The document discusses various experimental research designs including completely randomized design, randomized block design, Latin square design, and other designs. It provides definitions and explanations of key concepts in experimental research such as experimental versus control groups, independent and dependent variables, randomization, and threats to internal and external validity. Examples of different types of experimental designs are given, including pre-experimental, quasi-experimental, and true experimental designs. Characteristics and advantages and disadvantages of each design type are also summarized.
This presentation is for educational purpose only. I do not own the rights to written material or pictures or illustrations used.
This is being uploaded for students who are in search of, or trying to understand how a quasi-experimental research design should look like.
This presentation is for educational purpose only. I do not own the rights to written material or pictures or illustrations used.
This is being uploaded for students who are in search of, or trying to understand how a quasi-experimental research design should look like.
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Experimental ProceduresThe specific experimental design procedur.docxgitagrimston
Experimental Procedures
The specific experimental design procedures also need to be identified. This discussion involves indicating the overall experiment type, citing reasons for the design, and advancing a visual model to help the reader understand the procedures.
• Identify the type of experimental design to be used in the proposed study. The types available in experiments are pre-experimental designs, quasi-experiments, true experiments, and single-subject designs. With pre-experimental designs, the researcher studies a single group and provides an intervention during the experiment. This design does not have a control group to compare with the experimental group. In quasi-experiments, the investigator uses control and experimental groups but does not randomly assign participants to groups (e.g., they may be intact groups available to the researcher). In a true experiment, the investigator randomly assigns the participants to treatment groups. A single-subject design or N of 1 design involves observing the behavior of a single individual (or a small number of individuals) over time.
• Identify what is being compared in the experiment. In many experiments, those of a type called between-subject designs, the investigator compares two or more groups (Keppel & Wickens, 2003; Rosenthal & Rosnow, 1991). For example, a factorial design experiment, a variation on the betweengroup design, involves using two or more treatment variables to examine the independent and simultaneous effects of these treatment variables on an outcome (Vogt, 2011). This widely used behavioral research design explores the effects of each treatment separately and also the effects of variables used in combination, thereby providing a rich and revealing multidimensional view. In other experiments, the researcher studies only one group in what is called a within-group design. For example, in a repeated measures design, participants are assigned to different treatments at different times during the experiment. Another example of a within-group design would be a study of the behavior of a single individual over time in which the experimenter provides and withholds a treatment at different times in the experiment to determine its impact.
• Provide a diagram or a figure to illustrate the specific research design to be used. A standard notation system needs to be used in this figure. A research tip I recommend is to use a classic notation system provided by Campbell and Stanley (1963, p. 6):
X represents an exposure of a group to an experimental variable or event, the effects of which are to be measured.
O represents an observation or measurement recorded on an instrument.
Xs and Os in a given row are applied to the same specific persons. Xs and Os in the same column, or placed vertically relative to each other, are simultaneous.
The left-to-right dimension indicates the temporal order of procedures in the experiment (sometimes indicated with an ...
Design of experiments is the most common Research design will wide reliability. It is mostly applicable in scientific lab type of research. This method is not applicable for descriptive research.
It involves both qualitative and quantitative data sets. The researchers can manipulate, control, replicate and randomize the experimental variables.
There are several types of experimental design depending on the selection of control, test and standard groups and their experimental setting.
The slides also show the guidelines regarding design of research proposal, Literature survey and important ethics in research. Guiding protocol to prepare a research and review article is also discussed.
Steps in conducting a RCT
1. Drawing up a protocol
2. Selecting Reference & Experimental population
3. Randomization
4. Manipulation or Intervention
5. Follow up
6. Assessment of outcome
1. Drawing up a protocol
Aims and objectives of the study
Questions to be answered
Criteria for the selection of study and control groups
Size of the sample & allocation of subjects in both groups
Treatment to be applied - when, where, how
Standardization of working procedures and
Schedules as well as responsibilities of persons involved in the trial up to the stage of evaluation of outcome of the study.
2. Selecting Reference and Experimental Populations
Reference or target population - Population to which the findings of the trial, if found successful, are expected to be applicable (Eg: drugs, vaccines, etc.)
Experimental or Study population
Derived from the Reference population
Has same characteristics as the Reference population
Actual population that participates in the experimental study
Must give informed consent - Should be qualified or eligible for the trial
3. Randomization
Heart of the control trial
Procedure:
Participants are allocated into study and control groups
Eliminates bias and allows comparability
By random allocation every individual gets an equal chance for being allocated in to either groups.
4. Manipulation/ Intervention
Having formed the study and control group, the next step is to intervene or manipulate the study (experimental) group by deliberate application or withdrawal or reduction of a suspected causal factor
Eg: Drug, Vaccine, Dietary component, a habit
5. Follow up
Implies examination of the experimental and control group subjects at defined intervals of time in a standard manner, with equal intensity, under the same given circumstances in the same time frame till final assessment of outcome.
Attrition:
Inevitable losses to follow up (death, migration, loss of interest)
6. Assessment
a. Positive results:
Reduced incidence or severity of disease
Reduced cost to health service
Appropriate outcome in the study
b. Negative results:
Increased severity or frequency of side effects
Complications
Deaths
BIAS:
Any systematic error in the determination of association and outcome.
Bias may arise from errors of assessment of outcome due to human element
Subjective bias
Observer bias
Evaluation bias
1. Subjective Bias:
Participants, subjectively feel better or report improvement if they knew they were receiving a new form of treatment. This is known as “Subject variation”.
2. Observer Bias:
Investigator measuring the outcome of a therapeutic trial may be influenced if he knows beforehand the particular procedure or therapy to which the patient has been subjected.
3. Evaluation Bias:
Investigator may subconsciously give a favorable report of the outcome of the trial.
Blinding:
1. Single Blind Trial: Participant
2. Double Blind: Partcipant + Investigator
3. Triple Blind: Participant + Investigator + Data Analyzer
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3. Research design
It is master plan specifying the methods and
procedures for following for collecting and
analyzing the needed information in a research
study
4. Experimental research design
…the researcher selects participants and divides
them into two or more groups having similar
characteristics and, then, applies the
treatment(s) to the groups and measures the
effects upon the groups
5. Uniqueness of experimental
research design
• Experimental Research is unique in two
important respects:
1) Only type of research that attempts to influence a
particular variable
2) Best type of research for testing hypotheses about
cause-and-effect relationships
• Experimental Research looks at the following
variables:
• Independent variable (treatment)
• Dependent variable (outcome)
6. Major Characteristics of
Experimental Research
• The researcher manipulates the independent variable.
• They decide the nature and the extent of the
treatment.
• After the treatment has been administered,
researchers observe or measure the groups receiving
the treatments to see if they differ.
• Experimental research enables researchers to go
beyond description and prediction, and attempt to
determine what caused effects.
7. Essential Characteristics of
Experimental Research
Comparison of Groups:
• The experimental group receives a treatment of some sort while
the control group receives no treatment.
• Enables the researcher to determine whether the treatment has
had an effect or whether one treatment is more effective than
another.
Manipulation of the Independent Variable:
• The researcher deliberately and directly determines what forms the
independent variable will take and which group will get which form.
8. Essential Characteristics of
Experimental Research
Randomization
• Random assignment is similar but not identical to random selection.
• Random assignment means that every individual who is
participating in the experiment has an equal chance of being
assigned to any of the experimental or control groups.
• Random selection means that every member of a population has an
equal chance of being selected to be a member of the sample.
• Three things occur with random assignments of subjects:
1) It takes place before the experiment begins
2) Process of assigning the groups takes place
3) Groups should be equivalent
9. Simple Random Sample
Every subset of a specified size n from the
population has an equal chance of being
selected
10. Stratified Random Sample
The population is divided into two or more
groups called strata, according to some
criterion, such as geographic location, grade
level, age, or income, and subsamples are
randomly selected from each strata.
11. Cluster Sample
The population is divided into subgroups
(clusters) like families. A simple random
sample is taken of the subgroups and then all
members of the cluster selected are surveyed.
12. Systematic Sample
Every kth member ( for example: every 10th
person) is selected from a list of all population
members.
13. Types of Designs
The basic structure of a research study . . .
particularly relevant to experimental research
Types of experimental designs (Campbell & Stanley,
1963)
Pre-experimental
Quasi-experimental
True experimental
14. Pre-experimental
design
Quasi –
experimental
design
True experimental
design
•One shot case design
•One group pretest-
posttest design
•FEATURES
•Manipulation of
independent variables
•Limited control over
the extraneous
variables
•No randomization and
control group
•Non randomized block
design
•Time series design
•FEATURES
•Manipulation of
independent variable
•Absence of either
randomization/ control
group
•Post –test only control
design
•Pre –test– posttest
control group design
•Factorial design
•Randomized block
design
•Cross over design
•FEATURES
•Manipulation of
independent variable
•Presence of control
group
•Randomization
15. Variable
a concept (e.g., intelligence, height, aptitude) that
can assume any one of a range of values
Independent variable - an activity of
characteristic believed to make a difference with
respect to some behavior
Ex - experimental variable, active variable, cause,
treatment
Dependent variable - the change or difference
occurring a result of the independent variable
Ex- Assigned variable, effect, outcome, posttest
16. Steps in conducting
experimental research
Decide if an experiment addresses the
research problem
Form hypotheses to test cause-effect
relationships
Select an experimental treatment and
introduce it
Identify study participants choose a type of
experimental design
Conduct the experiment
Organize and analyze the data
Develop an experimental research report
17. The concept of validity…the experiment tests the
variable(s) that it purports to test
Threats to validity…
Internal: factors other than the independent
variable that affect the dependent variable(
campbell 1963)
External: factors that affect the generalizability of
the study to groups and settings beyond those of the
experiment
18. Threats of internal validity
History
Maturation of subjects
Testing
Instrumentation change
Mortality
Selection bias – maturation interaction
19. History
Some event beside the experimental treatment
occurs during the course of the study , and this
event even influence dependent variable.
20. Maturation of subjects
Experimental research is carried on long
period of time over a group of subjects there
may be changes in the subjects in different
ways.
Increase in height, weight.
Ex. Nutritional protocol on height & weight of
malnourished children
21. Testing
Effect of taking a pretest of subjects’
performance of post test.
The effect of taking a pretest may sensitize an
individual and improve the score of the post
test.
Individuals generally score higher during
second test regardless of treatment.
22. Instrument change
Changes in instruments, calibration of
instruments, observers or scorers may cause
changes in the measurements
23. Mortality
Loss or dropout of the subject during course
of the study
The longer period of study the more chance for
dropout.
Ex. longitudinal study
24. Selection bias
Subjects are not selected randomly for
participation in groups , there is a possibility of
comparison may not equivalent.
25. External validity
Hawthorne effect
Subjects may behave in particular manner
because they are aware that they are being
observed
26. Experimental effect
Threat to study results when researcher’s
characteristic , mannerism, behavior may
influence subject matter.
27. Reactive effect of pretest
Effect of pretest occurs when subjects have
been sensitized to the treatment because of
taking pretest.
Ex – pretest may sensitize to learn about HIV/
AIDS irrespective of health education is
provided
28. Novelty effect:
Treatment is new , the subjects and researchers act
different ways
People : Generalization is not applicable depending
upon the race.
Place: Generalization not possible for people living
in rural and urban area
Time : older results can not be generalized over
periods of time.
29. Most common way to eliminate
threats
Experimental control Experimental control attempts to
predict events that will occur in the experimental setting
by neutralizing the effects of other factors.
Physical Control Gives all subjects equal exposure to
the independent variable. Controls non-experimental
variables that effect the dependent variable.
Selective Control Indirectly manipulate by selecting in
or out variables that cannot be controlled
Statistical Control Variables not conducive to physical
or selective manipulation may be controlled by statistical
techniques.
30. Criteria for evaluating
experimental Research
Does the experiment have a powerful
intervention?
Does it employ few treatment groups (e.g. only
two)?
Will participant profit from the intervention?
Is there a systematic way the researcher
derived the number of participants per group?
31. Criteria for evaluating
experimental Research
Were there an adequate number of
participants used in the study?
Were valid, reliable, and sensitive measures or
observations used?
Did the study control for extraneous factors?
Did the researcher control for threats to
internal validity?
32. Types of pre experimental
design
The One-Shot Case Study
A single measure is recorded after the treatment
in administered.
Study lacks any comparison or control of
extraneous influences.
To remedy this design, a comparison could be
made with another group.
Diagrammed as:
33. The One-Group Pretest-Posttest Design
Subjects are measured before and after treatment is
administered.
Uncontrolled-for threats to internal validity exist.
To remedy this design, a comparison group could be
added.
Diagrammed as:
34. The Static-Group Comparison
Design
Use of 2 existing, or intact groups.
Experimental group is measured after being
exposed to treatment.
Control group is measured without having been
exposed to the treatment.
Diagrammed as:
35. The Static-Group Pretest-Posttest Design
Pretest is given to both groups.
“Gain” or “change” = pretest score -
posttest score.
Better control of subject characteristics
threat.
A pretest raises the possibility of a testing
threat.
36. Pre experimental design
Advantages Disadvantages
Very simple
Convenient to conduct in
natural settings
Suitable for beginners
Weak design to establish
casual relationship between
independent and dependent
variable
Very little control over the
research
Higher threat to internal
validity
37. Characteristic of quasi
experimental research design
Manipulation of independent variable
Lack of one / two essential character of true
experimental design
Quasi independent variable used instead of
true independent variable.
38. Types of quasi experimental
design
Nonequivalent /Non randomized control group
design
O X O
O O
random assignment of intact groups that are
pretested ( O ), exposed to a treatment ( X )
and then posttested ( O )
Time-series design
O O O O X O O O O
a single group is pretested ( O ) repeatedly until
pretest scores are stable, exposed to a
treatment ( X ) and, then, is repeatedly
posttested ( O )
40. Characteristics of true
experimental design
Manipulation – control of independent
variable by the researcher through treatment/
intervention
Control – the use of control group and
extraneous variables on the dependent
variable
Randomization – every subject gets equal
chance being assigned to experimental and
control group.
41. Advantages Disadvantage
s
Most powerful design to establish
causal relationship between
independent and dependent
variable
Cannot be replicated in studies
conducted in human begins due
ethical problems
Purity of the observation Many of the human variables
neither have valid measurable
criteria nor instruments to
measure.
Create conditions in a short period
of time that may take years to
occur naturally
Studies conducted in hospital /
community difficult to control the
extraneous variable
Conducted in laboratory,
experimental unit, specialized
research setting
Very difficult get co operation for
treatment/ intervention
42. True Experimental
• The essential ingredient of a true experiment is
random assignment of subjects to treatment groups
• Random assignments is a powerful tool for
controlling threats to internal validity
– The Randomized Posttest-only Control Group Design
• Both groups receiving different treatments
– The Randomized Pretest-Posttest Control Group
Design
• Pretest is included in this design
– The Randomized Solomon Four-Group Design
• Four groups used, with two pre-tested and two not pre-tested
43. The Randomized Posttest-Only
Control Group Design
Experimental group tested after treatment exposure.
Control group tested at the same time without exposure
to experimental treatment.
Includes random assignment to groups.
Threats to internal validity – mortality, attitudinal,
implementation, data collector bias, location and history.
44. Example of a Randomized Posttest-
Only Control Group Design
45. The Randomized Pretest-
Posttest Control Group Design
Experimental group tested before and
after treatment exposure
Control group tested at same two times
without exposure to experimental
treatment
Includes random assignment to groups.
Pretest raises the possibility of a pretest
treatment interaction threat
46. Example of a Randomized Pretest-
Posttest Control Group Design
47. The Randomized Solomon Four-
Group Design
Combines pretest-posttest with control group
design and the posttest-only with control
group design.
Provides means of controlling the interactive
test effect and other sources of extraneous
variation.
Does include random assignment.
Weakness: requires a large sample.
48. Example of a Randomized Solomon
Four-Group Design
50. Solomon four-group design
R O X1 O
R O X2 O
R X1 O
R X2 O
four groups are formed by random assignment
( R ) of participants, two groups are pretested
( O ) and two are not, one pretested and one
un pretested group receive the experimental
treatments ( X1, X2 ), each group is are
administered a posttest on the dependent
variable, and posttest scores are compared to
determine effectiveness of treatments
51. Factorial design
involve two or more independent variables
with at least one independent variable being
manipulated by the researcher
two-by-two factorial design (four cells)
2 X 2
two types of factors (e.g., method of
instruction) each of which has two levels (e.g.,
traditional vs. innovative)
52. Using a Factorial Design to Study
Effects of Method and Class Size on
Achievement
55. Randomized block design
Principle of local control along with other two
principle of experimental design
subjects are first divided into groups
each group the subjects are relatively
homogeneous
The number of the equal in each group
Extraneous variable is fixed
57. Cross over design / repeat
measure design
Subjects exposed more than one treatment
Subjects randomly assigned to different orders
of treatment
Equal distribution of character among the
group
58. Latin square design
very frequently used in agricultural research.
An experiment has to be made through which
the effects of five different varieties of
fertilizers on the yield of a certain crop.
out put occur depend on soil not only on the
fertilizer
L.S. design is used when there are two major
extraneous factors such as the varying soil
fertility and varying seeds
60. Other designs
Descriptive design
Univariant descriptive design – the frequency
of occurrence of the phenomenon
Ex – the experience of patients suffering from
rheumatoid arthritis
Prevalence of vitamin D deficiency among
pregnant women
Used to identify, describe the perception,
awareness, behavior, attitude, knowledge and
practice of people.
61. Exploratory design
Used to identify , explore and describe the
existing phenomenon and its related factors
Ex . contributing factors of sleep disturbance
among patients admitted in ICU
62. Comparative design
Comparing and contrasting two or more
sample of subjects on one or more variable
Attributes-Knowledge, perception, attitudes
Physical and psychological symptoms
Ex KAP on Vitamin D among antenatal
mothers
63. Prospective Cohort Study
Some have the
factor (c)
Population
(lapse of time)
Begin enquiry here
& work forwards
Sample people
without
the disease
Disease (a)
Disease (b)
No Disease
No Disease
Statistic = Relative Risk [RR] = (a/c) divided by (b/d)
This shows the ratio of incidence in exposed
compared to non-exposed.
RR > 1 implies a hazard;
RR < 1 implies a protective factor
95% CI are usually presented:
e.g., RR = 1.9 (95% CI 1.5, 2.3)
Note: as you begin
with people who do not
have the disease, you
can calculate incidence
but not prevalence.
(Prevalence would be
underestimated as you
omitted existing
cases)
Some do not (d)
Outcomes
64. Retrospective Case-Control Study
Population
Select
Cases
(have the
disease)
Sample of
Controls
(who do not
have the
disease)
Exposed (c)
Exposed (a)
Not Exposed (d)
Not Exposed (b)
Begin enquiry here
& look backwards
Statistic = Odds Ratio [OR] = (a/b) divided by (c/d)
This shows how many times more likely were the cases
to have been exposed than the controls.
OR interpreted in same way as RR
Review
history
Review
history
Note: as you begin
with people who already
have the disease, you
cannot calculate
incidence or prevalence
65. Developmental research
design
Cross sectional design
Researcher collect data at particular point of
time
Ex –assessing the awareness on swine flu
among people of an area
Longitudinal design
Collect the extended period of time
follow up studies
66. Other type of trails
Pilot studies and feasibility studies– run before
a large trail take place
Screening trails – cervical cancer screening
trail
Prevention trails – breast cancer prevention
trail.
Trails looking at causes and patterns of
disease
Case control studies
Sequential trails
67. Conclusion
There are several research designs and the
researcher must decide in advance of
collection and analysis of data as to which
design would prove to be more appropriate for
his research project.
68. Applying What you Have
Learned: An Experimental Study
Review the article and look for the following:
The research problem and use of quantitative
research
Use of the literature
The purpose statement and research
hypothesis
Types and procedures of data collection
Types and procedures of data analysis and
interpretation
The overall report structure
Editor's Notes
Experimental research = try something and systematically observe what happens.Two basic conditions of formal experiments – 1st, at least 2 (or more) conditions or methods are compared to assess the effect of treatments (independent variable). 2nd, independent variable directly manipulated by researcher.
Experimental group receives a treatment.Control/comparison group receives no/different treatment. Become yardstick to determine whether the treatment is effective/not.Researcher actively manipulates a treatment (independent variable) – deliberately & directly determines what forms (treatment) and which group will get.Independent variables that can be manipulated – teaching method, type of counseling, learning activities, etc.Independent variables may be established in several ways – (i) one variable vs. another, (ii) presence vs. absence, (iii) varying degrees of the same form.
Intended to eliminate the threat of extraneous or additional variables.Ensures that groups formed are equivalent at the beginning of an experiment.No guarantee of equivalent groups unless both groups (experimental & control) are sufficiently large.
One group only (experimental group) that received treatment. No control/comparison group = to effectiveness cannot be measured.No pretest, researcher knows nothing about the subject before treatment thus does not know whether it is effective or not.
Pretest exist, so does nine uncontrolled-for threats (history, maturation, instrument decay, data collector characteristics, data collector bias, testing, statistical regression, attitude of subjects & implementation.Researcher would not know if any differences between pretest and posttest due to treatment given/threats.
a.k.a. nonequivalent control group designSubjects are being formed but not randomly assigned.Diagrammed shows better control (history, maturation, testing & regression) but still not a good design as the possibility of other threats (mortality, location & subject characteristics) occur.
? Better control = changed being analyzed but still remain a threat as it depends on initial performance (pretest improve or less).
? True=random assignment to treatment (independent variable) group.Random assignment best tool to control threat to internal validity.
Two groups – experimental and control/comparison group which is formed by random assignment.There are still threats but can sometimes be controlled by appropriate modifications.Important to keep clear distinction between random selection and random assignment.Random selection is intended to provide a representative sample.Random assignment is intended to equate groups and often is not accompanying by random selection.
X1 represents exposure to treatment (independent variable).O refers to the measurement of the dependent variable (outcome).R represents random assignment of individual to groups.X2 represents control group.