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Generalizing to Other Populations of Research Participants, Cultural Considerations

validity is the extent to which the results of a study may be generalized. In other words, can the results be generalized to other populations of research participants or to other ways of manipulating or measuring the variables?

Even though a researcher randomly assigns participants to experimental conditions, the researcher can rarely randomly select participants from the general population.
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Thus, there are some generalizability concerns about the type of Individuals who participate in psychological research. For example, participants are often freshmen and sophomore students taking introductory psychology classes.
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Among other things, they tend to be young, and have a high for approval, etc.
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A similar concern is raised because researchers must ask people to to participate in their research.
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Volunteers tend to be more educated, more , more in need of approval, and have a higher status than nonvolunteers.
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Thus, the of our research findings may be limited to a highly select and unusual group. Other sources of generalizability concerns are gender and cultural differences.
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Generalizing to Other Experimenters, Pretests, and Laboratory Settings

The person who actually conducts the experiment is the source of another problem.
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These include the experimenter's , gender, and the amount of practice in the role of .
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A solution to this generalizing concern, is to use two or more experimenters, preferably both and female, to conduct the research.
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Another generalizability concern is pretesting. Intuitively, pretesting seems like a good idea because the researcher can be sure that the groups are and then measure changes in their .
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However, may limit the generalizability of the findings to populations that did not receive a pretest.
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This is because, in the real word, people are given a pretest. Attitudes, for example, are not measured prior to listening to an advertisement and then again later.
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In addition to the characteristics of the experimenter and pretesting, of the setting in which laboratory studies are done is another generalizability issue.
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That is, concern as to whether the artificiality of a setting limits the ability to generalize what is observed there to settings.
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experiments are one way of counterbalancing laboratory artificiality.
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However, even field experiments can be contrived and , with little real-world relevance.
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Thus, Aronson, Brewer, and Carlsmith (1985), proposed a better distinction relative to realism and experimental realism.
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realism refers to whether the experiment bears similarity to events that occur in the real world.
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refers to whether the experiment has an impact on the participants, involves them, and makes them take the experiment seriously.
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Since mundane and experimental realism are independent dimensions of the research project, both laboratory and field experiments may be high on one dimension but low on the other dimension, low on both dimensions, or high on both dimensions.
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Using this type of distinction, illustrates that laboratory experiments are automatically artificial; even when an experiment lacks realism, it may be very realistic in terms of realism.
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The Importance of Replication

has been stressed as a way of overcoming any problems of generalization that occur in a single study.
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There are types of replications to consider: replications and conceptual replications.
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A replication is an attempt to replicate precise procedures of a study to see whether the results are obtained and that the findings are reliable.
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A study, however, that failed to replicate the same results is not adequate cause for discarding the original research.
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If there are repeated failures to then this may lead to the conclusion that the original results were a fluke of some kind and that a error was made.
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In addition to an exact replication, another type of replication, called a replication can be done.
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Conceptual replications are considered even more important than exact replications in furthering our of behavior.
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In conceptual replication, the variable is manipulated in a way.
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This is important because the specific manipulations are usually definitions of complex variables.
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Thus, when a conceptual replication is done, it helps answer a crucial question as to whether the relationship continues to hold up when the variables are measured or manipulated in other ways.
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When conceptual replications produce results, our in the generalizability of the relationships between variables is greatly increased.
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Evaluating Generalizations via Literature Reviews and Meta-Analysis

In addition to replicating studies, researchers have also drawn conclusions about the of research findings by conducting literature reviews.
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In a review, a reviewer reads a number of studies that addresses a specific topic and then writes a paper that and evaluates the literature.
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Specifically, the literature review provides information that what has been found, tells the reader what findings are strongly supported and those that are only supported in the literature, points out findings and areas in which research is lacking, and discusses directions for research.
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Sometimes a literature review will be done using a technique in which the author provides descriptions of research findings and draws conclusions.
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Other times, the review will be done using a technique called a in which the researcher actually compares the results of a large number of studies in an area.
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The analysis consists of a set of statistical procedures that use sizes to compare a given finding across different studies.
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Instead of relying on the reviewer's impressions and reaching qualitative conclusions in a review, the meta-analysis is used to reach conclusions.







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