In a study, the internal validity can be defined as the level of truth in the whole experiment, to the extent that your cause-and-effect hypothesis cannot be explained any other way. In easier terms, internal validity is when you can draw a link between the cause and effect in a practical experiment.
Internal Validity - FAQ
There are eight limitations or threats to internal validity, including instrumentation, regression to the mean, history, selection bias, testing, attrition, maturation, and social interaction.
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It can be evaluated based on unwanted variables that could pose a risk in establishing valid values. The greater values are successfully identified and controlled, and the more control you have over such variables, the more confident you will be in your cause-and-effect results.
Internal validity is the level of self-assurance that other factors or variables do not influence the cause-and-effect relationship you are testing. In contrast, external validity is the extent of generalization of your contexts where the experiment’s validity relies on the experimental design.
Internal validity can be defined as the ability to link the results to the truth in an experiment.
In a social experiment where blind subjects were being observed for behavioral characteristics, the conclusion should indicate that the subjects might have acted differently than usual, knowing that they were being studied.
Internal validity: Definition
Internal validity can be defined as how logical and reasonable results from the experiment are. An effective validity involves a successful demonstration that the results and conclusions from the experiment cannot be explained any other way.
Internal validity can be affected by factors such as the Hawthorne effect, the placebo effect, confounding, the observer effect, and the carryover effect. If any of these issues manage to compromise your results and observations, the study must go under discussion.
Importance of internal validity
Internal validity is vital to an experimental design because it makes the findings and conclusions of a cause-and-effect connection trustworthy and credible, without which a study fails to establish a case and effect link between the two variables.
A good research example:
Imagine you hypothesized that taking a glass of orange juice improves the memory capacity of students. Your experimental design includes testing a specific number of college students for morning and evening laboratory sessions to drink the juice and take a memory-reliant test. You also have an identical control group containing the same number of participants.
At the lab, you give the experimental group a glass of orange juice and the control group a glass of water, after which they take the memory test. Upon analysing the results, you establish that the experimental group did averagely better compared to the control group. In this case, a valid internal validity would be to conclude that taking a glass of orange juice improves memory capacity.
Checking for internal validity
For you to establish if your experiment has met the internal validity requirements, there are three conditions the study has to meet. They are:
- The cause and effect variables change together.
- The cause precedes the effect in your response variables.
- There should be no extraneous factors that would lead to an alternative response or an alternative explanation of the results.
For example, in the above experiment, only two thirds of these conditions were met. They are:
- Taking a glass of orange juice and better memory both increased together.
- Taking the juice occurred prior to the test.
The third condition does not fit because the memory performance can be attributed to an extraneous factor that the time of day might affect the participants’ memory. Due to the difference in opinion about the difference in performance, you cannot certainly state whether the juice or the time of day may have caused the results. This, therefore, means that the experiment has low internal validity. Therefore, we cannot correctly establish the claim of the cause-and-effect study.
Trade-off between external and internal validity
External validity is the level of generalization of your contexts where the experiment’s validity relies on the experimental design. This means that you can apply the experiment’s findings in a broader context. There usually exists a relationship between the two types of validity. The more the external factors are regulated, the fewer chances you have to generalize your results to a wider context.
In my theory of the effect of orange juice on memory capacity, the external validity is dependent on the participant inclusion criteria, the memory test, and the lab environment. For example, limiting the subjects to college-aged participants promotes internal validity while reducing the external validity.
Therefore, the experiment may only be generalized to a specific population group, college-aged subjects.
Possible threats and how to reduce them
Different threats to internal validity can be approached by either single and multi-group experiments. Countering these threats is vital if you intend to have a robust experiment with minimal counterarguments.
i) Single-group studies
A researcher wants to carry out an experiment that will establish whether having indoor plants in office environments boosts the morale and attitude of the personnel. The researcher puts a select group inside an office well-endowed with green plants, while the other group was put in an office environment without plants for two months. All the participants were given a timed productivity pre-test before they begin the experiment and post-test afterward.
|A dissimilar event affects the results
|A few days before the experiment comes to an end, the participants are warned of layoffs. As a result, they are stressed out on the exam day and their results may be affected.
|The results of the experiment differ as a natural effect of time
|Many of the subjects are newbies to their job posts while taking the pre-test. Their productivity improves over a month as a result of their time spent at the position.
|The pre-test and post-test had different approaches
|In the pre-test, the product yield was measured for 15 minutes, while the post-test was at least half an hour long.
|The first test affected the results of the post-test
|Subjects had better performance at the end of the experiment as the same test was given. Many subjects performed better because of repetition and purpose to pass the test.
How to solve for these threats
- Introducing a control group repels all the threats.
- Using a large sample size repels the threat because of more sensitive results.
- Using questionnaires to mask the purpose of the experiment counters testing threats.
ii) Multi-group studies
A group of researchers wants to establish whether a phone application or flashcards are better at teaching vocabulary for an SAT exam. The experimental design includes dividing 11th-grade students based on the pre-test scores on vocabulary. For half an hour each day, Group A uses flashcards, Group B used mobile phones, while Group C spends time studying for the exam and acts as the control group. At the end of the semester, post-test results are tabulated and compared.
How to counter these types of threats
- Random subject placement into groups counters regression and selection bias.
- Withholding experimental details from the subjects limits the effects of social contact, which would botch the results.
In a Nutshell
- Internal validity is the ability of a researcher to link the results to the truth in an experiment.
- It can be faced by threats including instrumentation, regression to the mean, history, selection bias, testing, attrition, maturation, and social interaction.
- It can be determined based on unwanted variables that could pose a risk in establishing valid values.
- Without it, a study fails to establish a cause-and-effect link between the two variables.
- There are three conditions the study has to meet for you to establish if your experiment has internal validity.