflect real-world settings.
How can researchers improve the validity of ex post facto studies?
Answer: Researchers can enhance validity by: (1) matching subjects in experimental and control groups on relevant variables, (2) building extraneous variables into the design and using analysis of variance, (3) selecting homogeneous samples to control specific variables, (4) testing alternative hypotheses to rule out competing explanations, and (5) being transparent about limitations. While these methods don’t provide the same level of control as experimental research, they significantly strengthen ex post facto investigations.
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