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Threats to Construct Validity

External threats to validity

❶Experimental and quasi-experimental designs for research. Experimental Validity — Provides an explanation of both internal and external validity, as well as threats to both.

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In this example, the researcher wants to make a causal inference, namely, that different doses of the drug may be held responsible for observed changes or differences. When the researcher may confidently attribute the observed changes or differences in the dependent variable to the independent variable, and when the researcher can rule out other explanations or rival hypotheses , then the causal inference is said to be internally valid.

In many cases, however, the magnitude of effects found in the dependent variable may not just depend on. Internal validity, therefore, is more a matter of degree than of either-or, and that is exactly why research designs other than true experiments may also yield results with a high degree of internal validity.

In order to allow for inferences with a high degree of internal validity, precautions may be taken during the design of the scientific study. As a rule of thumb, conclusions based on correlations or associations may only allow for lesser degrees of internal validity than conclusions drawn on the basis of direct manipulation of the independent variable.

And, when viewed only from the perspective of Internal Validity, highly controlled true experimental designs i. By contrast, however, the very strategies employed to control these factors may also limit the generalizability or external validity of the findings. Lack of clarity about which variable occurred first may yield confusion about which variable is the cause and which is the effect. A major threat to the validity of causal inferences is confounding: Changes in the dependent variable may rather be attributed to the existence or variations in the degree of a third variable which is related to the manipulated variable.

Where spurious relationships cannot be ruled out, rival hypotheses to the original causal inference hypothesis of the researcher may be developed. Selection bias refers to the problem that, at pre-test, differences between groups exist that may interact with the independent variable and thus be 'responsible' for the observed outcome. Researchers and participants bring to the experiment a myriad of characteristics, some learned and others inherent.

For example, sex, weight, hair, eye, and skin color, personality, mental capabilities, and physical abilities, but also attitudes like motivation or willingness to participate. During the selection step of the research study, if an unequal number of test subjects have similar subject-related variables there is a threat to the internal validity. For example, a researcher created two test groups, the experimental and the control groups. The subjects in both groups are not alike with regard to the independent variable but similar in one or more of the subject-related variables.

Self-selection also has a negative effect on the interpretive power of the dependent variable. This occurs often in online surveys where individuals of specific demographics opt into the test at higher rates than other demographics. Often, these are large-scale events natural disaster, political change, etc. Subjects change during the course of the experiment or even between measurements. For example, young children might mature and their ability to concentrate may change as they grow up.

Both permanent changes, such as physical growth and temporary ones like fatigue, provide "natural" alternative explanations; thus, they may change the way a subject would react to the independent variable. So upon completion of the study, the researcher may not be able to determine if the cause of the discrepancy is due to time or the independent variable.

Repeatedly measuring the participants may lead to bias. Participants may remember the correct answers or may be conditioned to know that they are being tested. Repeatedly taking the same or similar intelligence tests usually leads to score gains, but instead of concluding that the underlying skills have changed for good, this threat to Internal Validity provides a good rival hypotheses.

The instrument used during the testing process can change the experiment. This also refers to observers being more concentrated or primed, or having unconsciously changed the criteria they use to make judgments. This can also be an issue with self-report measures given at different times. In this case the impact may be mitigated through the use of retrospective pretesting.

If any instrumentation changes occur, the internal validity of the main conclusion is affected, as alternative explanations are readily available. Threats to internal validity Timeline: The opinions of respondents depend on the recall time to gather opinions. Then the validity of their answers will increase.

However, in case the research is conducted after a long duration then the opinions can be biased and misleading. Effective changes in instrumentation or in the criteria of recording behavior can be cause threats to validity. For example , performance of 2nd graders starts decreasing after 1 hour due to variable factors, like fatigue, stress, tiredness etc.

However, some respondents may drop out. This will change the defined sample size. Especially studies which have long timelines face this threat to their validity. This threat to validity could be when sample is selected to study extreme behaviour in respondents. For example if a researcher needs to study consumption of mangoes.

Then the threat to validity would be when the collection of data is in a peak consumption season. External threats to validity Impact of pre-testing: Most often researchers conduct pre-tests or pilot tests to determine efficacy of the measuring instrument.

However, pre-tests might impact the sensitivity and responsiveness to the experimental variable. For example, researcher conduct a pre-test on a sample of 25 respondents. Effect of inclusion and exclusion criteria: Effect of selecting a sample based on specific selection criteria. This can impact the outcomes of study which would not have been the case, if there was random sampling. This happens in case of test subjects who have been exposed to same experiment multiple times.

In such cases the effect of previous findings have an impact on overall results. Reactions to experimental arrangement: This is also known as Hawthorne effect. Experimental and quasi-experimental designs for research. Design and analysis issues for field settings. Research methods for business students fifth edition 3rd ed.

Inadequate Preoperational Explication of Constructs

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Threats to validity of Research Design Barbara Ohlund and Chong-ho Yu The books by Campbell and Stanley () and Cook and Campbell () are considered classic in the field of experimental design.

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We often conduct research in order to determine Threats to Internal & External Validity The controlled or experimental design enables the investigator to control for threats to internal and external validity. Threats to internal validity compromise our confidence.

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Construct validity is the quality of choices about the particular forms of the independent and dependent variables. These choices will affect the quality of research findings. Threats to construct validity can arise from the choice of treatment (the operationalization of the IV, and the. Threats to validity of Research Design Chong-ho Yu () The books by Campbell and Stanley (), Cook and Campbell (), and Shadish, Cook, and Campbell, () are considered seminal works in the field of experimental design.

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Five threats to validity in qualitative research are: how observations are explained and interpreted, how the data might be altered to match a particular theory. Examples of threats to internal and external validity in a research By Shruti Datt on October 20, In my previous article I have discussed how the validity can be ensured with respect to Quantitative and Qualitative analysis.