External and Internal Validity
Summary
TLDRThis script discusses the importance of validity in research, focusing on internal and external validity. External validity ensures findings can be generalized to other populations and settings, while internal validity confirms the accuracy of measures within the study. The script outlines common threats to both, such as participant characteristics, setting, timing, selection bias, sample size, and confounding variables, emphasizing the need for careful study design to ensure reliable and generalizable results.
Takeaways
- 🔍 Research validity is about the soundness of the research design and methods.
- 🌐 External validity is the ability to generalize study findings to other populations and settings.
- 🚫 Lack of external validity means findings are limited and may not apply to other people or contexts.
- 🔬 Internal validity concerns the accuracy of measures within the study and the true relationship between variables.
- 🚫 Lack of internal validity suggests that findings may not reflect the intended constructs or relationships.
- 👥 Participant characteristics can affect external validity if they do not represent the larger population.
- 🏫 The controlled research environment can limit external validity due to its artificiality compared to real-world settings.
- ⏳ Timing is crucial; past studies may not have external validity in the present due to societal changes.
- 🎯 Selection bias can affect both external and internal validity if groups are not comparable at the study's start.
- 🔢 Small sample sizes can lead to unreliable statistics and findings that may be due to chance.
- 🔄 Confounding variables can undermine internal validity if they influence the dependent variable alongside the independent variable.
- 📚 History effects, such as external events, can impact how participants respond and affect internal validity.
- 📈 Maturation effects, like aging or fatigue, can internally influence responses over the course of a study.
- 🛠️ Instrumentation issues arise when measurement tools change, potentially skewing study results.
- 📝 Testing effects can occur in pre- and post-tests, where familiarity with the test can improve performance.
- 🔄 Attrition refers to participants leaving a study, which can introduce bias and affect both internal and external validity.
Q & A
What does 'validity' mean in the context of research design and methods?
-In research, 'validity' refers to the soundness of the research design and methods used to ensure that the findings are accurate and meaningful.
What are the two main types of validity discussed in the script?
-The two main types of validity discussed are internal validity and external validity.
Why is external validity important in research?
-External validity is important because it allows researchers to generalize their findings to other populations and settings, extending the applicability of the research beyond the specific study context.
What does a lack of external validity imply about the research findings?
-A lack of external validity implies that the research findings cannot be confidently applied to other people or contexts outside of the study, limiting the scope of the research's applicability.
What is internal validity and why is it crucial for a study?
-Internal validity relates to the accuracy of the measures within a study and ensures that the findings reflect the true relationship between the independent and dependent variables, without being influenced by extraneous factors.
What are some common threats to external validity?
-Common threats to external validity include participant characteristics, the research environment, and timing, all of which can reduce the generalizability of the study results to other populations and settings.
How can the research environment affect external validity?
-The research environment, often being highly controlled and artificial, may not represent the real-world contexts to which researchers wish to generalize their findings, thus affecting external validity.
What are some threats to internal validity that can compromise a study's findings?
-Threats to internal validity include selection bias, sample size, confounding variables, history, maturation, instrumentation, testing or practice effects, and attrition or mortality.
Why is controlling extraneous variables important for internal validity?
-Controlling extraneous variables is important for internal validity because it ensures that any changes in the dependent variable are due to the independent variable, not other factors, thus establishing a clear causal relationship.
How can sample size impact the internal validity of a study?
-A small sample size can reduce internal validity because it may lack the statistical power needed to produce reliable results, making the findings more susceptible to being due to chance.
What is meant by 'selection bias' and how can it affect both internal and external validity?
-Selection bias occurs when the groups being compared in a study are not similar at the outset, potentially due to differences in participant characteristics. This can affect both internal validity by influencing the study's results and external validity by impacting the generalizability of those results.
Can you explain the difference between 'history' and 'maturation' as threats to internal validity?
-History refers to external events that occur during the study that may affect participant responses, while maturation is an internal process, such as aging or fatigue, that naturally occurs and can influence the results. Both can affect how participants respond, but history is external, and maturation is internal.
What is 'instrumentation' and how can it threaten the internal validity of a study?
-Instrumentation occurs when the measurement tool or method used in a study changes over time, potentially producing different results. This can threaten internal validity by introducing variability in the data collection process that is unrelated to the study's variables of interest.
How can 'testing' or 'practice effects' impact the internal validity of a study?
-Testing or practice effects occur when participants perform better on a test the second time due to familiarity or practice, which can lead to improved performance not related to the study's independent variable, thus threatening internal validity.
What is 'attrition' and how can it affect both internal and external validity?
-Attrition refers to participants dropping out of a study. It affects internal validity by potentially introducing bias if the reasons for dropping out are related to the study's variables. It can also affect external validity if the group that remains in the study differs significantly from the general population.
Outlines
📊 Understanding Research Validity: Internal and External
This paragraph introduces the concept of validity in research, distinguishing between internal and external validity. External validity is emphasized as the ability to generalize findings to other populations and settings, which is crucial for the applicability of research. The paragraph also explains the limitations of external validity, such as when a study's participant demographics limit the applicability of results. Internal validity, on the other hand, concerns the accuracy of measures within a study and the ability to confidently attribute changes in the dependent variable to the independent variable. The paragraph outlines common threats to both types of validity, such as participant characteristics, research environment, and timing, which can affect the generalizability of results.
🔍 Threats to Internal and External Validity in Research
This section delves deeper into the specific threats to internal and external validity. For external validity, it discusses the impact of participant characteristics, such as the common practice of recruiting undergraduates for psychological studies, which may not represent the broader population. The controlled nature of research settings and the passage of time are also highlighted as factors that can limit the generalizability of findings. Turning to internal validity, the paragraph addresses threats such as selection bias, which can affect the comparability of groups, and sample size, which can impact the reliability of statistical results. Confounding variables, history, maturation, instrumentation, testing effects, and attrition are also discussed as factors that can compromise a study's ability to establish a clear relationship between the dependent and independent variables.
🛠 Addressing Validity Threats for Reliable Research Outcomes
The final paragraph focuses on the importance of addressing threats to validity when designing a study. It emphasizes the need to ensure that the study's results accurately reflect the relationship between variables and are generalizable to other populations and contexts. The paragraph discusses the issue of attrition, where participants dropping out of a study can affect both sample size and the representativeness of the sample. It also touches on the potential for selection bias in studies involving pretests and post-tests. The paragraph concludes by stressing the importance of careful consideration of these threats to ensure that research findings are both valid and applicable to a wider audience.
Mindmap
Keywords
💡Validity
💡Internal Validity
💡External Validity
💡Generalizability
💡Participant Characteristics
💡Selection Bias
💡Confounding Variables
💡Attrition
💡Maturation
💡Instrumentation
Highlights
Validity in research is crucial for ensuring the soundness of research design and methods.
Two main types of validity discussed: internal and external validity.
External validity concerns the generalizability of study findings to other populations and settings.
Research aims to expand knowledge beyond the specific study context.
Limitations in studying a small population can impact external validity.
External validity allows for confident application of findings to broader contexts.
Lack of external validity restricts the applicability of findings to other groups or situations.
Internal validity relates to the accuracy of measures within the study.
Internal validity ensures that findings reflect the intended constructs and relationships.
Threats to external validity include participant characteristics, research environment, and timing.
Undergraduate participants may not represent the larger population.
Controlled research settings may not reflect real-world conditions.
Temporal changes can affect the external validity of past studies.
Threats to internal validity include selection bias, sample size, confounding variables, and more.
Selection bias can affect both external and internal validity if groups are not comparable.
Sample size impacts the statistical power and reliability of study results.
Confounding variables can influence results if not properly controlled.
History effects, maturation, instrumentation, testing effects, and attrition are specific threats to internal validity.
Careful study design can mitigate threats to both internal and external validity.
Ensuring validity strengthens the confidence in the true relationship between variables.
Generalizability of results to other populations and contexts is a key outcome of validity.
Transcripts
there are many forms of validity and
research in general validity refers to
how sound your research design and
method are we are going to talk about
two types of validity internal validity
and external validity external validity
refers to how well the findings of our
study can be generalized to other
populations and settings after all the
purpose of research is to learn more
about the world at large and not just
about our specific group of participants
or what goes on in our lab alone it
would be great if we could just study
everyone in all possible contexts but
unfortunately our access is typically
limited to a small population of
participants in a single context or
situation however we still want to be
able to take our findings and say with a
degree of confidence that they represent
what goes on outside of our study
that's what external validity gives us a
lack of external validity means that our
findings cannot be applied to other
people or other contexts outside of the
study we performed or that application
to other people and contexts is limited
for example if we only had white males
participate in our study our findings
might not apply to females or non-white
races and ethnicities so while external
validity refers to factors outside of
our study internal validity on the other
hand relates to the validity of measures
within our study it depends on factors
such as did we capture the construct
that we intended to with our measure was
the independent variable really the
cause of the changes in the dependent
variable or did we control for all other
possible factors that could have
affected our results a lack of internal
liddie means that our findings may not
necessarily reflect what we think they
do
for example our study may have looked at
the effect of pet ownership on mental
health but let's say that unbeknownst to
us at the time the type of pet has a
significant effect on whether or not the
owner will experience mental health
benefits if we did not control for the
type of pet in our study that our
findings do not necessarily reflect what
we think they do
and our study lacks internal validity
let's review some common threats to
external and internal validity this is
by no means an exhaustive list rather
here we just have three examples of
threats to external validity remember
anything that reduces the
generalizability of the study results to
other populations and settings will
reduce external validity let's take a
look at participant characteristics the
question we want to ask is do they
represent the larger population we want
to generalize to for example a large
majority of studies in psychology
recruit undergraduates looking to get
extra credit in their courses
however these participants may differ
from the larger population in a number
of factors such as age IQ and
socioeconomic status setting
the research environment is typically a
very controlled and artificial one very
much unlike the everyday world that we
want to generalize our findings to it is
important for studies to be able to
control all possible extraneous
variables to be sure of the relationship
between the independent and dependent
variables but this does come at a cost
of external validity to a world in which
the variables of interest will almost
always occur in the presence of other
extraneous variables and timing the
world changes with time and so studies
conducted in the past may not have
external validity to the world today for
example a study conducted sixty years
ago on sexism in the workplace may have
produced very different results than a
similar study conducted today and what
about threats to internal validity we'll
go over a few more here since internal
validity can involve such a wide variety
of factors within a study so the thing
to remember here is that anything that
reduces the studies ability to establish
a relationship between the dependent and
independent variable reduces its
internal validity so starting with
selection bias selection bias can be a
problem for the same reasons that
participant characteristics can be a
problem for external validity if we are
comparing two groups of participants we
want to make sure the two groups are as
similar to each other as possible at the
beginning of the study so that
differences in the characteristics of
participants don't affect our results
for example if one group consists of
college undergrads volunteering for
extra credit and the other group was
recruited from flyers at a local arcade
we may find that the two groups differ
in their level of education
motivation and possibly IQ not saying
that those who hang out at the arcade
have low IQs just that there may be a
larger proportion of individuals with
higher IQs in a group that is pursuing
an education and putting forth the
outside effort to earn extra credit next
we have sample size having too few
participants in the study can mean that
the statistics don't have enough power
to produce results we can trust in other
words our findings are more likely to be
the result of chance if we are basing
them on only a few individuals
confounding this occurs when an
extraneous variable we did not control
for has an effect on our results in
other words something other than the
independent variable is affecting the
dependent variable in history history
refers to events outside of the study or
between a pretest and a post-test having
an effect on how participants respond
this could be something as significant
as a natural disaster or as simple as a
participant reading a book on
memorization skills during a study on
memory maturation maturation is a
natural process in which participants
change between a pretest or post-test or
during the course of a study in which
multiple measurements are made it may
simply be that they got older in a study
that spans years or that they became
fatigued or hungry during testing
maturation is similar to history and
that both affect how a participant
responds in a study but they differ in
that maturation is internal
and is a natural course of things while
history has to do with an external event
of some kind
instrumentation this occurs when the
instrument or measure we are using in a
study changes in some way over the
course of a study if the measure is
different at the beginning than it is at
the end it could possibly be producing
different results instrumentation can
occur for example if an experimenter
decides to tweak a test to make it
better or if the springs on a scale
start to wear out it can also occur in
observational measures if the observer
gets better with practice at detecting
certain behaviors over the course of a
study next we have testing also
sometimes referred to as practice
effects in studies that use the same or
similar measure for a pretest and a
post-test run the risk of practice
effects if a participant is given a math
test for a pretest and a post-test she
is likely to perform better the second
time that she has seen the test before
it could be a matter of the participant
getting better with repeated practice or
it could simply be familiarity with a
test that leads to better performance
and finally we have attrition or
mortality attrition refers to
participants dropping out during the
course of a study not only does this
become a problem for sample size but
there may also very likely be a reason
that some participants drop out and
others continue on with the study for
example participants who drop out may
have a more difficult time with
transportation to and from the location
of a study and therefore may be of lower
socioeconomic
Attis this factor that differs between
those who stick around and those who
don't
may have an impact on the sorts of
findings we end up with if the study
involves a pretest and a post-test the
group who took the pretest at the
beginning of the study may differ from
the group who took the post-test at the
end also the factor determining which
participants are still in the study may
be exerting a sort of selection bias on
the characteristics of the participants
our results are based on which is a
threat to the internal validity of our
results but this can also create a
threat to external validity if the
participant sample our results are based
on differs in a significant way from the
general population with careful
consideration of the potential threats
to internal and external validity when
designing your study you should be
confident that your results reflect a
true relationship between your dependent
and independent variables and that those
results are generalizable to most other
populations and contexts
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