What is the difference between internal and external validity in research?

  

Dont understand the question and would like some advice on referencing this question as well.
Quantitative Research
Experimental
Experimental Research
Cause and effect relationships are established by
manipulating the INDEPENDENT variable(s) and
observing the effect on the DEPENDENT variable.
Research design must control for the possible effects of
extraneous variables that could mask, enhance, or in
some way alter the effect of the independent variable on
the dependent variable.
Example:
General study description: Recruited
obese participants will spend 3 weeks in
a tightly controlled laboratory setting
Dependent Variable:
Weight Loss
Independent variable: food
intake
Independent variable:
exercise regimen
Internal & External Validity
Internal Validity: determined by the degree to which
the observed effects of the independent variable (IV) are
REAL and not caused by extraneous factors
Alternative explanations for the effect of the
independent variable (IV) on the dependent variable (DV)
threaten internal validity
KEY: controlling for the possible effects of extraneous
variables
Internal & External Validity
External Validity: determined by the ability to
generalize the study results beyond the study sample
Threats to Internal Validity
alternate

History
Maturation(children)
Testing
Instrumentation
Selection bias
explanations
Mortality/attrition
Hawthorne
Placebo
blind vs. double blind
Implementation
fidelity
Control Strategies
Threats to Internal Validity
Randomly select participants from a well-defined study
population
Randomly assign selected participants to groups
Include non-treatment control groups in the research
design
Final Point on Int/Ext Validity
External validity can not exist without internal validity
If the results of the study are not internally valid, there is
nothing to generalize.
Researchers should be always be concerned about
ensuring internal validity first.
Choosing a Design
Identify and use a design that
Controls as many extraneous variable as possible
Will still be practical and feasible to implement
Experimental Designs
X =independent variable (the treatment)
X2 or Y = additional treatments
O = measurement of the dependent variable (an
observation)
Each observation or measurement is numbered indicating
order (O1, O2, O3 )
R = random assignment
Hawthorne effect
Examples of Types of Randomization
(Jacobsen, 2012, figure 13-6)
Non-experimental Designs
Survey research designs
Cross sectional
Longitudinal
Trend studies track population changes over time
Cohort study follow a particular group or subgroup over time
Youth Risk Behavior Survey (YRBS)
http://www.cdc.gov/HealthyYouth/yrbs/pdf/us_injury_trend_yrbs.pdf
National Longitudinal Study of Adolescent Health (Add Health)
http://www.cpc.unc.edu/projects/addhealth/design
Panel study examine the same group of people over time at the
individual level
Panel Study of American Religion and Ethnicity (PS-ARE) http://www.psare.org/index.asp
Framework for a
Cohort Study
(Jacobsen, 2012, figure 12-2)
Non-experimental Designs
Correlational study
Identifies relationships and the degree or closeness of those
relationships
A correlation exits if, when one variable increases another
variable either increases or decreases in a somewhat
predictable way.
What is the relationship between participation in intramural
sports and BMI among WOU students?
What is the relationship between religiosity and age of sexual
initiation in seventh grade students?
Types of Relationships
Linear relationships
Positive: both variables move in the same direction (one
variable increases as the other increases)
Negative: one variable moves in the opposite direction of the
other (one variable increases while the other decreases)
Curvilinear relationships
Assessing correlation
Rough measure = scatter plot
Statistic = correlation coefficient or r (describes a sample
of paired values from two different variables)

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Measures the closeness with which the pairs of values fit a
straight line
Range of values for r = +1.0 to -1.0
When r = 0, there is no correlation
1.0 = perfect correlation
Interpreting a Scatter Plot
Line of best fit
http://staff.argyll.epsb.ca/jreed/math9/strand4/scatterPlot.h
tm
Relationships
cause & effect
Correlation of ice cream sales and death by drowning (r
= +.86)
In the months when ice cream sales go up, so do deaths
by drowning and likewise when ice cream sales go down,
so do deaths by drowning
A.) Does ice cream consumption cause drowning deaths
to increase? or B.) Do drowning deaths cause surviving
family members and friends to eat more ice cream?

Introduction:
In the field of research, there are various methods that can be used to collect data. One of the methods is quantitative research which involves the collection and analysis of numerical data. Experimental research is a type of quantitative research where cause and effect relationships between independent and dependent variables are established. In this type of research, control for extraneous variables is of utmost importance to determine the validity of the results.

Description:
Experimental research involves investigating the relationship between an independent variable and a dependent variable while controlling for extraneous variables. The independent variable is manipulated to observe the effect on the dependent variable. The study design must control for the effects of extraneous variables that could interfere with the results. Internal validity is established by controlling for extraneous variables while external validity refers to the ability to generalize the study results beyond the sample. One of the designs used in experimental research is the randomized controlled trial. Researchers must be concerned with ensuring internal validity first before external validity can be established. Non-experimental designs such as correlational studies and survey research can also be used to identify relationships and the degree of closeness between variables.

Objectives:

1. To understand the basics of experimental research design.
2. To know the techniques to ensure internal and external validity.
3. To recognize the different types of experimental and non-experimental designs.
4. To explore the application of correlational studies.

Learning Outcomes:

By the end of this content, the audience will be able to:

1. Define experimental research design and explain why controlling extraneous variables is critical.
2. Describe how internal and external validity is ensured in experimental research design.
3. Identify the different types of experimental and non-experimental designs and differentiate between them.
4. Demonstrate an understanding of correlational study design and the types of relationships it identifies.

Reference:

The information is based on the content provided in Jacobsen, K. H. (2012). Introduction to health research methods. Jones & Bartlett Publishers.

Solution 1:

To establish the cause and effect relationship between food intake and exercise regimen on weight loss, a quantitative research experimental design can be used. The study will recruit obese participants who will spend 3 weeks in a tightly controlled laboratory setting. The independent variables will be food intake and exercise regimen, while weight loss will be the dependent variable. To control for the possible effects of extraneous variables that could interfere with the effect of independent variables on weight loss, researchers can select participants randomly from a well-defined study population, randomly assign selected participants to different groups, and include non-treatment control groups in the research design. The study can also use the Hawthorne effect to minimize selection bias explanations. Data can be collected through observations, recordings, and measurements, and analyzed using statistical methods.

Solution 2:

To identify the relationship between intramural sports participation and BMI among WOU students, a non-experimental correlational study can be conducted. The study will collect data on the participation in intramural sports and BMI from a sample of WOU students. The independent variable is participation in intramural sports, while BMI is the dependent variable. The researchers will use survey research designs, cross-sectional studies and trend studies to track population changes over time, ask questions about student’s participation in intramural sports over a period of time, and identify if there is any correlation between intramural sports participation and BMI. Data can be analyzed using statistical methods, and the degree of relationship between variables can be determined as a linear relationship (positive or negative).

Suggested Resources/Books:

1. “Experimental Design: Procedures for the Behavioral Sciences” by Roger E. Kirk
2. “Research Methods and Statistics in Psychology” by Hugh Coolican
3. “Quantitative Research Methods for Communication: A Hands-On Approach” by Jason S. Wrench

Similar Asked Questions:

1. How do you establish cause and effect relationships in experimental research?
2. What is the difference between internal and external validity in research design?
3. What are some common threats to internal validity in experimental research?
4. What is the importance of controlling extraneous variables in experimental research?
5. What are some examples of non-experimental research designs and when are they used?

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